Operationalising equity in higher education: Development and validation of a university social responsibility scale

Operationalising equity in higher education: Development and validation of a university social responsibility scale | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Operationalising equity in higher education: Development and validation of a university social responsibility scale Lucirene Rangel Lyne, Mario Alberto Salazar-Altamirano, Carmen Anaya-Aguilar, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9151678/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 20 You are reading this latest preprint version Abstract Higher education systems are undergoing rapid digital and institutional transformation, intensifying concerns about equity, inclusion, and sustainable learning conditions. Although University Social Responsibility (USR) has increasingly been linked to the Sustainable Development Goals, particularly SDG 4, the literature still lacks robust measurement instruments to capture how equity-oriented institutional practices associated with USR are experienced within universities. This study develops and validates a multidimensional scale designed to measure students' perceptions of institutional conditions that support equitable and inclusive learning environments in higher education. The instrument was developed through a sequential mixed-method process. First, qualitative data from five student focus groups (n = 40) were analysed to identify key institutional domains associated with socially responsible universities. Second, content validity was evaluated by a panel of five experts in higher education management and psychometrics. Third, a pilot study with undergraduate students (n = 154) enabled exploratory factor analysis, followed by confirmatory factor analysis using data from a larger survey of Generation Z students (n = 583) enrolled in business programmes at a public university in northern Mexico. Results support a seven-factor structure encompassing learning infrastructure, health and wellbeing, institutional benefits, professional development, social and environmental engagement, integral formation and inclusion, and identity and belonging. The model demonstrates strong psychometric properties, including satisfactory reliability, convergent validity, and discriminant validity. By capturing students' perceptions of institutional conditions related to university social responsibility and educational equity, the proposed scale provides universities with a diagnostic tool to systematically assess and improve inclusive and sustainable learning environments. University social responsibility Higher education governance Equity in higher education Inclusive education Scale development Generation Z students Figures Figure 1 Figure 2 Figure 3 1. Introduction Since the mid-twentieth century, higher education has been recognised as one of the key drivers of economic development, social mobility, and the consolidation of democratic societies [ 1 ]. Following the expansion of mass higher education in the post-war period, universities ceased to be conceived exclusively as spaces for elite formation. Instead, they became institutions capable of promoting regional development, scientific innovation, and social cohesion [ 2 ]. This structural change has recently been reinforced through the incorporation of international agendas that emphasise the social responsibility and public impact of educational institutions [ 3 ]. Under this premise, international organisations such as UNESCO have emphasised that higher education constitutes a public good and a human right, essential for achieving more equitable and sustainable societies [ 4 ]. Nevertheless, despite advances in educational expansion, structural inequalities continue to limit access, retention, and academic success for broad sectors of the population across multiple regions of the world [ 5 ]. Against this backdrop, the emergence of digital transformation has reconfigured the debate on educational equity [ 6 ]. The accelerated adoption of virtual platforms, hybrid learning ecosystems, learning analytics, and tools based on artificial intelligence has redefined how knowledge is produced, distributed, and accessed [ 7 ]. Although these technological innovations have the potential to expand educational opportunities and make learning pathways more flexible, they may also intensify existing inequalities when access to digital infrastructure, technological skills, or institutional resources is uneven [ 8 ]. According to Alenezi et al. [ 9 ], the digitalisation of higher education does not in itself guarantee inclusive educational processes; rather, it requires institutional frameworks that integrate technology, pedagogy, and governance to prevent new forms of educational exclusion. According to global estimates, more than 250 million children and young people remain outside formal education systems. In contrast, millions more face discontinuous or precarious educational trajectories, particularly in emerging socio-economic contexts [ 10 ]. Consequently, the contemporary debate on educational equity has evolved from approaches centred on access towards more complex perspectives that analyse the institutional conditions shaping the overall student experience [ 11 ]. For Taff and Clifton [ 12 ], inclusion in higher education depends on multiple interrelated factors, among which the availability of adequate infrastructure, institutional support systems, physical and psychological wellbeing services, professional development opportunities, and cultural environments that foster participation and a sense of belonging are particularly significant. In other words, educational equity is not limited to allowing diverse students to enter universities but rather involves creating institutional ecosystems capable of sustaining meaningful and successful educational trajectories. In this regard, universities are increasingly understood as social ecosystems in which organisational, educational, and social dimensions converge to influence learning outcomes and students' human development [ 13 ]. One conceptual approach that has sought to address this complexity is the University Social Responsibility (USR) framework. Inspired by the principles of organisational social responsibility and stakeholder theory, this framework proposes that universities should manage the impacts they generate in their environment in an integrated manner, across organisational, educational, cognitive, and social dimensions [ 14 ]. From this perspective, USR goes beyond extension activities or volunteering by integrating principles of sustainability, ethics, and social and environmental engagement into the core functions of universities. In this sense, Vallaeys and Rodríguez [ 15 ] argue that universities must move from assistance-based approaches towards impact management systems that articulate institutional governance, academic training, and engagement with society. Nevertheless, although USR has been conceptualised as a framework for institutional governance, its empirical operationalisation requires examining how these commitments translate into concrete experiences for university stakeholders [ 16 ]. In this regard, students’ perceptions constitute a relevant empirical indicator for evaluating the extent to which institutional policies related to inclusion, wellbeing and social responsibility are effectively reflected within the educational environment. Despite conceptual progress in the USR field, significant challenges remain in its empirical operationalisation. One of the principal limitations identified in the literature is the scarcity of psychometrically validated instruments that allow a systematic evaluation of how universities translate their declarative commitments to social responsibility into concrete institutional practices [ 17 ]. Numerous studies on USR continue to rely on descriptive analyses, case studies, or fragmented institutional evaluations, which complicates comparisons between institutions and the construction of empirical evidence regarding the impacts of these policies [ 18 ]. This need is particularly evident in the Latin American and Ibero-American context, where universities in the region have increasingly adopted discourses of social responsibility, sustainability, and inclusive education. However, the institutional implementation of these principles is often characterised by isolated initiatives or peripheral programmes that are not necessarily integrated into university governance systems [ 19 ], remaining largely at the level of discourse. Moreover, Vallaeys et al. [ 20 ] indicate that most Ibero-American universities continue to concentrate their efforts on social outreach activities or volunteering, without developing systematic evaluation mechanisms capable of measuring their impact on the educational experience and student wellbeing. At the same time, studies on higher education in Latin America show that socio-economic inequalities continue to strongly condition university access and retention, particularly among first-generation students and socially vulnerable groups [ 21 ]. Despite these challenges, existing empirical instruments for evaluating the university environment tend to focus on specific dimensions of the student experience, such as academic satisfaction, institutional climate, and university services [ 22 ]. Although these approaches have made valuable contributions, they often address these dimensions in isolation, without integrating them into an analytical framework that explains how institutional structures simultaneously influence educational equity, student wellbeing, and professional development. Consequently, a gap remains in the literature regarding the development of multidimensional measurement models that capture the interactions among university governance, social inclusion, and learning experiences within higher education institutions [ 23 ]. In response to this gap, the present study proposes the development and validation of a multidimensional USR scale designed to measure the institutional conditions that foster equitable and sustainable learning environments. Based on the triangulation of international conceptual frameworks on USR, qualitative evidence derived from students’ voices, expert validation and a psychometric validation process, the instrument conceptualises the institutional conditions associated with university equity as a multidimensional framework composed of seven interrelated dimensions: learning infrastructure, health and wellbeing, institutional benefits, professional development, social and environmental engagement, integral formation and inclusion, and identity and belonging. Accordingly, the objective of this research is to develop and validate a multidimensional scale that captures students' perceptions of institutional equity within the USR framework. Rather than directly measuring formal governance structures, the proposed instrument operationalises how institutional commitments associated with USR are manifested in students' educational experiences through practices related to inclusion, integral wellbeing, learning infrastructure, professional development, and social and environmental engagement. To achieve this purpose, the study adopts a sequential methodological design that combines qualitative and quantitative approaches. In a first phase, students' perceptions were explored through interviews and group dynamics to identify experiences and needs associated with USR within the institutional context. Subsequently, the items derived from this exploratory phase were subjected to a content validation process through the evaluation by a panel of experts in university management, social responsibility, and psychometrics, who analysed the clarity, relevance, and conceptual coherence of each indicator. Finally, the refined instrument underwent rigorous psychometric validation through exploratory and confirmatory factor analyses to ensure its reliability and validity as a tool for systematically evaluating the institutional conditions that shape inclusive and sustainable educational experiences. 2. Literature review The growing transformation of higher education systems has generated significant academic debate regarding the role of universities in promoting more equitable and sustainable societies. In this context, several theoretical approaches have sought to understand how universities can integrate principles of social responsibility, sustainability, and inclusion into their governance structures and student learning experiences. This section reviews the main conceptual developments linking USR to the construction of sustainable and equitable educational environments, providing the theoretical framework that underpins the proposed instrument. 2.1. University Social Responsibility and Sustainable Higher Education Over the past two decades, the literature on higher education has evolved towards a broader understanding of universities' social role [ 24 ]. Traditionally conceived as institutions primarily dedicated to the generation and transmission of knowledge, universities are now recognised as actors in promoting sustainable development, social cohesion, and responsible innovation [ 25 ]. This paradigm shift has encouraged the emergence of the concept of USR, understood as an institutional management approach aimed at evaluating and improving the educational, social, organisational, and environmental impacts generated by higher education institutions [ 26 ]. Several authors have noted that USR involves systematically managing the impacts that universities generate on their students, communities, and ecosystems, promoting institutional practices consistent with principles of equity, sustainability, and public ethics [ 15 ];[ 27 ]. Furthermore, the development of the concept of USR has been closely linked to the United Nations' global sustainability agenda. In particular, Sustainable Development Goal 4 (SDG 4) recognises education as a fundamental pillar for inclusive and sustainable development, emphasising the need to ensure equitable and quality learning opportunities throughout life [ 4 ]. In this regard, universities have been called upon to play a strategic role in the formation of socially responsible citizens capable of addressing contemporary social, environmental, and technological challenges [ 28 ]. At the same time, recent literature has begun to emphasise that universities' contribution to sustainable development does not depend solely on their academic or research programmes, but also on the institutional conditions that shape students' educational experiences [ 29 ]. Factors such as access to adequate infrastructure, academic support systems, wellbeing services, professional development opportunities, and inclusive cultural environments directly influence universities' capacity to generate equitable and sustainable educational trajectories [ 30 ]. Despite these conceptual advances, the empirical operationalisation of USR remains a challenge for research in higher education. A large proportion of existing studies have focused on qualitative analyses or specific institutional evaluations, which has limited the development of systematic measurement tools capable of evaluating how universities translate their declarative commitments to sustainability and inclusion into concrete organisational practices [ 27 ]. 2.2. Equity and inclusion in higher education governance In contemporary debates on higher education, equity and inclusion have attracted central interest within educational policy agendas and university governance frameworks [ 31 ]. Traditionally, the analysis of educational equity focused on expanding access to higher education; however, recent literature has broadened this perspective by recognising that university inclusion also involves ensuring institutional conditions that support student retention, wellbeing, and academic success [ 32 ]. As a result, equity in higher education is increasingly conceived as a structural process that spans multiple dimensions of the educational experience, from admission policies to institutional support systems and learning environments [ 33 ]. Within this perspective, it has been noted that highly participatory higher education systems face the challenge of balancing educational expansion with social justice [ 34 ]. As universities incorporate increasingly diverse student populations, new institutional responsibilities emerge to adapt educational environments to heterogeneous socio-economic, cultural, and generational realities. In this regard, university governance plays a fundamental role in defining policies, resources, and organisational structures that may facilitate or limit educational inclusion within institutions [ 35 ]. Similarly, Germain [ 11 ] highlights that university inclusion does not depend solely on normative decisions or access policies, but also on the institutional capacity to build educational ecosystems that foster student wellbeing and participation. Factors such as the availability of academic support services, access to adequate infrastructure, opportunities for professional development, and the presence of inclusive institutional cultures significantly influence students' educational trajectories, particularly in contexts where pre-existing socio-economic and educational inequalities converge [ 36 ]. Within this framework, the approach to educational equity aligns naturally with USR's perspectives by recognising that universities must not only expand access but also create institutional environments capable of sustaining inclusive and socially meaningful educational trajectories. For this reason, understanding how the organisational and cultural conditions of universities influence the student experience has become an expanding field of research within studies of educational governance. This perspective opens the possibility of analysing university equity not only as a normative principle, but also as an institutional infrastructure composed of multiple interrelated domains that shape the educational environment. 2.3. Institutional domains shaping inclusive learning environments The growing interest in equity in higher education has led the literature to recognise that educational outcomes depend not only on formal access to institutions, but also on the organisational conditions that shape the university experience [ 37 ]. Within this perspective, Lapidot-Lefler [ 38 ] notes that inclusive educational environments emerge from the interaction of multiple institutional dimensions that influence student participation, wellbeing, and academic development. These conditions encompass material, organisational, and cultural aspects that together configure what some authors have referred to as university learning ecosystems [ 39 ]. First, an adequate learning infrastructure is a fundamental element in ensuring equitable educational experiences. Appropriate physical spaces, accessible technological resources, and inclusive digital environments facilitate effective access to knowledge and reduce structural barriers that disproportionately affect students from diverse socio-economic backgrounds [ 40 ]. In the literature on university sustainability, these conditions are considered part of institutional responsibilities aimed at ensuring accessible and resilient learning environments [ 30 ]. Second, research on student retention has highlighted the importance of institutional systems of support and wellbeing in sustaining successful educational trajectories. Academic guidance services, mentoring programmes, psychological support, and institutional policies oriented towards student wellbeing significantly influence the university experience and the reduction of educational inequalities [ 41 ]. Several studies have shown that integrating these support mechanisms strengthens student participation and reduces the risk of academic dropout [ 42 ];[ 39 ]. A third relevant domain relates to the opportunities for professional development and social engagement provided by universities. The literature on USR emphasises that higher education institutions should facilitate learning experiences that connect academic learning with the solution of social and environmental problems [ 43 ]. Community engagement activities, sustainability projects, and professional development programmes contribute to expanding students' capacities to participate actively in social transformation [ 28 ]. Finally, several studies have emphasised the importance of the cultural and identity dimensions of the university experience, including integral formation, the construction of inclusive environments, and the development of a sense of institutional belonging. These dimensions influence how students integrate into university life and their perceptions of recognition within the academic community [ 44 ]. Evidence suggests that students who develop a strong sense of institutional belonging tend to demonstrate higher levels of academic engagement and persistence in their studies [ 45 ]. Taken together, these domains suggest that USR can be understood as a multidimensional institutional infrastructure that integrates material conditions, support systems, learning opportunities, and inclusive cultural environments. Although prior literature commonly conceptualises USR through broad institutional domains, empirical analyses may reveal more differentiated dimensions when these conditions are examined from the perspective of students' lived experiences within universities. Based on this literature, Table 1 summarises the main institutional domains identified in previous research and their relationship with the construction of inclusive and sustainable educational environments. Table 1 Institutional domains associated with inclusive educational environments in higher education Institutional domain Conceptual description Main references Learning infrastructure Physical and digital conditions that facilitate access to educational resources Lozano et al. [ 30 ] Wellbeing and institutional support Guidance systems, academic support, and student wellbeing services Thomas [ 42 ]; Kahu & Nelson [ 39 ] Professional development and social engagement Opportunities for applied learning and engagement with society Filho et al. [ 28 ] Integral formation and inclusion Educational environments that promote diversity, participation, and an inclusive culture Marginson [ 33 ] Identity and belonging Student integration within the university community Strayhorn [ 45 ] Source: Own elaboration. The reviewed literature suggests that USR and the promotion of equitable educational environments depend on a set of interrelated institutional conditions that influence students' learning experiences. Learning infrastructure, support and wellbeing systems, opportunities for professional development, social and environmental engagement, and inclusive cultural environments emerge as domains that shape universities' capacity to foster sustainable and inclusive educational trajectories. The following section describes the study design and the methodological phases used to construct and validate the instrument. 3. Methodology To develop and validate a multidimensional USR scale to evaluate institutional conditions associated with equitable educational environments, the present study adopted a sequential methodological approach to the development of measurement instruments in the social sciences. The instrument development process was structured in three main phases: (1) qualitative exploration and initial item generation, (2) content validation through an expert panel, and (3) psychometric validation of the instrument through exploratory and confirmatory factor analysis. This approach integrated knowledge from the academic literature, university stakeholders' experience, and the statistical evaluation of the instrument. The methodological process is presented below. 3.1. Research design As mentioned previously, the research design followed a sequential mixed-methods approach oriented towards scale development and validation, widely used in measurement studies within the social and organisational sciences [ 46 ];[ 47 ]. This approach combines exploratory and confirmatory phases to construct instruments that are both empirically robust and conceptually coherent. In particular, the scale development process followed the classical paradigm proposed by Churchill [ 48 ], which establishes a series of systematic stages for the generation, purification, and validation of measurement indicators. According to this approach, the research was conducted in three consecutive stages, which were developed between February and December 2025. First, a qualitative exploratory phase was conducted to identify students' perceptions of USR and the institutional conditions that influence the educational experience. Subsequently, the items derived from this phase were subjected to content validation by an expert panel with experience in university management, social responsibility, and psychometrics. Finally, the resulting instrument was subjected to quantitative validation, including an exploratory factor analysis based on a pilot study and a confirmatory factor analysis applied to an expanded sample of university students. This methodological design allowed the progressive evaluation of the conceptual clarity of the items, the coherence of the proposed theoretical dimensions, and the factorial structure of the instrument, following methodological recommendations for scale development studies in organisational and educational research [ 49 ]. This approach enabled the identification of broad conceptual domains from the literature, which were subsequently refined empirically during the qualitative and quantitative phases of the scale validation process. 3.2. Phase 1: Qualitative exploration and item generation To identify institutional dimensions relevant to the construction of the USR scale, a qualitative exploratory phase was conducted through focus groups with university students. This approach allows understanding of perceptions, experiences, and shared meanings among participants, facilitating the generation of conceptual categories that can subsequently be translated into measurement indicators [ 50 ]. The fieldwork was conducted between February and March 2025, during which five focus groups were organised, each composed of eight undergraduate students, resulting in a total of 40 participants. The selection of this number of participants was based on methodological recommendations suggesting groups of between six and ten individuals to facilitate interaction, the exchange of experiences, and the generation of rich information in exploratory contexts [ 50 ]. Participants came from business programmes at a public university in northern Mexico, enabling the collection of diverse perspectives on the institutional conditions shaping their university experience. The sessions were conducted in person. They followed a semi-structured guide designed to explore students' perceptions of educational infrastructure, university wellbeing, institutional support systems, opportunities for professional development, the university's social and environmental engagement, and the sense of institutional belonging. The research team moderated the discussions and subsequently analysed them using Atlas. ti 25, employing a thematic coding process that identified recurring patterns and conceptual categories relevant to the study. The development of this exploratory phase was conducted in accordance with international ethical principles for research involving human participants. In particular, the study followed the guidelines outlined in the Declaration of Helsinki for research involving human subjects [ 51 ]. Participation was voluntary; students were informed of the study's objectives, and the confidentiality of their responses was guaranteed. Participants also provided informed consent prior to the beginning of the sessions. The findings of this phase enabled the identification of an initial set of institutional dimensions associated with the university experience from students' perspectives. These preliminary categories were subsequently contrasted with the theoretical frameworks reviewed in the literature and used as the basis for the initial generation of instrument items, which were later subjected to content validation through expert evaluation. 3.3. Phase 2: Content validity through expert evaluation Once the initial pool of items had been generated from the qualitative exploratory phase and contrasted with the academic literature, a content validation process was conducted through expert evaluation. This procedure aims to ensure that the proposed indicators adequately represent the theoretical constructs intended to be measured by evaluating their clarity, conceptual relevance, and coherence with the study's theoretical framework [ 52 ];[ 53 ]. The expert evaluation was conducted in April 2025 and involved five specialists with experience in university management, organisational social responsibility, and quantitative research methods. The selection of a small panel of experts follows methodological recommendations for content validation processes, in which the academic and professional expertise of the evaluators is prioritised over panel size, with participation of between three and ten specialists common in instrument development studies [ 52 ]; [ 53 ]. The experts received a preliminary version of the instrument along with a description of the conceptual dimensions derived from the study's theoretical framework. Each item was evaluated according to three main criteria: semantic clarity, conceptual relevance, and coherence with the corresponding theoretical dimension. This procedure enabled the identification of potential ambiguities, redundancies, or inconsistencies in the formulation of the indicators, facilitating the refinement of the initial pool of items. Based on the expert panel's observations, adjustments were made to the wording of several indicators, and indicators that presented conceptual overlap or low relevance to the evaluated construct were removed. This refinement process improved the conceptual precision of the instrument and strengthened its content validity before proceeding to the empirical validation phase. The resulting set of items constituted the preliminary version of the questionnaire, which was subsequently subjected to a pilot study and an exploratory factor analysis to evaluate its dimensional structure. 3.4. Instrument development and pilot test Once the initial pool of items had been generated from the qualitative exploratory phase and contrasted with the academic literature, a content validation process was conducted through expert evaluation. This procedure aims to ensure that the proposed indicators adequately represent the theoretical constructs intended to be measured by evaluating their clarity, conceptual relevance, and coherence with the study's theoretical framework [ 52 ];[ 53 ]. The expert evaluation was conducted in April 2025 and involved five specialists with experience in university management, organisational social responsibility, and quantitative research methods. The selection of a small panel of experts follows methodological recommendations for content validation processes, in which the academic and professional expertise of the evaluators is prioritised over panel size, with participation of three to ten specialists common in instrument development studies [ 52 ];[ 53 ]. The experts received a preliminary version of the instrument along with a description of the conceptual dimensions derived from the study's theoretical framework. Each item was evaluated according to three main criteria: semantic clarity, conceptual relevance, and coherence with the corresponding theoretical dimension. This procedure enabled the identification of potential ambiguities, redundancies, or inconsistencies in the formulation of the indicators, thereby facilitating the refinement of the initial pool of items. Based on the expert panel's observations, adjustments were made to the wording of several indicators, and indicators that presented conceptual overlap or low relevance to the evaluated construct were removed. This refinement process improved the conceptual precision of the instrument and strengthened its content validity before proceeding to the empirical validation phase. The resulting set of items constituted the preliminary version of the questionnaire, which was subsequently subjected to a pilot study and an exploratory factor analysis to evaluate its dimensional structure. 3.5. Exploratory factor analysis. To examine the preliminary dimensional structure of the instrument and evaluate the underlying grouping of the items, an exploratory factor analysis (EFA) was conducted using the data obtained from the pilot study in Jamovi 2.6.26 software. Exploratory factor analysis is a technique widely used in scale development studies, as it allows the identification of correlation patterns among observed variables and the exploration of the latent structure of constructs without imposing a priori restrictions on the measurement model [ 49 ]. Although the pilot study sample (n = 154) was relatively small compared with the instrument's initial number of items (43 indicators), it is considered acceptable for exploratory scale development studies. The methodological literature indicates that, although some authors recommend ratios of 5 or more cases per item, exploratory factor analyses may yield stable solutions when factor loadings and item communalities are sufficiently high [ 54 ]. Consequently, the pilot sample was deemed adequate for a preliminary examination of the instrument's factorial structure before proceeding to confirmatory validation with a larger sample. Following methodological recommendations for psychometric studies, the adequacy of the data for factor analysis was evaluated using the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett's test of sphericity. KMO values above 0.60 indicate that the data are appropriate for factor analysis. At the same time, a significant result in Bartlett's test suggests that the correlation matrix differs significantly from an identity matrix, confirming the presence of sufficient relationships among the items to proceed with factor analysis [ 49 ];[ 55 ]. Factor extraction was performed using the principal axis factoring method, recommended for identifying latent constructs in exploratory scale development studies [ 56 ];[ 49 ]. Subsequently, an oblique Oblimin rotation was applied to improve the interpretability of the factorial structure. Oblique rotations are considered more appropriate in social science research when the underlying constructs are expected to be correlated, as they allow correlations among factors rather than imposing independence between them [ 54 ]. This approach allows examination of the instrument's preliminary dimensional structure before proceeding to its confirmatory validation via structural equation modelling. Factor retention was determined by considering multiple complementary criteria, including eigenvalues greater than 1, analysis of the scree plot, and the theoretical interpretability of the resulting dimensions. In addition, to ensure the quality of the indicators, items with factor loadings of 0.50 or greater were considered adequate, while avoiding cross-loadings among factors [ 49 ];[ 54 ]. These criteria allowed refining the initial pool of indicators and establishing the instrument's preliminary factorial structure, which was subsequently evaluated through confirmatory factor analysis. Additionally, to assess the preliminary internal consistency of the identified dimensions, Cronbach's alpha was estimated, one of the most widely used indicators of scale reliability in social science research. According to the criteria proposed by Cronbach [ 57 ] and subsequent developments in applied psychometrics, alpha values of 0.70 or higher are generally considered indicative of adequate internal consistency among the indicators composing each dimension [ 49 ];[ 47 ]. The results of these reliability tests are presented in the results section. 3.6. Main data collection and sample Following preliminary refinement of the instrument based on the pilot study and exploratory factor analysis, data collection was conducted to validate the measurement model using confirmatory factor analysis. This stage aimed to evaluate the stability of the previously identified factorial structure and to examine the instrument's reliability and validity in an independent sample. Data collection was carried out between August and December 2025 at a public university in northern Mexico. The final instrument was administered electronically to undergraduate students enrolled in business programmes. This sampling strategy is common in scale development and validation studies in educational contexts, particularly when the objective is to examine institutional perceptions from students' direct experiences [ 46 ]. A total of 583 university students participated, all belonging to Generation Z, who currently constitute the predominant group in contemporary higher education systems and represent a particularly relevant cohort for analysing institutional conditions associated with inclusion, wellbeing, and sustainable educational experiences [ 58 ]. The sample size used is consistent with methodological recommendations for confirmatory factor analysis and structural equation modelling, which suggest that samples exceeding 200 observations are needed to ensure stable estimates and adequate statistical power [ 59 ];[ 49 ]. Participation in the study was voluntary and anonymous, always ensuring the confidentiality of the information provided by participants. Before completing the questionnaire, students received clear information about the research objectives, the academic use of the data, and their right to withdraw from the study at any time without consequences. The study design followed the ethical principles established in the Declaration of Helsinki, which emphasise the protection of participants in research involving human beings, including respect for autonomy, confidentiality, and informed consent [ 51 ]. The final questionnaire consisted of the items resulting from the refinement process carried out in the previous phases of the study. Participants evaluated each statement using a five-point Likert scale ranging from 1 (“strongly disagree”) to 5 (“strongly agree”). This type of scale is widely used in social science research to measure perceptions and attitudes, allowing the capture of gradual variations in the evaluation of organisational and institutional phenomena [ 47 ]. The data obtained in this phase were subsequently analysed using covariance-based confirmatory factor analysis to evaluate the instrument's factorial structure and examine the reliability and validity of the proposed measurement model. 3.7. Confirmatory factor analysis To evaluate the stability of the factorial structure identified in the exploratory phase and to examine the validity of the proposed measurement model, a confirmatory factor analysis (CFA) was conducted using covariance-based structural equation modelling (CB-SEM) in AMOS 22 software. CFA is a widely used technique in scale validation studies, as it allows empirical testing of the adequacy of a previously specified theoretical model and the evaluation of the relationships between observed indicators and the latent constructs intended to be measured [ 49 ];[ 59 ]. The analysis was conducted using the maximum likelihood estimation method, one of the most frequently used procedures in structural equation modelling due to its ability to produce efficient and consistent estimates when the assumptions of multivariate normality and adequate sample size are satisfied [ 59 ]. This approach is particularly appropriate for psychometric validation studies, as it allows the simultaneous evaluation of the instrument's reliability and the overall adequacy of the measurement model. The evaluation of model fit was carried out using multiple goodness-of-fit indices, following widely accepted methodological recommendations in the structural equation modelling literature. In particular, the Comparative Fit Index (CFI), the Root Mean Square Error of Approximation (RMSEA), and the Chi-square/degrees of freedom ratio (χ²/df) were considered. According to the criteria proposed by Hu and Bentler [ 60 ], CFI values of 0.90 or higher indicate acceptable model fit, whereas values of 0.95 or higher indicate excellent fit. In the case of RMSEA, values below 0.08 are considered indicative of reasonable model fit, while values below 0.06 suggest optimal fit [ 60 ]; [ 59 ]. In addition to overall model fit, the convergent validity of the constructs was evaluated using Average Variance Extracted (AVE) and Composite Reliability (CR). Following the recommendations of Fornell and Larcker [ 61 ], AVE values greater than 0.50 indicate that the indicators adequately explain the variance of the latent construct. In contrast, CR values greater than 0.70 indicate satisfactory internal consistency. Discriminant validity among the constructs was examined using the Heterotrait-Monotrait ratio (HTMT), a criterion considered one of the most robust methods for evaluating differentiation among conceptually related constructs. According to Henseler et al. [ 62 ], HTMT values below 0.85 suggest that the constructs present sufficient conceptual discrimination within the model. To assess the potential presence of common method bias (CMB), Harman’s single-factor test was conducted. The results showed that the first factor accounted for 31.4% of the total variance, which is below the recommended threshold of 50%, suggesting that common method bias is unlikely to be a significant concern in this study. These procedures allowed a rigorous evaluation of the adequacy of the proposed measurement model. They confirmed the instrument's factorial structure, designed to operationalise USR as an institutional infrastructure oriented towards equity in higher education. To provide a clear overview of the sequential process followed in the development and validation of the instrument, Fig. 1 summarises the main stages of the research design, including the qualitative exploration, expert validation, pilot testing, exploratory factor analysis, and confirmatory validation phases. Once the sequential methodological process followed for the development and validation of the instrument has been described, the following section presents the empirical results derived from the analyses conducted in this study. In particular, the findings are reported according to the different stages of the validation process, beginning with the description of the sample profile and the results of the exploratory factor analysis conducted with the pilot data, followed by the confirmatory factor analysis and the evaluation of the reliability and validity of the proposed measurement model. 4. Results This section presents the empirical results derived from the development and validation process of the proposed instrument. First, the qualitative findings from the focus groups with students are presented, which enabled the identification of relevant dimensions for understanding the institutional conditions associated with USR. Subsequently, the results of the content validation process conducted through expert evaluation are reported. Next, the profile of the sample used in the main study is described, and the results of the exploratory factor analysis applied to the pilot study data are presented to examine the instrument's preliminary dimensional structure. Finally, the results of the confirmatory factor analysis and the evaluation of the reliability and validity indicators of the proposed measurement model are reported. 4.1. Qualitative findings (focus groups) To explore how students perceive the institutional conditions that shape inclusive and socially responsible educational experiences, five focus groups were conducted with 8 participants each, for a total of 40 undergraduate students enrolled in business programmes. The groups were conducted using a semi-structured guide designed to discuss perceptions of educational infrastructure, institutional support, student wellbeing, opportunities for professional development, and experiences of integration within the university community. The information was analysed using the Atlas. ti 25 software through thematic coding, an approach widely used in exploratory studies to identify recurring patterns in participants' experiences and perceptions [ 63 ]. The analytical process continued until theoretical saturation was reached, that is, the point at which the inclusion of new discussions no longer generated substantially different conceptual categories from those already identified [ 64 ]. This procedure ensured that the identified domains consistently reflected students' shared experiences. The qualitative findings showed strong convergence between the conceptual domains identified in the literature review and the perceptions expressed by students in the focus groups. Participants highlighted the relevance of physical and digital learning conditions, institutional systems of academic support and wellbeing, as well as opportunities for applied learning and social and environmental engagement promoted by the university. Likewise, aspects related to inclusive institutional culture and a sense of belonging to the university community emerged clearly and were described as factors that strengthen student integration and retention. It should be noted that, although the literature review identified five broad conceptual domains associated with USR (learning infrastructure, institutional wellbeing, professional development, integral formation and identity and belonging), the qualitative analysis conducted through the five focus groups (n = 40 students) confirmed the relevance of these areas from the students’ perspective, while also showing that some institutional conditions tend to be perceived in a more differentiated manner within the university experience. Participants distinguished between different institutional support mechanisms and types of interaction with the university environment, suggesting that these conceptual domains may empirically manifest as more specific dimensions within the analysed educational context. Table 2 summarises the main categories identified during the focus groups and representative examples of the perceptions expressed by the participants. Table 2 Conceptual domains emerging from focus groups Conceptual domain Description Example perception Learning infrastructure Physical and digital conditions that facilitate access to educational resources and support learning processes “Having access to digital platforms and well-equipped classrooms helps students learn more effectively.” Wellbeing and institutional benefits Academic advising systems, psychological support, and services that support student wellbeing and academic progression “Students need academic advisors and counselling services to deal with academic pressure.” Professional development and social engagement Opportunities for internships, applied learning, and university initiatives that connect students with social challenges. “Projects that allow students to work with communities help us understand the social role of the university.” Integral formation and inclusion Institutional environments that promote diversity, participation, and an inclusive academic culture “Feeling respected regardless of background encourages students to participate more actively.” Identity and belonging Processes that strengthen students’ integration and identification with the university community “When students feel part of the university community, they are more motivated to continue their studies.” Source: Own elaboration. These domains represent broad conceptual areas derived from both the literature review and the qualitative exploration. In subsequent quantitative analyses, these domains were further refined through exploratory factor analysis, yielding more specific measurement dimensions. 4.2. Content validity (expert panel) To evaluate the content validity of the preliminary instrument, the initial questionnaire version was submitted for review by a panel of five experts with academic and professional experience in USR, educational management, and applied psychometrics. The use of expert panels is a widely recommended procedure in scale development studies, as it allows the examination of the conceptual adequacy of items, their semantic clarity, and their correspondence with the theoretical constructs intended to be measured [ 65 ];[ 66 ]. The experts evaluated the proposed dimensions considering three main criteria: clarity, relevance, and conceptual coherence. Clarity refers to the degree to which indicators are formulated in a manner understandable to potential participants; relevance evaluates the appropriateness of each dimension for representing the institutional conditions associated with USR; and coherence examines the consistency between the items and the conceptual domain to which they belong [ 65 ]. To quantify the level of agreement among the specialists, the Content Validity Index (CVI) was calculated using Jamovi 2.6.26. This indicator allows the evaluation of the degree of consensus among experts regarding the adequacy of the instrument's elements. According to the psychometric literature, CVI values equal to or greater than 0.80 are considered indicative of adequate content validity when the panel consists of between three and ten evaluators [ 53 ]. Table 3 summarizes the expert panel's evaluations of the instrument's preliminary dimensions. Table 3 Expert evaluation of the instrument (Content Validity Index) Dimension Clarity (CVI) Relevance (CVI) Coherence (CVI) Learning infrastructure 0.94 0.96 0.92 Health and wellbeing 0.91 0.95 0.90 Institutional benefits 0.92 0.94 0.91 Professional development 0.90 0.93 0.88 Social and environmental engagement 0.89 0.92 0.87 Integral formation and inclusion 0.88 0.90 0.89 Identity and belonging 0.96 0.98 0.95 Source: Own elaboration. The results presented above showed high levels of agreement among the experts across all evaluated dimensions, with clarity values ranging from 0.88 to 0.96, relevance values ranging from 0.90 to 0.98, and conceptual coherence values ranging from 0.87 to 0.95. These results indicate that the proposed dimensions adequately capture the institutional domains associated with USR in higher education. In addition, the specialists' qualitative observations allowed refining the wording of several indicators and adjusting the formulation of certain items, thereby strengthening the conceptual consistency of the instrument before its application in the pilot study. 4.3. Sample characteristics To contextualise the psychometric analyses conducted in the study, this section presents the characteristics of the two samples used in the instrument validation process: the pilot study sample, used for the exploratory factor analysis, and the main study sample, used for the estimation of the confirmatory model. The use of independent samples for the exploratory and confirmatory phases is a recommended practice in scale development studies, as it allows evaluation of the factorial structure's stability and reduces the risk of model overfitting [ 46 ];[ 49 ]. The pilot sample consisted of 154 undergraduate students, whereas the main sample comprised 583 students enrolled in business programmes at a public university in northern Mexico. In both cases, participants predominantly belonged to Generation Z, a generational cohort characterised by its high familiarity with digital environments and its growing presence in contemporary higher education systems [ 58 ]. In demographic terms, the average age of participants in the pilot sample was 20.8 years (SD = 1.7), whereas in the main sample the mean age was 21.2 years (SD = 1.9). Regarding gender distribution, the pilot sample consisted of 57% women and 43% men, while the main sample comprised 59% women and 41% men. This distribution is consistent with the composition observed in university business programmes across different educational contexts [ 33 ]. With respect to academic level, participants spanned different years of university education, allowing the capture of perceptions from students at different stages of their educational trajectory. The mean semester completed in the main sample was 5.1 (SD = 1.6), suggesting a balanced representation of students in intermediate and advanced phases of their academic programmes. Table 4 presents a summary of the main demographic characteristics of both samples used in the study. The inclusion of these two samples aligns with the research's sequential methodological design, in which the pilot data were used to identify the instrument's preliminary factorial structure. In contrast, the main sample enabled the evaluation of the measurement model's stability and validity through confirmatory factor analysis. Table 4 Sample characteristics Variable Pilot sample (n = 154) Main sample (n = 583) Age (mean ± SD) 20.8 ± 1.7 21.2 ± 1.9 Female 57% 59% Male 43% 41% Semester (mean ± SD) 4.9 ± 1.5 5.1 ± 1.6 Academic programs Business-related programs Business-related programs Source: Own elaboration. 4.4. Exploratory factor analysis To examine the instrument's preliminary factorial structure, an exploratory factor analysis (EFA) was conducted using data from the pilot study (n = 154). EFA is a technique widely used in scale development studies in the social sciences, as it allows the identification of correlation patterns among observed variables and the exploration of the latent structure of constructs without imposing prior restrictions on the measurement model [ 56 ];[ 49 ]. Before proceeding with factor extraction, the adequacy of the data was evaluated using the Kaiser-Meyer-Olkin (KMO) measure and Bartlett’s test of sphericity. The results showed a KMO value of .979, considered excellent according to the criteria established in the psychometric literature. Likewise, Bartlett's test was statistically significant χ²(903) = 33,696.93; p < .001, confirming the existence of sufficient correlations among the items to proceed with the factor analysis. These results indicate that the correlation matrix exhibits an appropriate pattern of interrelationships for identifying latent factors. The initial item pool consisted of 49 indicators derived from the qualitative phase and the theoretical review. During the exploratory factor analysis, items were evaluated based on their factor loadings, potential cross-loadings, and conceptual coherence with the underlying constructs. As a result of this refinement process, six items were eliminated, yielding a final exploratory solution comprising 43 items distributed across seven factors. Together, these factors accounted for 83.19% of the total variance, providing initial evidence of the proposed scale's multidimensional structure. Factor extraction was conducted using principal axis factoring (PAF), followed by an Oblimin rotation. This approach is recommended in scale development studies because it allows the identification of latent constructs while accounting for correlations among factors [ 56 ];[ 49 ]. Factor retention was determined by considering multiple complementary criteria, including eigenvalues greater than 1, inspection of the scree plot, and the theoretical interpretability of the resulting dimensions. The initial eigenvalues indicated the presence of seven factors, which supported the retention of seven dimensions. Together, these factors explained 83.19% of the total variance, a percentage considerably higher than the levels commonly reported in social and educational research instruments, where multidimensional models typically explain between 50% and 60% of the total variance [ 49 ]. This high level of explained variance suggests a strong alignment between the indicators and the underlying theoretical constructs. Nevertheless, the moderate to high factor loadings (.511-.820), together with the results of the discriminant validity and HTMT tests, indicate that the dimensions maintain adequate conceptual differentiation and do not exhibit redundancy among items. Figure 2 presents the scree plot, which shows a clear inflection point after the seventh component, confirming the appropriateness of retaining seven dimensions. The Oblimin rotation yielded a clear, conceptually interpretable factorial structure. The items were consistently grouped into seven dimensions, coherent with the proposed conceptual model: identity and belonging; integral formation and inclusion; professional development; philanthropy and environment; learning infrastructure; health and integral wellbeing; and institutional benefits. The philanthropy and environment dimension groups indicators related to student participation in solidarity activities, volunteering, and environmental responsibility actions within the university. In the statistical tables, this dimension appears abbreviated as FILAN, used only as a technical label within the factorial analysis. Factor loadings ranged between .50 and .82, exceeding the minimum threshold of .50 recommended for exploratory scale development studies. In general terms, the factorial solution showed a simple structure, without problematic cross-loadings and with conceptually coherent groupings, supporting the instrument's preliminary stability. Table 5 presents the factor loadings for the items retained after extraction and rotation. Table 5 Exploratory factor analysis results (pilot sample) Dimension Item Factor loading Identity and belonging ID4 0.815 ID5 0.804 ID1 0.803 ID3 0.796 ID2 0.699 Integral formation and inclusion CULTU4 0.721 CULTU5 0.705 CULTU1 0.688 CULTU2 0.683 CULTU3 0.669 CULTU8 0.519 CULTU7 0.519 CULTU9 0.511 Professional development PROFE5 0.692 PROFE8 0.669 PROFE6 0.668 PROFE7 0.657 PROFE1 0.618 PROFE4 0.604 PROFE3 0.594 PROFE2 0.590 Social and environmental engagement FILAN2 0.704 FILAN3 0.703 FILAN4 0.696 FILAN1 0.665 FILAN5 0.664 FILAN6 0.654 Learning infrastructure INFRA3 0.772 INFRA5 0.76 INFRA1 0.752 INFRA4 0.747 INFRA2 0.742 Health and wellbeing SYB2 0.799 SYB4 0.787 SYB5 0.733 SYB3 0.693 SYB1 0.616 Institutional benefits BENEF2 0.700 BENEF1 0.652 BENEF3 0.643 BENEF4 0.62 BENEF5 0.617 Source: Own elaboration. Despite the modest pilot sample size, the factor solution showed strong loadings and conceptual interpretability, supporting the robustness of the extracted dimensions. 4.5. Confirmatory factor analysis To evaluate the factorial structure of the instrument and confirm the adequacy of the proposed measurement model, a confirmatory factor analysis (CFA) was conducted using the main sample composed of 583 university students enrolled in business programmes at a public university in northern Mexico. The analysis was performed using covariance-based structural equation modelling (CB-SEM) in AMOS software, a technique widely employed in psychometric validation studies to evaluate theoretically grounded measurement models [ 49 ];[ 59 ]. The confirmatory model specified seven latent constructs corresponding to the dimensions identified in the exploratory factor analysis: identity and belonging; integral formation and inclusion; professional development; philanthropy and socio-environmental engagement; learning infrastructure; health and integral wellbeing; and institutional benefits. The adequacy of the model was evaluated using several global fit indices, following methodological recommendations widely accepted in the structural equation modelling literature. The indicators considered included the χ²/df ratio, the Comparative Fit Index (CFI), and the Root Mean Square Error of Approximation (RMSEA). According to the criteria established by Hu and Bentler [ 60 ] and Hair et al. [ 49 ], χ²/df values below 3, CFI values above .90, and RMSEA values below .08 indicate acceptable model fit. The results indicate an adequate fit of the proposed measurement model. As shown in Table 6 , the fit indices reported χ²/df = 2.74, CFI = .929, and RMSEA = .070, indicating that the estimated factorial structure satisfactorily reproduces the observed covariance matrix. Table 6 Model fit indices of the confirmatory factor analysis Fit index Recommended threshold Result Chi-square/df .90 0.929 RMSEA < .08 0.07 Source: Own elaboration. Figure 3 presents the measurement model estimated through confirmatory factor analysis. This structural diagram shows the relationships between the latent constructs and their observed indicators, illustrating the correspondence between the proposed theoretical dimensions and the instrument's empirical structure. Table 7 also reports the standardised factor loadings, along with the Composite Reliability (CR) and Average Variance Extracted (AVE) indicators for each construct. The factor loadings ranged between .71 and .88, exceeding the minimum threshold of .50 recommended for scale validation studies [ 49 ]. Similarly, the CR values were above .90, and the AVE values exceeded the .50 threshold, confirming the instrument's convergent validity. Table 7 Standardised factor loadings and convergent validity Construct Item Loading CR AVE Identity and belonging ID1 0.84 0.94 0.71 ID2 0.78 ID3 0.86 ID4 0.88 ID5 0.80 Integral formation and inclusion CULTU1 0.75 0.93 0.64 CULTU2 0.79 CULTU3 0.76 CULTU4 0.82 CULTU5 0.77 CULTU6 0.74 CULTU7 0.73 CULTU8 0.72 CULTU9 0.71 Professional development PROFE1 0.72 0.92 0.61 PROFE2 0.74 PROFE3 0.77 PROFE4 0.81 PROFE5 0.83 PROFE6 0.79 PROFE7 0.76 PROFE8 0.75 Social and environmental engagement FILAN1 0.73 0.91 0.60 FILAN2 0.78 FILAN3 0.80 FILAN4 0.75 FILAN5 0.74 FILAN6 0.72 Learning infrastructure INFRA1 0.82 0.94 0.69 INFRA2 0.85 INFRA3 0.84 INFRA4 0.81 INFRA5 0.79 Health and wellbeing SYB1 0.76 0.92 0.65 SYB2 0.83 SYB3 0.79 SYB4 0.82 SYB5 0.78 Institutional benefits BENEF1 0.71 0.90 0.58 BENEF2 0.75 BENEF3 0.77 BENEF4 0.74 BENEF5 0.73 Source: Own elaboration. These results support the internal consistency and stability of the proposed measurement model, confirming that the seven identified dimensions adequately represent the conceptual structure of the USR scale developed in this study. 4.6. Reliability and discriminant validity To evaluate the instrument's internal consistency and examine the discriminant validity among the model's constructs, several reliability and validity indicators recommended in scale development and validation studies in the social sciences were analysed [ 49 ];[ 61 ]. First, the internal consistency of the instrument’s dimensions was examined using Cronbach’s alpha coefficient (α) and Composite Reliability (CR). As shown in Table 8 , all constructs presented α values above .80 and CR values above .90, substantially exceeding the minimum thresholds recommended in the literature (α > .70; CR > .70). These results indicate a high level of internal consistency among the indicators composing each dimension of the instrument. Table 8 Reliability and convergent validity of the constructs Construct Cronbach’s α CR AVE Identity and belonging 0.93 0.94 0.71 Integral formation and inclusion 0.91 0.93 0.64 Professional development 0.90 0.92 0.61 Social and environmental engagement 0.89 0.91 0.60 Learning infrastructure 0.92 0.94 0.69 Health and wellbeing 0.88 0.92 0.65 Institutional benefits 0.87 0.90 0.58 Source: Own elaboration. Convergent validity was also evaluated through the Average Variance Extracted (AVE). The AVE values reported for each construct were above the .50 threshold, indicating that the model's dimensions explain more than half of the variance in their observed indicators and thus meet the criteria proposed by Fornell and Larcker [ 61 ]. Taken together, these results confirm that the indicators used adequately represent the model's latent constructs. Subsequently, the instrument's discriminant validity among its dimensions was examined. For this purpose, two complementary criteria widely used in the structural equation modelling literature were applied: the Fornell-Larcker criterion and the Heterotrait-Monotrait (HTMT) index. First, the square roots of the AVEs for each construct were compared with the correlations among constructs. As shown in Table 9 , the square root of the AVE (presented on the diagonal) is greater than the correlations among constructs, indicating that each dimension shares more variance with its own indicators than with other constructs in the model. This result confirms the instrument's discriminant validity according to the Fornell-Larcker criterion. Table 9 Discriminant validity (Fornell–Larcker criterion) Construct IB IFI PD SEE LI HW BEN Identity and belonging (IB) 0.84 Integral formation and inclusion (IFI) 0.52 0.80 Professional development (PD) 0.48 0.55 0.78 Social and environmental engagement (SEE) 0.46 0.51 0.57 0.77 Learning infrastructure (LI) 0.49 0.47 0.50 0.44 0.83 Health and wellbeing (HW) 0.42 0.46 0.48 0.40 0.51 0.81 Institutional benefits (BEN) 0.45 0.49 0.47 0.43 0.52 0.50 0.76 Source: Own elaboration. Note Diagonal = √AVE. Additionally, the Heterotrait–Monotrait ratio (HTMT) index was calculated and is presented in Table 10 . This index is currently considered one of the most robust methods for assessing discriminant validity in structural equation models [ 62 ]. The obtained values were below the recommended threshold of .85, providing additional evidence that the instrument's dimensions represent conceptually distinct constructs. Table 10 HTMT ratios Construct IB IFI PD SEE LI HW BEN Identity and belonging — Integral formation and inclusion 0.6 — Professional development 0.6 0.7 — Social and environmental engagement 0.6 0.6 0.7 — Learning infrastructure 0.6 0.6 0.60 0.6 — Health and wellbeing 0.5 0.6 0.6 0.50 0.6 — Institutional benefits 0.6 0.60 0.6 0.5 0.7 0.6 — Source: Own elaboration (Note: All values < .85). These reliability and validity results support the psychometric robustness of the developed instrument, confirming that the proposed scale demonstrates adequate internal consistency, convergent validity, and discriminant validity. 4.7. Final instrument To facilitate the replicability of the study and promote the use of the instrument in future research, this section presents the final version of the USR scale developed and validated in the present study. Following the sequential instrument development process, which included a literature review, student focus groups, expert content validation, a pilot study, and exploratory and confirmatory factor analyses, a multidimensional scale composed of 7 dimensions and 43 items was developed. These dimensions reflect different institutional conditions associated with USR and its role in constructing inclusive and sustainable educational environments. The items were formulated as statements evaluated using a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). This measurement format is widely used in social science research because it can consistently and comparably capture perceptions and subjective evaluations across participants [ 47 ]. Table 11 presents the final version of the instrument, including the dimensions and their corresponding items. Table 11 Final instrument of the University Social Responsibility Scale Dimension Item Statement Learning Infrastructure (INFRA) INFRA1 The classrooms and academic spaces at the university provide adequate lighting, ventilation, and comfort for studying. INFRA2 At my faculty, I have sufficient access to computer equipment, internet, and other technological resources required for my academic activities. INFRA3 The library facilities and study spaces are sufficient and appropriate for completing both individual and group work. INFRA4 The sports facilities, gym, and green areas at the university contribute positively to my physical and recreational well-being. INFRA5 I consider the university’s facilities to be safe and well maintained, allowing me to carry out my activities without risk. Health and Wellbeing (SYB) SYB1 The university provides access to psychological and emotional support services. SYB2 The university implements sufficient initiatives aimed at promoting and protecting students’ mental health. SYB3 The basic medical care provided by the university is accessible and timely when required. SYB4 The university provides clear and accessible information about available physical and mental health services. SYB5 I believe that the university is concerned with my overall well-being, not only my academic performance. Institutional Benefits (BENEF) BENEF1 I am aware of the institutional benefits offered by the university and have made use of them (e.g. scholarships, discounts, special programmes). BENEF2 The financial support and incentives provided by the university help me to continue my studies. BENEF3 The university regularly disseminates calls for applications that allow students to request resources for academic, research, entrepreneurial, or social projects. BENEF4 I perceive that the university aims to ensure that all students have access to services at an affordable cost. BENEF5 I consider the institutional benefits provided by the university to be genuine support for improving my experience as a student. Professional Development (PROFE) PROFE1 The university offers high-quality academic programmes that contribute to my professional development. PROFE2 The course content includes and promotes professional ethics and social responsibility. PROFE3 The university’s academic programmes are relevant and aligned with current labour market requirements. PROFE4 The subjects I take motivate me to generate creative ideas, entrepreneurial initiatives, and innovations. PROFE5 At the university, I have received training to conduct scientific research and address contemporary issues. PROFE6 The university incorporates scientific or applied research projects into most subjects. PROFE7 The university facilitates connections with professional associations related to different degree programmes. PROFE8 I have received training in technological resources and other skills that enhance my competitiveness. Social and Environmental Engagement (FILAN) FILAN1 I have had the opportunity to participate in volunteer or community service programmes organised by the university. FILAN2 The university actively promotes and encourages participation in support initiatives during crises, disasters, or situations affecting vulnerable groups. FILAN3 The university encourages me to participate in environmental activities such as reforestation, clean-up campaigns, or recycling initiatives. FILAN4 The university implements ongoing recycling and environmental responsibility initiatives. FILAN5 I perceive that the university’s social and environmental actions genuinely contribute to improving the community and the environment. FILAN6 I believe that participating in philanthropic activities organised by the university has strengthened my sense of social responsibility. Integral Formation and Inclusion (CULTU) CULTU1 The university regularly offers cultural events (e.g. book fairs, concerts, plays, exhibitions) open to all students. CULTU2 I have attended at least one cultural event organised or promoted by the university during my studies. CULTU3 I believe that the university’s cultural activities contribute to my overall development beyond academic learning. CULTU4 Information about workshops and artistic or cultural activities is communicated clearly and in a timely manner to all students. CULTU5 I feel that the university values and encourages my participation in artistic and cultural activities. CULTU6 The university admits students regardless of their socio-economic or ethnic background. CULTU7 The university’s facilities provide adequate accessibility for people with disabilities. CULTU8 I perceive that all students can participate in university activities regardless of their personal circumstances. CULTU9 The university implements effective measures to prevent violence, harassment, bullying, and discrimination. Identity and Belonging (ID) ID1 I feel proud to belong to this university. ID2 I perceive a supportive and collaborative environment among students in my faculty. ID3 The university’s institutional activities and symbols (e.g. events, colours, logo, motto) strengthen my sense of identity. ID4 As a student at this university, I feel that I am part of a meaningful and valuable mission. ID5 Being part of this university provides me with a clear direction for my personal and professional development. Source: Own elaboration. Note All items were measured using a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). 5. Discussion The present study aimed to develop and validate a multidimensional scale to operationalise the institutional conditions associated with USR-oriented equity within higher education institutions. Importantly, the proposed scale does not attempt to measure governance structures directly; rather, it captures how equity-oriented institutional practices associated with USR are perceived and experienced by students within the university environment. The results obtained provide robust empirical evidence that USR can be analysed through an integrated set of institutional conditions shaping students' educational experiences. In particular, the identified factorial structure confirms that dimensions such as learning infrastructure conditions, institutional wellbeing, academic support, professional development, integral formation, and sense of belonging constitute interrelated components of a university ecosystem oriented towards inclusion and sustainable learning. These findings are consistent with previous research indicating that USR should not be understood merely as a set of outreach activities or social and environmental engagement, but rather as an institutional approach that integrates academic, organisational, and social dimensions within university governance [ 30 ];[ 26 ]. The results of the exploratory and confirmatory factor analyses revealed a final structure composed of seven dimensions, which empirically refines the five conceptual domains initially identified in the literature review and corroborated during the qualitative phase of the study. This finding suggests that although previous studies tend to conceptualise USR through broad institutional categories, students' experiences reveal that these conditions operate as more differentiated institutional mechanisms within university life. In this sense, the empirical validation process enabled disaggregating certain conceptual domains into specific dimensions, such as institutional support systems, professional development opportunities, and mechanisms of social engagement, which more precisely shape how students experience institutional policies and practices related to social responsibility within the university. From a conceptual perspective, the results contribute to expanding the understanding of USR as an operational framework for managing equity in higher education. Several authors have argued that universities play a fundamental role in promoting more just and sustainable societies, not only through knowledge generation but also by configuring institutional environments that foster inclusion, participation, and the integral development of students [ 28 ]; [ 33 ]. In this regard, the scale developed in this study enables these normative principles to be translated into observable, measurable dimensions, facilitating the empirical analysis of how universities implement institutional practices oriented towards educational equity. Thus, the proposed instrument contributes to reducing one of the limitations identified in recent literature: the scarcity of validated measurement tools capable of systematically evaluating the impact of university policies on the construction of inclusive educational environments[ 39 ]. The findings also highlight the importance of considering the student experience as a central indicator for evaluating USR. Recent research has emphasised that inclusion processes in higher education do not depend solely on formal access to universities, but also on institutional conditions that facilitate student retention, wellbeing, and integration within the academic community [ 42 ]; [ 45 ]. In line with this perspective, the focus group results from this study show that students perceive educational equity as a multidimensional phenomenon encompassing both structural aspects, such as technological infrastructure and access to academic resources, and relational factors, including institutional support, university culture, and a sense of belonging. In this way, the validated model confirms that USR manifests itself through a set of institutional practices that directly influence the quality of the educational experience. Another relevant contribution of the study is the integration of dimensions of student wellbeing and professional development into the USR framework. Traditionally, the literature on USR has emphasised universities' commitment to sustainable development and social responsibility in their relationships with society [ 26 ]; [ 28 ]. However, the results of this research suggest that USR should also be understood as a process aimed at ensuring institutional conditions that promote student wellbeing, mental health, and professional preparation. This finding is particularly relevant in the contemporary context of digital transformation and increasing academic pressure within universities, where the promotion of healthy educational environments has become an essential component of institutional sustainability[ 39 ]. The study also provides empirical evidence from the Latin American context, a region where structural inequalities continue to pose a significant challenge for higher education systems. Several international reports indicate that although access to higher education in Latin America has increased considerably over recent decades, important gaps remain in retention, educational quality, and development opportunities across different social groups [ 33 ]. In this context, the development of measurement instruments capable of rigorously evaluating the institutional conditions that promote inclusion becomes essential for guiding evidence-based university policies. The scale proposed in this study offers a precise tool for diagnosing and monitoring these conditions within universities. Although the present study focuses on undergraduate students, the institutional domains identified in this scale may also inform broader discussions on inclusive and sustainable learning environments across the educational life cycle. Finally, from a methodological perspective, the results confirm the validity of the sequential approach used to develop the instrument. The combination of literature review, qualitative exploration through focus groups, expert content validation, and exploratory and confirmatory factor analyses allowed the construction of a psychometrically robust scale. This methodological process follows classical recommendations for instrument development in the social sciences [ 47 ] and [ 46 ], and ensures that the identified dimensions reflect both theoretical foundations and students' empirical perceptions. Consequently, the scale developed in this research not only advances knowledge of USR but also provides a solid methodological foundation for future studies of educational governance and equity in higher education. 6. Theoretical and practical implications The results of this study have implications for both the theoretical development of USR and the institutional management of equity in higher education. First, from a conceptual perspective, the developed instrument contributes to advancing the empirical operationalisation of USR as an institutional infrastructure oriented towards equity. Although USR has been widely discussed in the literature as a normative framework guiding universities' social and environmental engagement, numerous studies have highlighted the difficulty of translating this concept into measurable indicators capable of evaluating its implementation within educational institutions [ 26 ];[ 30 ]. In this regard, the scale proposed in this research provides a tool capable of systematically capturing the organisational conditions shaping inclusive educational environments, thereby helping to address a methodological gap identified in previous studies on university governance and institutional sustainability. Second, the results expand understanding of equity in higher education by demonstrating that this phenomenon cannot be reduced solely to access policies or inclusion programmes, but is instead shaped by an integrated set of institutional conditions that influence students' educational experiences. The dimensions identified in the validated model (learning infrastructure, institutional wellbeing, academic support, professional development, integral formation, social and environmental engagement, and university identity) reflect the multidimensional nature of inclusion processes in higher education, which depend on both structural and cultural factors within universities [ 33 ];[ 42 ]. In this way, the proposed instrument enables progress towards a more holistic understanding of educational equity, aligned with contemporary approaches that conceive universities as institutional ecosystems that influence students' academic, social, and personal development [ 39 ]. From a practical perspective, the developed scale provides higher education institutions with a systematic diagnostic tool to evaluate and monitor institutional conditions associated with USR. In a global context characterised by accelerated processes of digital transformation and increasing pressure to ensure more inclusive educational systems, universities require instruments capable of identifying areas for improvement in their institutional governance and guiding the implementation of evidence-based policies. In this regard, the proposed scale facilitates the evaluation of key dimensions of the educational environment that influence student retention, wellbeing and integration within the academic community. Moreover, the instrument may contribute to the design and evaluation of institutional strategies to strengthen universities' social sustainability. Several international frameworks have emphasised the importance of higher education institutions incorporating principles of social responsibility and equity into their management models, particularly in relation to Sustainable Development Goal 4, which promotes inclusive and quality education for all [ 28 ]. In this context, the developed scale enables the generation of empirical information that can support institutional decision-making by facilitating the identification of gaps in access to educational resources, in the availability of student support services, or in the development of professional learning opportunities. In this sense, the scale also contributes to operationalising Sustainable Development Goal 4 by providing a tool to assess institutional conditions that support inclusive and equitable learning environments within universities. Finally, the instrument also offers opportunities for comparative research on university governance and educational equity across different national contexts. The possibility of measuring USR dimensions in a standardised manner opens new avenues for research to examine how different higher education systems implement institutional strategies to promote inclusive educational environments. In this way, the proposed scale serves not only as an institutional diagnostic tool but also as a methodological resource that may advance knowledge on equity, sustainability, and governance in contemporary higher education. 7. Conclusion This study addressed a persistent limitation in the higher education literature: the difficulty of translating the normative principles of USR into empirical tools capable of evaluating how institutions construct equitable educational environments. By developing and validating a multidimensional scale grounded in students' experiences and a rigorous methodological process, this research provides an instrument that operationalises USR as a measurable institutional infrastructure within universities. Beyond its methodological contribution, the study proposes a reinterpretation of USR from an educational governance perspective. Rather than understanding USR solely as a set of social and environmental engagement initiatives, the results show that it materialises through a network of institutional conditions (learning infrastructure, wellbeing, academic support, integral formation, professional development, social and environmental engagement, and university identity) that shape the educational experience and, ultimately, equity within the university system. In this way, the research contributes to advancing the academic dialogue on sustainability and higher education by offering a measurement model that enables a shift from the normative discourse on inclusion to its empirical evaluation. In contexts where universities face increasing pressure to demonstrate their social impact, the availability of valid, replicable instruments is essential for guiding institutional decision-making and strengthening the development of more inclusive and sustainable educational systems. 8. Limitations and future research directions Despite the study's contributions, several limitations remain and offer opportunities for future research. First, the data were obtained from students belonging to a single public university in northern Mexico, which may limit the generalisability of the results to other institutional contexts or higher education systems. Second, the cross-sectional design of the study prevents examining how perceptions of USR evolve over time or across different stages of students' academic trajectories. Furthermore, because the scale is based on students' perceptions, the instrument primarily captures the experiential dimension of USR rather than the full architecture of institutional governance. Future research could complement this approach by incorporating analyses of institutional policies or the perspectives of other university stakeholders, such as administrators, faculty members, or administrative staff, to examine more comprehensively how governance structures are translated into institutional practices oriented towards equity. In addition, although the scale was validated through rigorous psychometric procedures, its application in other cultural and educational contexts would strengthen the instrument's external validity. Consequently, future research could replicate the model across universities in different countries, compare public and private institutions, or explore relationships between the dimensions of USR and variables such as student retention, academic wellbeing, or educational performance, thereby expanding the analytical potential of the proposed scale. Declarations Competing interests: The authors declare no competing interests. Ethics approval: Ethical approval for this study was granted by the Research Ethics Committee of CETYS University (Baja California, Mexico) on February 27, 2025. The study was reviewed and approved in accordance with institutional ethical standards and the National Guidelines for the Integration and Functioning of Research Ethics Committees (CONBIOÉTICA, 2016). All procedures involving human participants were conducted in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments. Consent to participate: Informed consent was obtained from all individual participants included in the study. Participation was voluntary and all responses were treated as confidential and anonymous. Consent to publish: Not applicable. Funding: The authors received no financial support for the research, authorship, and/or publication of this article. Author Contribution L.R.L. conceived the study and led the qualitative phase, including item generation through focus groups. M.A.S.-A. contributed to the research design, statistical analysis, and interpretation of results. C.A.-A. supervised the study, contributed to the conceptual development, and coordinated the validation process. R.R.-R. contributed to the theoretical framework and critical revision of the manuscript. L.R.L. and M.A.S.-A. drafted the manuscript. All authors reviewed, edited, and approved the final version of the manuscript. Acknowledgement The authors would like to thank the participants for their valuable contributions to this study, as well as the expert reviewers who supported the content validation of the instrument. Data Availability The datasets generated and analysed during the current study are available from the corresponding author on reasonable request. References Altbach PG, Berdahl RO, Berdahl RO, Gumport PJ. 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Introduction","content":"\u003cp\u003eSince the mid-twentieth century, higher education has been recognised as one of the key drivers of economic development, social mobility, and the consolidation of democratic societies [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Following the expansion of mass higher education in the post-war period, universities ceased to be conceived exclusively as spaces for elite formation. Instead, they became institutions capable of promoting regional development, scientific innovation, and social cohesion [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This structural change has recently been reinforced through the incorporation of international agendas that emphasise the social responsibility and public impact of educational institutions [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Under this premise, international organisations such as UNESCO have emphasised that higher education constitutes a public good and a human right, essential for achieving more equitable and sustainable societies [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Nevertheless, despite advances in educational expansion, structural inequalities continue to limit access, retention, and academic success for broad sectors of the population across multiple regions of the world [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAgainst this backdrop, the emergence of digital transformation has reconfigured the debate on educational equity [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The accelerated adoption of virtual platforms, hybrid learning ecosystems, learning analytics, and tools based on artificial intelligence has redefined how knowledge is produced, distributed, and accessed [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Although these technological innovations have the potential to expand educational opportunities and make learning pathways more flexible, they may also intensify existing inequalities when access to digital infrastructure, technological skills, or institutional resources is uneven [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. According to Alenezi et al. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], the digitalisation of higher education does not in itself guarantee inclusive educational processes; rather, it requires institutional frameworks that integrate technology, pedagogy, and governance to prevent new forms of educational exclusion. According to global estimates, more than 250\u0026nbsp;million children and young people remain outside formal education systems. In contrast, millions more face discontinuous or precarious educational trajectories, particularly in emerging socio-economic contexts [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConsequently, the contemporary debate on educational equity has evolved from approaches centred on access towards more complex perspectives that analyse the institutional conditions shaping the overall student experience [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. For Taff and Clifton [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], inclusion in higher education depends on multiple interrelated factors, among which the availability of adequate infrastructure, institutional support systems, physical and psychological wellbeing services, professional development opportunities, and cultural environments that foster participation and a sense of belonging are particularly significant. In other words, educational equity is not limited to allowing diverse students to enter universities but rather involves creating institutional ecosystems capable of sustaining meaningful and successful educational trajectories. In this regard, universities are increasingly understood as social ecosystems in which organisational, educational, and social dimensions converge to influence learning outcomes and students' human development [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOne conceptual approach that has sought to address this complexity is the University Social Responsibility (USR) framework. Inspired by the principles of organisational social responsibility and stakeholder theory, this framework proposes that universities should manage the impacts they generate in their environment in an integrated manner, across organisational, educational, cognitive, and social dimensions [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. From this perspective, USR goes beyond extension activities or volunteering by integrating principles of sustainability, ethics, and social and environmental engagement into the core functions of universities. In this sense, Vallaeys and Rodr\u0026iacute;guez [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] argue that universities must move from assistance-based approaches towards impact management systems that articulate institutional governance, academic training, and engagement with society.\u003c/p\u003e \u003cp\u003eNevertheless, although USR has been conceptualised as a framework for institutional governance, its empirical operationalisation requires examining how these commitments translate into concrete experiences for university stakeholders [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In this regard, students\u0026rsquo; perceptions constitute a relevant empirical indicator for evaluating the extent to which institutional policies related to inclusion, wellbeing and social responsibility are effectively reflected within the educational environment.\u003c/p\u003e \u003cp\u003eDespite conceptual progress in the USR field, significant challenges remain in its empirical operationalisation. One of the principal limitations identified in the literature is the scarcity of psychometrically validated instruments that allow a systematic evaluation of how universities translate their declarative commitments to social responsibility into concrete institutional practices [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Numerous studies on USR continue to rely on descriptive analyses, case studies, or fragmented institutional evaluations, which complicates comparisons between institutions and the construction of empirical evidence regarding the impacts of these policies [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis need is particularly evident in the Latin American and Ibero-American context, where universities in the region have increasingly adopted discourses of social responsibility, sustainability, and inclusive education. However, the institutional implementation of these principles is often characterised by isolated initiatives or peripheral programmes that are not necessarily integrated into university governance systems [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], remaining largely at the level of discourse. Moreover, Vallaeys et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] indicate that most Ibero-American universities continue to concentrate their efforts on social outreach activities or volunteering, without developing systematic evaluation mechanisms capable of measuring their impact on the educational experience and student wellbeing. At the same time, studies on higher education in Latin America show that socio-economic inequalities continue to strongly condition university access and retention, particularly among first-generation students and socially vulnerable groups [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite these challenges, existing empirical instruments for evaluating the university environment tend to focus on specific dimensions of the student experience, such as academic satisfaction, institutional climate, and university services [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Although these approaches have made valuable contributions, they often address these dimensions in isolation, without integrating them into an analytical framework that explains how institutional structures simultaneously influence educational equity, student wellbeing, and professional development. Consequently, a gap remains in the literature regarding the development of multidimensional measurement models that capture the interactions among university governance, social inclusion, and learning experiences within higher education institutions [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn response to this gap, the present study proposes the development and validation of a multidimensional USR scale designed to measure the institutional conditions that foster equitable and sustainable learning environments. Based on the triangulation of international conceptual frameworks on USR, qualitative evidence derived from students\u0026rsquo; voices, expert validation and a psychometric validation process, the instrument conceptualises the institutional conditions associated with university equity as a multidimensional framework composed of seven interrelated dimensions: learning infrastructure, health and wellbeing, institutional benefits, professional development, social and environmental engagement, integral formation and inclusion, and identity and belonging.\u003c/p\u003e \u003cp\u003eAccordingly, the objective of this research is to develop and validate a multidimensional scale that captures students' perceptions of institutional equity within the USR framework. Rather than directly measuring formal governance structures, the proposed instrument operationalises how institutional commitments associated with USR are manifested in students' educational experiences through practices related to inclusion, integral wellbeing, learning infrastructure, professional development, and social and environmental engagement.\u003c/p\u003e \u003cp\u003eTo achieve this purpose, the study adopts a sequential methodological design that combines qualitative and quantitative approaches. In a first phase, students' perceptions were explored through interviews and group dynamics to identify experiences and needs associated with USR within the institutional context. Subsequently, the items derived from this exploratory phase were subjected to a content validation process through the evaluation by a panel of experts in university management, social responsibility, and psychometrics, who analysed the clarity, relevance, and conceptual coherence of each indicator. Finally, the refined instrument underwent rigorous psychometric validation through exploratory and confirmatory factor analyses to ensure its reliability and validity as a tool for systematically evaluating the institutional conditions that shape inclusive and sustainable educational experiences.\u003c/p\u003e"},{"header":"2. Literature review","content":"\u003cp\u003eThe growing transformation of higher education systems has generated significant academic debate regarding the role of universities in promoting more equitable and sustainable societies. In this context, several theoretical approaches have sought to understand how universities can integrate principles of social responsibility, sustainability, and inclusion into their governance structures and student learning experiences. This section reviews the main conceptual developments linking USR to the construction of sustainable and equitable educational environments, providing the theoretical framework that underpins the proposed instrument.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. University Social Responsibility and Sustainable Higher Education\u003c/h2\u003e \u003cp\u003eOver the past two decades, the literature on higher education has evolved towards a broader understanding of universities' social role [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Traditionally conceived as institutions primarily dedicated to the generation and transmission of knowledge, universities are now recognised as actors in promoting sustainable development, social cohesion, and responsible innovation [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This paradigm shift has encouraged the emergence of the concept of USR, understood as an institutional management approach aimed at evaluating and improving the educational, social, organisational, and environmental impacts generated by higher education institutions [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral authors have noted that USR involves systematically managing the impacts that universities generate on their students, communities, and ecosystems, promoting institutional practices consistent with principles of equity, sustainability, and public ethics [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e];[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Furthermore, the development of the concept of USR has been closely linked to the United Nations' global sustainability agenda. In particular, Sustainable Development Goal 4 (SDG 4) recognises education as a fundamental pillar for inclusive and sustainable development, emphasising the need to ensure equitable and quality learning opportunities throughout life [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In this regard, universities have been called upon to play a strategic role in the formation of socially responsible citizens capable of addressing contemporary social, environmental, and technological challenges [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAt the same time, recent literature has begun to emphasise that universities' contribution to sustainable development does not depend solely on their academic or research programmes, but also on the institutional conditions that shape students' educational experiences [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Factors such as access to adequate infrastructure, academic support systems, wellbeing services, professional development opportunities, and inclusive cultural environments directly influence universities' capacity to generate equitable and sustainable educational trajectories [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite these conceptual advances, the empirical operationalisation of USR remains a challenge for research in higher education. A large proportion of existing studies have focused on qualitative analyses or specific institutional evaluations, which has limited the development of systematic measurement tools capable of evaluating how universities translate their declarative commitments to sustainability and inclusion into concrete organisational practices [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Equity and inclusion in higher education governance\u003c/h2\u003e \u003cp\u003eIn contemporary debates on higher education, equity and inclusion have attracted central interest within educational policy agendas and university governance frameworks [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Traditionally, the analysis of educational equity focused on expanding access to higher education; however, recent literature has broadened this perspective by recognising that university inclusion also involves ensuring institutional conditions that support student retention, wellbeing, and academic success [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. As a result, equity in higher education is increasingly conceived as a structural process that spans multiple dimensions of the educational experience, from admission policies to institutional support systems and learning environments [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWithin this perspective, it has been noted that highly participatory higher education systems face the challenge of balancing educational expansion with social justice [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. As universities incorporate increasingly diverse student populations, new institutional responsibilities emerge to adapt educational environments to heterogeneous socio-economic, cultural, and generational realities. In this regard, university governance plays a fundamental role in defining policies, resources, and organisational structures that may facilitate or limit educational inclusion within institutions [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSimilarly, Germain [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] highlights that university inclusion does not depend solely on normative decisions or access policies, but also on the institutional capacity to build educational ecosystems that foster student wellbeing and participation. Factors such as the availability of academic support services, access to adequate infrastructure, opportunities for professional development, and the presence of inclusive institutional cultures significantly influence students' educational trajectories, particularly in contexts where pre-existing socio-economic and educational inequalities converge [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWithin this framework, the approach to educational equity aligns naturally with USR's perspectives by recognising that universities must not only expand access but also create institutional environments capable of sustaining inclusive and socially meaningful educational trajectories. For this reason, understanding how the organisational and cultural conditions of universities influence the student experience has become an expanding field of research within studies of educational governance. This perspective opens the possibility of analysing university equity not only as a normative principle, but also as an institutional infrastructure composed of multiple interrelated domains that shape the educational environment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Institutional domains shaping inclusive learning environments\u003c/h2\u003e \u003cp\u003eThe growing interest in equity in higher education has led the literature to recognise that educational outcomes depend not only on formal access to institutions, but also on the organisational conditions that shape the university experience [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Within this perspective, Lapidot-Lefler [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] notes that inclusive educational environments emerge from the interaction of multiple institutional dimensions that influence student participation, wellbeing, and academic development. These conditions encompass material, organisational, and cultural aspects that together configure what some authors have referred to as university learning ecosystems [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFirst, an adequate learning infrastructure is a fundamental element in ensuring equitable educational experiences. Appropriate physical spaces, accessible technological resources, and inclusive digital environments facilitate effective access to knowledge and reduce structural barriers that disproportionately affect students from diverse socio-economic backgrounds [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In the literature on university sustainability, these conditions are considered part of institutional responsibilities aimed at ensuring accessible and resilient learning environments [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSecond, research on student retention has highlighted the importance of institutional systems of support and wellbeing in sustaining successful educational trajectories. Academic guidance services, mentoring programmes, psychological support, and institutional policies oriented towards student wellbeing significantly influence the university experience and the reduction of educational inequalities [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Several studies have shown that integrating these support mechanisms strengthens student participation and reduces the risk of academic dropout [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e];[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA third relevant domain relates to the opportunities for professional development and social engagement provided by universities. The literature on USR emphasises that higher education institutions should facilitate learning experiences that connect academic learning with the solution of social and environmental problems [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Community engagement activities, sustainability projects, and professional development programmes contribute to expanding students' capacities to participate actively in social transformation [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFinally, several studies have emphasised the importance of the cultural and identity dimensions of the university experience, including integral formation, the construction of inclusive environments, and the development of a sense of institutional belonging. These dimensions influence how students integrate into university life and their perceptions of recognition within the academic community [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Evidence suggests that students who develop a strong sense of institutional belonging tend to demonstrate higher levels of academic engagement and persistence in their studies [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTaken together, these domains suggest that USR can be understood as a multidimensional institutional infrastructure that integrates material conditions, support systems, learning opportunities, and inclusive cultural environments. Although prior literature commonly conceptualises USR through broad institutional domains, empirical analyses may reveal more differentiated dimensions when these conditions are examined from the perspective of students' lived experiences within universities.\u003c/p\u003e \u003cp\u003eBased on this literature, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarises the main institutional domains identified in previous research and their relationship with the construction of inclusive and sustainable educational environments.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInstitutional domains associated with inclusive educational environments in higher education\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitutional domain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConceptual description\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMain references\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLearning infrastructure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical and digital conditions that facilitate access to educational resources\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLozano et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWellbeing and institutional support\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGuidance systems, academic support, and student wellbeing services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThomas [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]; Kahu \u0026amp; Nelson [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProfessional development and social engagement\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOpportunities for applied learning and engagement with society\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFilho et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIntegral formation and inclusion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEducational environments that promote diversity, participation, and an inclusive culture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMarginson [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIdentity and belonging\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudent integration within the university community\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStrayhorn [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eSource: Own elaboration.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe reviewed literature suggests that USR and the promotion of equitable educational environments depend on a set of interrelated institutional conditions that influence students' learning experiences. Learning infrastructure, support and wellbeing systems, opportunities for professional development, social and environmental engagement, and inclusive cultural environments emerge as domains that shape universities' capacity to foster sustainable and inclusive educational trajectories. The following section describes the study design and the methodological phases used to construct and validate the instrument.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Methodology","content":"\u003cp\u003eTo develop and validate a multidimensional USR scale to evaluate institutional conditions associated with equitable educational environments, the present study adopted a sequential methodological approach to the development of measurement instruments in the social sciences. The instrument development process was structured in three main phases: (1) qualitative exploration and initial item generation, (2) content validation through an expert panel, and (3) psychometric validation of the instrument through exploratory and confirmatory factor analysis. This approach integrated knowledge from the academic literature, university stakeholders' experience, and the statistical evaluation of the instrument. The methodological process is presented below.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Research design\u003c/h2\u003e \u003cp\u003eAs mentioned previously, the research design followed a sequential mixed-methods approach oriented towards scale development and validation, widely used in measurement studies within the social and organisational sciences [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e];[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. This approach combines exploratory and confirmatory phases to construct instruments that are both empirically robust and conceptually coherent. In particular, the scale development process followed the classical paradigm proposed by Churchill [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], which establishes a series of systematic stages for the generation, purification, and validation of measurement indicators.\u003c/p\u003e \u003cp\u003eAccording to this approach, the research was conducted in three consecutive stages, which were developed between February and December 2025. First, a qualitative exploratory phase was conducted to identify students' perceptions of USR and the institutional conditions that influence the educational experience. Subsequently, the items derived from this phase were subjected to content validation by an expert panel with experience in university management, social responsibility, and psychometrics. Finally, the resulting instrument was subjected to quantitative validation, including an exploratory factor analysis based on a pilot study and a confirmatory factor analysis applied to an expanded sample of university students.\u003c/p\u003e \u003cp\u003eThis methodological design allowed the progressive evaluation of the conceptual clarity of the items, the coherence of the proposed theoretical dimensions, and the factorial structure of the instrument, following methodological recommendations for scale development studies in organisational and educational research [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. This approach enabled the identification of broad conceptual domains from the literature, which were subsequently refined empirically during the qualitative and quantitative phases of the scale validation process.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Phase 1: Qualitative exploration and item generation\u003c/h2\u003e \u003cp\u003eTo identify institutional dimensions relevant to the construction of the USR scale, a qualitative exploratory phase was conducted through focus groups with university students. This approach allows understanding of perceptions, experiences, and shared meanings among participants, facilitating the generation of conceptual categories that can subsequently be translated into measurement indicators [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe fieldwork was conducted between February and March 2025, during which five focus groups were organised, each composed of eight undergraduate students, resulting in a total of 40 participants. The selection of this number of participants was based on methodological recommendations suggesting groups of between six and ten individuals to facilitate interaction, the exchange of experiences, and the generation of rich information in exploratory contexts [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Participants came from business programmes at a public university in northern Mexico, enabling the collection of diverse perspectives on the institutional conditions shaping their university experience.\u003c/p\u003e \u003cp\u003eThe sessions were conducted in person. They followed a semi-structured guide designed to explore students' perceptions of educational infrastructure, university wellbeing, institutional support systems, opportunities for professional development, the university's social and environmental engagement, and the sense of institutional belonging. The research team moderated the discussions and subsequently analysed them using Atlas. ti 25, employing a thematic coding process that identified recurring patterns and conceptual categories relevant to the study.\u003c/p\u003e \u003cp\u003e The development of this exploratory phase was conducted in accordance with international ethical principles for research involving human participants. In particular, the study followed the guidelines outlined in the Declaration of Helsinki for research involving human subjects [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Participation was voluntary; students were informed of the study's objectives, and the confidentiality of their responses was guaranteed. Participants also provided informed consent prior to the beginning of the sessions.\u003c/p\u003e \u003cp\u003eThe findings of this phase enabled the identification of an initial set of institutional dimensions associated with the university experience from students' perspectives. These preliminary categories were subsequently contrasted with the theoretical frameworks reviewed in the literature and used as the basis for the initial generation of instrument items, which were later subjected to content validation through expert evaluation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Phase 2: Content validity through expert evaluation\u003c/h2\u003e \u003cp\u003eOnce the initial pool of items had been generated from the qualitative exploratory phase and contrasted with the academic literature, a content validation process was conducted through expert evaluation. This procedure aims to ensure that the proposed indicators adequately represent the theoretical constructs intended to be measured by evaluating their clarity, conceptual relevance, and coherence with the study's theoretical framework [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e];[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe expert evaluation was conducted in April 2025 and involved five specialists with experience in university management, organisational social responsibility, and quantitative research methods. The selection of a small panel of experts follows methodological recommendations for content validation processes, in which the academic and professional expertise of the evaluators is prioritised over panel size, with participation of between three and ten specialists common in instrument development studies [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]; [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe experts received a preliminary version of the instrument along with a description of the conceptual dimensions derived from the study's theoretical framework. Each item was evaluated according to three main criteria: semantic clarity, conceptual relevance, and coherence with the corresponding theoretical dimension. This procedure enabled the identification of potential ambiguities, redundancies, or inconsistencies in the formulation of the indicators, facilitating the refinement of the initial pool of items.\u003c/p\u003e \u003cp\u003eBased on the expert panel's observations, adjustments were made to the wording of several indicators, and indicators that presented conceptual overlap or low relevance to the evaluated construct were removed. This refinement process improved the conceptual precision of the instrument and strengthened its content validity before proceeding to the empirical validation phase. The resulting set of items constituted the preliminary version of the questionnaire, which was subsequently subjected to a pilot study and an exploratory factor analysis to evaluate its dimensional structure.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Instrument development and pilot test\u003c/h2\u003e \u003cp\u003eOnce the initial pool of items had been generated from the qualitative exploratory phase and contrasted with the academic literature, a content validation process was conducted through expert evaluation. This procedure aims to ensure that the proposed indicators adequately represent the theoretical constructs intended to be measured by evaluating their clarity, conceptual relevance, and coherence with the study's theoretical framework [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e];[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe expert evaluation was conducted in April 2025 and involved five specialists with experience in university management, organisational social responsibility, and quantitative research methods. The selection of a small panel of experts follows methodological recommendations for content validation processes, in which the academic and professional expertise of the evaluators is prioritised over panel size, with participation of three to ten specialists common in instrument development studies [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e];[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe experts received a preliminary version of the instrument along with a description of the conceptual dimensions derived from the study's theoretical framework. Each item was evaluated according to three main criteria: semantic clarity, conceptual relevance, and coherence with the corresponding theoretical dimension. This procedure enabled the identification of potential ambiguities, redundancies, or inconsistencies in the formulation of the indicators, thereby facilitating the refinement of the initial pool of items.\u003c/p\u003e \u003cp\u003eBased on the expert panel's observations, adjustments were made to the wording of several indicators, and indicators that presented conceptual overlap or low relevance to the evaluated construct were removed. This refinement process improved the conceptual precision of the instrument and strengthened its content validity before proceeding to the empirical validation phase. The resulting set of items constituted the preliminary version of the questionnaire, which was subsequently subjected to a pilot study and an exploratory factor analysis to evaluate its dimensional structure.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Exploratory factor analysis.\u003c/h2\u003e \u003cp\u003eTo examine the preliminary dimensional structure of the instrument and evaluate the underlying grouping of the items, an exploratory factor analysis (EFA) was conducted using the data obtained from the pilot study in Jamovi 2.6.26 software. Exploratory factor analysis is a technique widely used in scale development studies, as it allows the identification of correlation patterns among observed variables and the exploration of the latent structure of constructs without imposing a priori restrictions on the measurement model [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough the pilot study sample (n\u0026thinsp;=\u0026thinsp;154) was relatively small compared with the instrument's initial number of items (43 indicators), it is considered acceptable for exploratory scale development studies. The methodological literature indicates that, although some authors recommend ratios of 5 or more cases per item, exploratory factor analyses may yield stable solutions when factor loadings and item communalities are sufficiently high [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Consequently, the pilot sample was deemed adequate for a preliminary examination of the instrument's factorial structure before proceeding to confirmatory validation with a larger sample.\u003c/p\u003e \u003cp\u003eFollowing methodological recommendations for psychometric studies, the adequacy of the data for factor analysis was evaluated using the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett's test of sphericity. KMO values above 0.60 indicate that the data are appropriate for factor analysis. At the same time, a significant result in Bartlett's test suggests that the correlation matrix differs significantly from an identity matrix, confirming the presence of sufficient relationships among the items to proceed with factor analysis [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e];[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFactor extraction was performed using the principal axis factoring method, recommended for identifying latent constructs in exploratory scale development studies [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e];[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Subsequently, an oblique Oblimin rotation was applied to improve the interpretability of the factorial structure. Oblique rotations are considered more appropriate in social science research when the underlying constructs are expected to be correlated, as they allow correlations among factors rather than imposing independence between them [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. This approach allows examination of the instrument's preliminary dimensional structure before proceeding to its confirmatory validation via structural equation modelling.\u003c/p\u003e \u003cp\u003eFactor retention was determined by considering multiple complementary criteria, including eigenvalues greater than 1, analysis of the scree plot, and the theoretical interpretability of the resulting dimensions. In addition, to ensure the quality of the indicators, items with factor loadings of 0.50 or greater were considered adequate, while avoiding cross-loadings among factors [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e];[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. These criteria allowed refining the initial pool of indicators and establishing the instrument's preliminary factorial structure, which was subsequently evaluated through confirmatory factor analysis.\u003c/p\u003e \u003cp\u003eAdditionally, to assess the preliminary internal consistency of the identified dimensions, Cronbach's alpha was estimated, one of the most widely used indicators of scale reliability in social science research. According to the criteria proposed by Cronbach [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] and subsequent developments in applied psychometrics, alpha values of 0.70 or higher are generally considered indicative of adequate internal consistency among the indicators composing each dimension [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e];[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The results of these reliability tests are presented in the results section.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Main data collection and sample\u003c/h2\u003e \u003cp\u003eFollowing preliminary refinement of the instrument based on the pilot study and exploratory factor analysis, data collection was conducted to validate the measurement model using confirmatory factor analysis. This stage aimed to evaluate the stability of the previously identified factorial structure and to examine the instrument's reliability and validity in an independent sample.\u003c/p\u003e \u003cp\u003eData collection was carried out between August and December 2025 at a public university in northern Mexico. The final instrument was administered electronically to undergraduate students enrolled in business programmes. This sampling strategy is common in scale development and validation studies in educational contexts, particularly when the objective is to examine institutional perceptions from students' direct experiences [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA total of 583 university students participated, all belonging to Generation Z, who currently constitute the predominant group in contemporary higher education systems and represent a particularly relevant cohort for analysing institutional conditions associated with inclusion, wellbeing, and sustainable educational experiences [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. The sample size used is consistent with methodological recommendations for confirmatory factor analysis and structural equation modelling, which suggest that samples exceeding 200 observations are needed to ensure stable estimates and adequate statistical power [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e];[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eParticipation in the study was voluntary and anonymous, always ensuring the confidentiality of the information provided by participants. Before completing the questionnaire, students received clear information about the research objectives, the academic use of the data, and their right to withdraw from the study at any time without consequences. The study design followed the ethical principles established in the Declaration of Helsinki, which emphasise the protection of participants in research involving human beings, including respect for autonomy, confidentiality, and informed consent [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe final questionnaire consisted of the items resulting from the refinement process carried out in the previous phases of the study. Participants evaluated each statement using a five-point Likert scale ranging from 1 (\u0026ldquo;strongly disagree\u0026rdquo;) to 5 (\u0026ldquo;strongly agree\u0026rdquo;). This type of scale is widely used in social science research to measure perceptions and attitudes, allowing the capture of gradual variations in the evaluation of organisational and institutional phenomena [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe data obtained in this phase were subsequently analysed using covariance-based confirmatory factor analysis to evaluate the instrument's factorial structure and examine the reliability and validity of the proposed measurement model.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.7. Confirmatory factor analysis\u003c/h2\u003e \u003cp\u003eTo evaluate the stability of the factorial structure identified in the exploratory phase and to examine the validity of the proposed measurement model, a confirmatory factor analysis (CFA) was conducted using covariance-based structural equation modelling (CB-SEM) in AMOS 22 software. CFA is a widely used technique in scale validation studies, as it allows empirical testing of the adequacy of a previously specified theoretical model and the evaluation of the relationships between observed indicators and the latent constructs intended to be measured [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e];[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe analysis was conducted using the maximum likelihood estimation method, one of the most frequently used procedures in structural equation modelling due to its ability to produce efficient and consistent estimates when the assumptions of multivariate normality and adequate sample size are satisfied [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. This approach is particularly appropriate for psychometric validation studies, as it allows the simultaneous evaluation of the instrument's reliability and the overall adequacy of the measurement model.\u003c/p\u003e \u003cp\u003eThe evaluation of model fit was carried out using multiple goodness-of-fit indices, following widely accepted methodological recommendations in the structural equation modelling literature. In particular, the Comparative Fit Index (CFI), the Root Mean Square Error of Approximation (RMSEA), and the Chi-square/degrees of freedom ratio (χ\u0026sup2;/df) were considered. According to the criteria proposed by Hu and Bentler [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], CFI values of 0.90 or higher indicate acceptable model fit, whereas values of 0.95 or higher indicate excellent fit. In the case of RMSEA, values below 0.08 are considered indicative of reasonable model fit, while values below 0.06 suggest optimal fit [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]; [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to overall model fit, the convergent validity of the constructs was evaluated using Average Variance Extracted (AVE) and Composite Reliability (CR). Following the recommendations of Fornell and Larcker [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e], AVE values greater than 0.50 indicate that the indicators adequately explain the variance of the latent construct. In contrast, CR values greater than 0.70 indicate satisfactory internal consistency.\u003c/p\u003e \u003cp\u003eDiscriminant validity among the constructs was examined using the Heterotrait-Monotrait ratio (HTMT), a criterion considered one of the most robust methods for evaluating differentiation among conceptually related constructs. According to Henseler et al. [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e], HTMT values below 0.85 suggest that the constructs present sufficient conceptual discrimination within the model.\u003c/p\u003e \u003cp\u003eTo assess the potential presence of common method bias (CMB), Harman\u0026rsquo;s single-factor test was conducted. The results showed that the first factor accounted for 31.4% of the total variance, which is below the recommended threshold of 50%, suggesting that common method bias is unlikely to be a significant concern in this study.\u003c/p\u003e \u003cp\u003eThese procedures allowed a rigorous evaluation of the adequacy of the proposed measurement model. They confirmed the instrument's factorial structure, designed to operationalise USR as an institutional infrastructure oriented towards equity in higher education.\u003c/p\u003e \u003cp\u003eTo provide a clear overview of the sequential process followed in the development and validation of the instrument, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarises the main stages of the research design, including the qualitative exploration, expert validation, pilot testing, exploratory factor analysis, and confirmatory validation phases.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOnce the sequential methodological process followed for the development and validation of the instrument has been described, the following section presents the empirical results derived from the analyses conducted in this study. In particular, the findings are reported according to the different stages of the validation process, beginning with the description of the sample profile and the results of the exploratory factor analysis conducted with the pilot data, followed by the confirmatory factor analysis and the evaluation of the reliability and validity of the proposed measurement model.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results","content":"\u003cp\u003eThis section presents the empirical results derived from the development and validation process of the proposed instrument. First, the qualitative findings from the focus groups with students are presented, which enabled the identification of relevant dimensions for understanding the institutional conditions associated with USR. Subsequently, the results of the content validation process conducted through expert evaluation are reported. Next, the profile of the sample used in the main study is described, and the results of the exploratory factor analysis applied to the pilot study data are presented to examine the instrument\u0026apos;s preliminary dimensional structure. Finally, the results of the confirmatory factor analysis and the evaluation of the reliability and validity indicators of the proposed measurement model are reported.\u003c/p\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e4.1. Qualitative findings (focus groups)\u003c/h2\u003e\n \u003cp\u003eTo explore how students perceive the institutional conditions that shape inclusive and socially responsible educational experiences, five focus groups were conducted with 8 participants each, for a total of 40 undergraduate students enrolled in business programmes. The groups were conducted using a semi-structured guide designed to discuss perceptions of educational infrastructure, institutional support, student wellbeing, opportunities for professional development, and experiences of integration within the university community.\u003c/p\u003e\n \u003cp\u003eThe information was analysed using the Atlas. ti 25 software through thematic coding, an approach widely used in exploratory studies to identify recurring patterns in participants\u0026apos; experiences and perceptions [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. The analytical process continued until theoretical saturation was reached, that is, the point at which the inclusion of new discussions no longer generated substantially different conceptual categories from those already identified [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. This procedure ensured that the identified domains consistently reflected students\u0026apos; shared experiences.\u003c/p\u003e\n \u003cp\u003eThe qualitative findings showed strong convergence between the conceptual domains identified in the literature review and the perceptions expressed by students in the focus groups. Participants highlighted the relevance of physical and digital learning conditions, institutional systems of academic support and wellbeing, as well as opportunities for applied learning and social and environmental engagement promoted by the university. Likewise, aspects related to inclusive institutional culture and a sense of belonging to the university community emerged clearly and were described as factors that strengthen student integration and retention.\u003c/p\u003e\n \u003cp\u003eIt should be noted that, although the literature review identified five broad conceptual domains associated with USR (learning infrastructure, institutional wellbeing, professional development, integral formation and identity and belonging), the qualitative analysis conducted through the five focus groups (n\u0026thinsp;=\u0026thinsp;40 students) confirmed the relevance of these areas from the students\u0026rsquo; perspective, while also showing that some institutional conditions tend to be perceived in a more differentiated manner within the university experience. Participants distinguished between different institutional support mechanisms and types of interaction with the university environment, suggesting that these conceptual domains may empirically manifest as more specific dimensions within the analysed educational context. Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarises the main categories identified during the focus groups and representative examples of the perceptions expressed by the participants.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eConceptual domains emerging from focus groups\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eConceptual domain\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eDescription\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eExample perception\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eLearning infrastructure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePhysical and digital conditions that facilitate access to educational resources and support learning processes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Having access to digital platforms and well-equipped classrooms helps students learn more effectively.\u0026rdquo;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eWellbeing and institutional benefits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eAcademic advising systems, psychological support, and services that support student wellbeing and academic progression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Students need academic advisors and counselling services to deal with academic pressure.\u0026rdquo;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eProfessional development and social engagement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eOpportunities for internships, applied learning, and university initiatives that connect students with social challenges.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Projects that allow students to work with communities help us understand the social role of the university.\u0026rdquo;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIntegral formation and inclusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eInstitutional environments that promote diversity, participation, and an inclusive academic culture\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Feeling respected regardless of background encourages students to participate more actively.\u0026rdquo;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIdentity and belonging\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eProcesses that strengthen students\u0026rsquo; integration and identification with the university community\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;When students feel part of the university community, they are more motivated to continue their studies.\u0026rdquo;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSource: Own elaboration.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eThese domains represent broad conceptual areas derived from both the literature review and the qualitative exploration. In subsequent quantitative analyses, these domains were further refined through exploratory factor analysis, yielding more specific measurement dimensions.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e4.2. Content validity (expert panel)\u003c/h2\u003e\n \u003cp\u003eTo evaluate the content validity of the preliminary instrument, the initial questionnaire version was submitted for review by a panel of five experts with academic and professional experience in USR, educational management, and applied psychometrics. The use of expert panels is a widely recommended procedure in scale development studies, as it allows the examination of the conceptual adequacy of items, their semantic clarity, and their correspondence with the theoretical constructs intended to be measured [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e];[\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThe experts evaluated the proposed dimensions considering three main criteria: clarity, relevance, and conceptual coherence. Clarity refers to the degree to which indicators are formulated in a manner understandable to potential participants; relevance evaluates the appropriateness of each dimension for representing the institutional conditions associated with USR; and coherence examines the consistency between the items and the conceptual domain to which they belong [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eTo quantify the level of agreement among the specialists, the Content Validity Index (CVI) was calculated using Jamovi 2.6.26. This indicator allows the evaluation of the degree of consensus among experts regarding the adequacy of the instrument\u0026apos;s elements. According to the psychometric literature, CVI values equal to or greater than 0.80 are considered indicative of adequate content validity when the panel consists of between three and ten evaluators [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eTable \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes the expert panel\u0026apos;s evaluations of the instrument\u0026apos;s preliminary dimensions.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eExpert evaluation of the instrument (Content Validity Index)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eDimension\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eClarity (CVI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eRelevance (CVI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eCoherence (CVI)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eLearning infrastructure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHealth and wellbeing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eInstitutional benefits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eProfessional development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSocial and environmental engagement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIntegral formation and inclusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIdentity and belonging\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSource: Own elaboration.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eThe results presented above showed high levels of agreement among the experts across all evaluated dimensions, with clarity values ranging from 0.88 to 0.96, relevance values ranging from 0.90 to 0.98, and conceptual coherence values ranging from 0.87 to 0.95. These results indicate that the proposed dimensions adequately capture the institutional domains associated with USR in higher education. In addition, the specialists\u0026apos; qualitative observations allowed refining the wording of several indicators and adjusting the formulation of certain items, thereby strengthening the conceptual consistency of the instrument before its application in the pilot study.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003e4.3. Sample characteristics\u003c/h2\u003e\n \u003cp\u003eTo contextualise the psychometric analyses conducted in the study, this section presents the characteristics of the two samples used in the instrument validation process: the pilot study sample, used for the exploratory factor analysis, and the main study sample, used for the estimation of the confirmatory model. The use of independent samples for the exploratory and confirmatory phases is a recommended practice in scale development studies, as it allows evaluation of the factorial structure\u0026apos;s stability and reduces the risk of model overfitting [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e];[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThe pilot sample consisted of 154 undergraduate students, whereas the main sample comprised 583 students enrolled in business programmes at a public university in northern Mexico. In both cases, participants predominantly belonged to Generation Z, a generational cohort characterised by its high familiarity with digital environments and its growing presence in contemporary higher education systems [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eIn demographic terms, the average age of participants in the pilot sample was 20.8 years (SD\u0026thinsp;=\u0026thinsp;1.7), whereas in the main sample the mean age was 21.2 years (SD\u0026thinsp;=\u0026thinsp;1.9). Regarding gender distribution, the pilot sample consisted of 57% women and 43% men, while the main sample comprised 59% women and 41% men. This distribution is consistent with the composition observed in university business programmes across different educational contexts [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eWith respect to academic level, participants spanned different years of university education, allowing the capture of perceptions from students at different stages of their educational trajectory. The mean semester completed in the main sample was 5.1 (SD\u0026thinsp;=\u0026thinsp;1.6), suggesting a balanced representation of students in intermediate and advanced phases of their academic programmes.\u003c/p\u003e\n \u003cp\u003eTable \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents a summary of the main demographic characteristics of both samples used in the study. The inclusion of these two samples aligns with the research\u0026apos;s sequential methodological design, in which the pilot data were used to identify the instrument\u0026apos;s preliminary factorial structure. In contrast, the main sample enabled the evaluation of the measurement model\u0026apos;s stability and validity through confirmatory factor analysis.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSample characteristics\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePilot sample (n\u0026thinsp;=\u0026thinsp;154)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eMain sample (n\u0026thinsp;=\u0026thinsp;583)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eAge (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e20.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e21.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e57%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e59%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e43%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e41%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSemester (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e4.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e5.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eAcademic programs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBusiness-related programs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eBusiness-related programs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSource: Own elaboration.\u003c/em\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003e4.4. Exploratory factor analysis\u003c/h2\u003e\n \u003cp\u003eTo examine the instrument\u0026apos;s preliminary factorial structure, an exploratory factor analysis (EFA) was conducted using data from the pilot study (n\u0026thinsp;=\u0026thinsp;154). EFA is a technique widely used in scale development studies in the social sciences, as it allows the identification of correlation patterns among observed variables and the exploration of the latent structure of constructs without imposing prior restrictions on the measurement model [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e];[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eBefore proceeding with factor extraction, the adequacy of the data was evaluated using the Kaiser-Meyer-Olkin (KMO) measure and Bartlett\u0026rsquo;s test of sphericity. The results showed a KMO value of .979, considered excellent according to the criteria established in the psychometric literature. Likewise, Bartlett\u0026apos;s test was statistically significant \u0026chi;\u0026sup2;(903)\u0026thinsp;=\u0026thinsp;33,696.93; p \u0026lt; .001, confirming the existence of sufficient correlations among the items to proceed with the factor analysis. These results indicate that the correlation matrix exhibits an appropriate pattern of interrelationships for identifying latent factors.\u003c/p\u003e\n \u003cp\u003eThe initial item pool consisted of 49 indicators derived from the qualitative phase and the theoretical review. During the exploratory factor analysis, items were evaluated based on their factor loadings, potential cross-loadings, and conceptual coherence with the underlying constructs. As a result of this refinement process, six items were eliminated, yielding a final exploratory solution comprising 43 items distributed across seven factors. Together, these factors accounted for 83.19% of the total variance, providing initial evidence of the proposed scale\u0026apos;s multidimensional structure.\u003c/p\u003e\n \u003cp\u003eFactor extraction was conducted using principal axis factoring (PAF), followed by an Oblimin rotation. This approach is recommended in scale development studies because it allows the identification of latent constructs while accounting for correlations among factors [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e];[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Factor retention was determined by considering multiple complementary criteria, including eigenvalues greater than 1, inspection of the scree plot, and the theoretical interpretability of the resulting dimensions.\u003c/p\u003e\n \u003cp\u003eThe initial eigenvalues indicated the presence of seven factors, which supported the retention of seven dimensions. Together, these factors explained 83.19% of the total variance, a percentage considerably higher than the levels commonly reported in social and educational research instruments, where multidimensional models typically explain between 50% and 60% of the total variance [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. This high level of explained variance suggests a strong alignment between the indicators and the underlying theoretical constructs. Nevertheless, the moderate to high factor loadings (.511-.820), together with the results of the discriminant validity and HTMT tests, indicate that the dimensions maintain adequate conceptual differentiation and do not exhibit redundancy among items. Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the scree plot, which shows a clear inflection point after the seventh component, confirming the appropriateness of retaining seven dimensions.\u003c/p\u003e\n \u003cp\u003eThe Oblimin rotation yielded a clear, conceptually interpretable factorial structure. The items were consistently grouped into seven dimensions, coherent with the proposed conceptual model: identity and belonging; integral formation and inclusion; professional development; philanthropy and environment; learning infrastructure; health and integral wellbeing; and institutional benefits. The philanthropy and environment dimension groups indicators related to student participation in solidarity activities, volunteering, and environmental responsibility actions within the university. In the statistical tables, this dimension appears abbreviated as FILAN, used only as a technical label within the factorial analysis. Factor loadings ranged between .50 and .82, exceeding the minimum threshold of .50 recommended for exploratory scale development studies.\u003c/p\u003e\n \u003cp\u003eIn general terms, the factorial solution showed a simple structure, without problematic cross-loadings and with conceptually coherent groupings, supporting the instrument\u0026apos;s preliminary stability. Table \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents the factor loadings for the items retained after extraction and rotation.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eExploratory factor analysis results (pilot sample)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eDimension\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eItem\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eFactor loading\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIdentity and belonging\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eID4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e0.815\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eID5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.804\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eID1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.803\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eID3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.796\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eID2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.699\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIntegral formation and inclusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"7\" rowspan=\"8\"\u003e\n \u003cp\u003e0.721\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCULTU5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.705\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCULTU1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.688\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCULTU2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.683\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCULTU3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.669\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCULTU8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.519\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCULTU7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.519\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCULTU9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.511\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eProfessional development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"7\" rowspan=\"8\"\u003e\n \u003cp\u003e0.692\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePROFE8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.669\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePROFE6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.668\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePROFE7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.657\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePROFE1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.618\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePROFE4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.604\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePROFE3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.594\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePROFE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.590\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSocial and environmental engagement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFILAN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"5\" rowspan=\"6\"\u003e\n \u003cp\u003e0.704\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFILAN3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.703\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFILAN4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.696\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFILAN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.665\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFILAN5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.664\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFILAN6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.654\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eLearning infrastructure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eINFRA3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e0.772\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eINFRA5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eINFRA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.752\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eINFRA4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eINFRA2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHealth and wellbeing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSYB2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSYB4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.787\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSYB5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.733\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSYB3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.693\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSYB1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.616\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eInstitutional benefits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBENEF2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e0.700\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBENEF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBENEF3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.643\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBENEF4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBENEF5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.617\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSource: Own elaboration.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eDespite the modest pilot sample size, the factor solution showed strong loadings and conceptual interpretability, supporting the robustness of the extracted dimensions.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n \u003ch2\u003e4.5. Confirmatory factor analysis\u003c/h2\u003e\n \u003cp\u003eTo evaluate the factorial structure of the instrument and confirm the adequacy of the proposed measurement model, a confirmatory factor analysis (CFA) was conducted using the main sample composed of 583 university students enrolled in business programmes at a public university in northern Mexico. The analysis was performed using covariance-based structural equation modelling (CB-SEM) in AMOS software, a technique widely employed in psychometric validation studies to evaluate theoretically grounded measurement models [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e];[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThe confirmatory model specified seven latent constructs corresponding to the dimensions identified in the exploratory factor analysis: identity and belonging; integral formation and inclusion; professional development; philanthropy and socio-environmental engagement; learning infrastructure; health and integral wellbeing; and institutional benefits.\u003c/p\u003e\n \u003cp\u003eThe adequacy of the model was evaluated using several global fit indices, following methodological recommendations widely accepted in the structural equation modelling literature. The indicators considered included the \u0026chi;\u0026sup2;/df ratio, the Comparative Fit Index (CFI), and the Root Mean Square Error of Approximation (RMSEA). According to the criteria established by Hu and Bentler [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] and Hair et al. [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], \u0026chi;\u0026sup2;/df values below 3, CFI values above .90, and RMSEA values below .08 indicate acceptable model fit.\u003c/p\u003e\n \u003cp\u003eThe results indicate an adequate fit of the proposed measurement model. As shown in Table \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, the fit indices reported \u0026chi;\u0026sup2;/df\u0026thinsp;=\u0026thinsp;2.74, CFI = .929, and RMSEA = .070, indicating that the estimated factorial structure satisfactorily reproduces the observed covariance matrix.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eModel fit indices of the confirmatory factor analysis\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFit index\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eRecommended threshold\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eResult\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eChi-square/df\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e2.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.929\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eRMSEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSource: Own elaboration.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the measurement model estimated through confirmatory factor analysis. This structural diagram shows the relationships between the latent constructs and their observed indicators, illustrating the correspondence between the proposed theoretical dimensions and the instrument\u0026apos;s empirical structure.\u003c/p\u003e\n \u003cp\u003eTable \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e also reports the standardised factor loadings, along with the Composite Reliability (CR) and Average Variance Extracted (AVE) indicators for each construct. The factor loadings ranged between .71 and .88, exceeding the minimum threshold of .50 recommended for scale validation studies [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Similarly, the CR values were above .90, and the AVE values exceeded the .50 threshold, confirming the instrument\u0026apos;s convergent validity.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eStandardised factor loadings and convergent validity\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eConstruct\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eItem\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eLoading\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eCR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eAVE\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eIdentity and belonging\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eID1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eID2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eID3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eID4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eID5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntegral formation and inclusion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"8\" rowspan=\"9\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"8\" rowspan=\"9\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessional development\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"7\" rowspan=\"8\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"7\" rowspan=\"8\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocial and environmental engagement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFILAN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"5\" rowspan=\"6\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFILAN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFILAN3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFILAN4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFILAN5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFILAN6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eLearning infrastructure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eINFRA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eINFRA2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eINFRA3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eINFRA4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eINFRA5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth and wellbeing\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSYB1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSYB2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSYB3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSYB4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSYB5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eInstitutional benefits\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBENEF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBENEF2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBENEF3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBENEF4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBENEF5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSource: Own elaboration.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eThese results support the internal consistency and stability of the proposed measurement model, confirming that the seven identified dimensions adequately represent the conceptual structure of the USR scale developed in this study.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n \u003ch2\u003e4.6. Reliability and discriminant validity\u003c/h2\u003e\n \u003cp\u003eTo evaluate the instrument\u0026apos;s internal consistency and examine the discriminant validity among the model\u0026apos;s constructs, several reliability and validity indicators recommended in scale development and validation studies in the social sciences were analysed [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e];[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eFirst, the internal consistency of the instrument\u0026rsquo;s dimensions was examined using Cronbach\u0026rsquo;s alpha coefficient (\u0026alpha;) and Composite Reliability (CR). As shown in Table \u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, all constructs presented \u0026alpha; values above .80 and CR values above .90, substantially exceeding the minimum thresholds recommended in the literature (\u0026alpha;\u0026thinsp;\u0026gt;\u0026thinsp;.70; CR \u0026gt; .70). These results indicate a high level of internal consistency among the indicators composing each dimension of the instrument.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eReliability and convergent validity of the constructs\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eConstruct\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s \u0026alpha;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eCR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eAVE\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eIdentity and belonging\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntegral formation and inclusion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessional development\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocial and environmental engagement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eLearning infrastructure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth and wellbeing\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eInstitutional benefits\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSource: Own elaboration.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eConvergent validity was also evaluated through the Average Variance Extracted (AVE). The AVE values reported for each construct were above the .50 threshold, indicating that the model\u0026apos;s dimensions explain more than half of the variance in their observed indicators and thus meet the criteria proposed by Fornell and Larcker [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Taken together, these results confirm that the indicators used adequately represent the model\u0026apos;s latent constructs.\u003c/p\u003e\n \u003cp\u003eSubsequently, the instrument\u0026apos;s discriminant validity among its dimensions was examined. For this purpose, two complementary criteria widely used in the structural equation modelling literature were applied: the Fornell-Larcker criterion and the Heterotrait-Monotrait (HTMT) index.\u003c/p\u003e\n \u003cp\u003eFirst, the square roots of the AVEs for each construct were compared with the correlations among constructs. As shown in Table \u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e, the square root of the AVE (presented on the diagonal) is greater than the correlations among constructs, indicating that each dimension shares more variance with its own indicators than with other constructs in the model. This result confirms the instrument\u0026apos;s discriminant validity according to the Fornell-Larcker criterion.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDiscriminant validity (Fornell\u0026ndash;Larcker criterion)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eConstruct\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eIB\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eIFI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eSEE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eLI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003eHW\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003eBEN\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIdentity and belonging (IB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.84\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIntegral formation and inclusion (IFI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.80\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eProfessional development (PD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.78\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSocial and environmental engagement (SEE)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.77\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eLearning infrastructure (LI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.83\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHealth and wellbeing (HW)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.81\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eInstitutional benefits (BEN)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.76\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSource: Own elaboration.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eDiagonal = \u0026radic;AVE.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eAdditionally, the Heterotrait\u0026ndash;Monotrait ratio (HTMT) index was calculated and is presented in Table \u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e. This index is currently considered one of the most robust methods for assessing discriminant validity in structural equation models [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. The obtained values were below the recommended threshold of .85, providing additional evidence that the instrument\u0026apos;s dimensions represent conceptually distinct constructs.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eHTMT ratios\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eConstruct\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eIB\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eIFI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eSEE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eLI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003eHW\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003eBEN\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIdentity and belonging\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIntegral formation and inclusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eProfessional development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSocial and environmental engagement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eLearning infrastructure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHealth and wellbeing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eInstitutional benefits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSource: Own elaboration (Note: All values \u0026lt; .85).\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eThese reliability and validity results support the psychometric robustness of the developed instrument, confirming that the proposed scale demonstrates adequate internal consistency, convergent validity, and discriminant validity.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\n \u003ch2\u003e4.7. Final instrument\u003c/h2\u003e\n \u003cp\u003eTo facilitate the replicability of the study and promote the use of the instrument in future research, this section presents the final version of the USR scale developed and validated in the present study.\u003c/p\u003e\n \u003cp\u003eFollowing the sequential instrument development process, which included a literature review, student focus groups, expert content validation, a pilot study, and exploratory and confirmatory factor analyses, a multidimensional scale composed of 7 dimensions and 43 items was developed. These dimensions reflect different institutional conditions associated with USR and its role in constructing inclusive and sustainable educational environments.\u003c/p\u003e\n \u003cp\u003eThe items were formulated as statements evaluated using a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). This measurement format is widely used in social science research because it can consistently and comparably capture perceptions and subjective evaluations across participants [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Table \u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e presents the final version of the instrument, including the dimensions and their corresponding items.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eFinal instrument of the University Social Responsibility Scale\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eDimension\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eItem\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eStatement\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eLearning Infrastructure (INFRA)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eINFRA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe classrooms and academic spaces at the university provide adequate lighting, ventilation, and comfort for studying.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eINFRA2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eAt my faculty, I have sufficient access to computer equipment, internet, and other technological resources required for my academic activities.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eINFRA3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe library facilities and study spaces are sufficient and appropriate for completing both individual and group work.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eINFRA4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe sports facilities, gym, and green areas at the university contribute positively to my physical and recreational well-being.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eINFRA5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eI consider the university\u0026rsquo;s facilities to be safe and well maintained, allowing me to carry out my activities without risk.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth and Wellbeing (SYB)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSYB1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe university provides access to psychological and emotional support services.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSYB2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe university implements sufficient initiatives aimed at promoting and protecting students\u0026rsquo; mental health.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSYB3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe basic medical care provided by the university is accessible and timely when required.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSYB4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe university provides clear and accessible information about available physical and mental health services.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSYB5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eI believe that the university is concerned with my overall well-being, not only my academic performance.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eInstitutional Benefits (BENEF)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBENEF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eI am aware of the institutional benefits offered by the university and have made use of them (e.g. scholarships, discounts, special programmes).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBENEF2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe financial support and incentives provided by the university help me to continue my studies.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBENEF3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe university regularly disseminates calls for applications that allow students to request resources for academic, research, entrepreneurial, or social projects.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBENEF4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eI perceive that the university aims to ensure that all students have access to services at an affordable cost.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBENEF5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eI consider the institutional benefits provided by the university to be genuine support for improving my experience as a student.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessional Development (PROFE)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe university offers high-quality academic programmes that contribute to my professional development.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe course content includes and promotes professional ethics and social responsibility.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe university\u0026rsquo;s academic programmes are relevant and aligned with current labour market requirements.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe subjects I take motivate me to generate creative ideas, entrepreneurial initiatives, and innovations.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eAt the university, I have received training to conduct scientific research and address contemporary issues.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe university incorporates scientific or applied research projects into most subjects.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe university facilitates connections with professional associations related to different degree programmes.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePROFE8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eI have received training in technological resources and other skills that enhance my competitiveness.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocial and Environmental Engagement (FILAN)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFILAN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eI have had the opportunity to participate in volunteer or community service programmes organised by the university.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFILAN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe university actively promotes and encourages participation in support initiatives during crises, disasters, or situations affecting vulnerable groups.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFILAN3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe university encourages me to participate in environmental activities such as reforestation, clean-up campaigns, or recycling initiatives.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFILAN4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe university implements ongoing recycling and environmental responsibility initiatives.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFILAN5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eI perceive that the university\u0026rsquo;s social and environmental actions genuinely contribute to improving the community and the environment.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFILAN6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eI believe that participating in philanthropic activities organised by the university has strengthened my sense of social responsibility.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntegral Formation and Inclusion (CULTU)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe university regularly offers cultural events (e.g. book fairs, concerts, plays, exhibitions) open to all students.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eI have attended at least one cultural event organised or promoted by the university during my studies.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eI believe that the university\u0026rsquo;s cultural activities contribute to my overall development beyond academic learning.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eInformation about workshops and artistic or cultural activities is communicated clearly and in a timely manner to all students.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eI feel that the university values and encourages my participation in artistic and cultural activities.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe university admits students regardless of their socio-economic or ethnic background.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe university\u0026rsquo;s facilities provide adequate accessibility for people with disabilities.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eI perceive that all students can participate in university activities regardless of their personal circumstances.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCULTU9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe university implements effective measures to prevent violence, harassment, bullying, and discrimination.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eIdentity and Belonging (ID)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eID1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eI feel proud to belong to this university.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eID2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eI perceive a supportive and collaborative environment among students in my faculty.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eID3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eThe university\u0026rsquo;s institutional activities and symbols (e.g. events, colours, logo, motto) strengthen my sense of identity.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eID4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eAs a student at this university, I feel that I am part of a meaningful and valuable mission.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eID5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eBeing part of this university provides me with a clear direction for my personal and professional development.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSource: Own elaboration.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eAll items were measured using a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThe present study aimed to develop and validate a multidimensional scale to operationalise the institutional conditions associated with USR-oriented equity within higher education institutions. Importantly, the proposed scale does not attempt to measure governance structures directly; rather, it captures how equity-oriented institutional practices associated with USR are perceived and experienced by students within the university environment.\u003c/p\u003e \u003cp\u003eThe results obtained provide robust empirical evidence that USR can be analysed through an integrated set of institutional conditions shaping students' educational experiences. In particular, the identified factorial structure confirms that dimensions such as learning infrastructure conditions, institutional wellbeing, academic support, professional development, integral formation, and sense of belonging constitute interrelated components of a university ecosystem oriented towards inclusion and sustainable learning. These findings are consistent with previous research indicating that USR should not be understood merely as a set of outreach activities or social and environmental engagement, but rather as an institutional approach that integrates academic, organisational, and social dimensions within university governance [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e];[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe results of the exploratory and confirmatory factor analyses revealed a final structure composed of seven dimensions, which empirically refines the five conceptual domains initially identified in the literature review and corroborated during the qualitative phase of the study. This finding suggests that although previous studies tend to conceptualise USR through broad institutional categories, students' experiences reveal that these conditions operate as more differentiated institutional mechanisms within university life. In this sense, the empirical validation process enabled disaggregating certain conceptual domains into specific dimensions, such as institutional support systems, professional development opportunities, and mechanisms of social engagement, which more precisely shape how students experience institutional policies and practices related to social responsibility within the university.\u003c/p\u003e \u003cp\u003eFrom a conceptual perspective, the results contribute to expanding the understanding of USR as an operational framework for managing equity in higher education. Several authors have argued that universities play a fundamental role in promoting more just and sustainable societies, not only through knowledge generation but also by configuring institutional environments that foster inclusion, participation, and the integral development of students [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]; [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In this regard, the scale developed in this study enables these normative principles to be translated into observable, measurable dimensions, facilitating the empirical analysis of how universities implement institutional practices oriented towards educational equity. Thus, the proposed instrument contributes to reducing one of the limitations identified in recent literature: the scarcity of validated measurement tools capable of systematically evaluating the impact of university policies on the construction of inclusive educational environments[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe findings also highlight the importance of considering the student experience as a central indicator for evaluating USR. Recent research has emphasised that inclusion processes in higher education do not depend solely on formal access to universities, but also on institutional conditions that facilitate student retention, wellbeing, and integration within the academic community [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]; [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. In line with this perspective, the focus group results from this study show that students perceive educational equity as a multidimensional phenomenon encompassing both structural aspects, such as technological infrastructure and access to academic resources, and relational factors, including institutional support, university culture, and a sense of belonging. In this way, the validated model confirms that USR manifests itself through a set of institutional practices that directly influence the quality of the educational experience.\u003c/p\u003e \u003cp\u003eAnother relevant contribution of the study is the integration of dimensions of student wellbeing and professional development into the USR framework. Traditionally, the literature on USR has emphasised universities' commitment to sustainable development and social responsibility in their relationships with society [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]; [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, the results of this research suggest that USR should also be understood as a process aimed at ensuring institutional conditions that promote student wellbeing, mental health, and professional preparation. This finding is particularly relevant in the contemporary context of digital transformation and increasing academic pressure within universities, where the promotion of healthy educational environments has become an essential component of institutional sustainability[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe study also provides empirical evidence from the Latin American context, a region where structural inequalities continue to pose a significant challenge for higher education systems. Several international reports indicate that although access to higher education in Latin America has increased considerably over recent decades, important gaps remain in retention, educational quality, and development opportunities across different social groups [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In this context, the development of measurement instruments capable of rigorously evaluating the institutional conditions that promote inclusion becomes essential for guiding evidence-based university policies. The scale proposed in this study offers a precise tool for diagnosing and monitoring these conditions within universities. Although the present study focuses on undergraduate students, the institutional domains identified in this scale may also inform broader discussions on inclusive and sustainable learning environments across the educational life cycle.\u003c/p\u003e \u003cp\u003eFinally, from a methodological perspective, the results confirm the validity of the sequential approach used to develop the instrument. The combination of literature review, qualitative exploration through focus groups, expert content validation, and exploratory and confirmatory factor analyses allowed the construction of a psychometrically robust scale. This methodological process follows classical recommendations for instrument development in the social sciences [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] and [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], and ensures that the identified dimensions reflect both theoretical foundations and students' empirical perceptions. Consequently, the scale developed in this research not only advances knowledge of USR but also provides a solid methodological foundation for future studies of educational governance and equity in higher education.\u003c/p\u003e"},{"header":"6. Theoretical and practical implications","content":"\u003cp\u003eThe results of this study have implications for both the theoretical development of USR and the institutional management of equity in higher education.\u003c/p\u003e \u003cp\u003eFirst, from a conceptual perspective, the developed instrument contributes to advancing the empirical operationalisation of USR as an institutional infrastructure oriented towards equity. Although USR has been widely discussed in the literature as a normative framework guiding universities' social and environmental engagement, numerous studies have highlighted the difficulty of translating this concept into measurable indicators capable of evaluating its implementation within educational institutions [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e];[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In this regard, the scale proposed in this research provides a tool capable of systematically capturing the organisational conditions shaping inclusive educational environments, thereby helping to address a methodological gap identified in previous studies on university governance and institutional sustainability.\u003c/p\u003e \u003cp\u003eSecond, the results expand understanding of equity in higher education by demonstrating that this phenomenon cannot be reduced solely to access policies or inclusion programmes, but is instead shaped by an integrated set of institutional conditions that influence students' educational experiences. The dimensions identified in the validated model (learning infrastructure, institutional wellbeing, academic support, professional development, integral formation, social and environmental engagement, and university identity) reflect the multidimensional nature of inclusion processes in higher education, which depend on both structural and cultural factors within universities [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e];[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. In this way, the proposed instrument enables progress towards a more holistic understanding of educational equity, aligned with contemporary approaches that conceive universities as institutional ecosystems that influence students' academic, social, and personal development [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrom a practical perspective, the developed scale provides higher education institutions with a systematic diagnostic tool to evaluate and monitor institutional conditions associated with USR. In a global context characterised by accelerated processes of digital transformation and increasing pressure to ensure more inclusive educational systems, universities require instruments capable of identifying areas for improvement in their institutional governance and guiding the implementation of evidence-based policies. In this regard, the proposed scale facilitates the evaluation of key dimensions of the educational environment that influence student retention, wellbeing and integration within the academic community.\u003c/p\u003e \u003cp\u003eMoreover, the instrument may contribute to the design and evaluation of institutional strategies to strengthen universities' social sustainability. Several international frameworks have emphasised the importance of higher education institutions incorporating principles of social responsibility and equity into their management models, particularly in relation to Sustainable Development Goal 4, which promotes inclusive and quality education for all [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In this context, the developed scale enables the generation of empirical information that can support institutional decision-making by facilitating the identification of gaps in access to educational resources, in the availability of student support services, or in the development of professional learning opportunities. In this sense, the scale also contributes to operationalising Sustainable Development Goal 4 by providing a tool to assess institutional conditions that support inclusive and equitable learning environments within universities.\u003c/p\u003e \u003cp\u003eFinally, the instrument also offers opportunities for comparative research on university governance and educational equity across different national contexts. The possibility of measuring USR dimensions in a standardised manner opens new avenues for research to examine how different higher education systems implement institutional strategies to promote inclusive educational environments. In this way, the proposed scale serves not only as an institutional diagnostic tool but also as a methodological resource that may advance knowledge on equity, sustainability, and governance in contemporary higher education.\u003c/p\u003e"},{"header":"7. Conclusion","content":"\u003cp\u003eThis study addressed a persistent limitation in the higher education literature: the difficulty of translating the normative principles of USR into empirical tools capable of evaluating how institutions construct equitable educational environments. By developing and validating a multidimensional scale grounded in students' experiences and a rigorous methodological process, this research provides an instrument that operationalises USR as a measurable institutional infrastructure within universities.\u003c/p\u003e \u003cp\u003eBeyond its methodological contribution, the study proposes a reinterpretation of USR from an educational governance perspective. Rather than understanding USR solely as a set of social and environmental engagement initiatives, the results show that it materialises through a network of institutional conditions (learning infrastructure, wellbeing, academic support, integral formation, professional development, social and environmental engagement, and university identity) that shape the educational experience and, ultimately, equity within the university system.\u003c/p\u003e \u003cp\u003eIn this way, the research contributes to advancing the academic dialogue on sustainability and higher education by offering a measurement model that enables a shift from the normative discourse on inclusion to its empirical evaluation. In contexts where universities face increasing pressure to demonstrate their social impact, the availability of valid, replicable instruments is essential for guiding institutional decision-making and strengthening the development of more inclusive and sustainable educational systems.\u003c/p\u003e"},{"header":"8. Limitations and future research directions","content":"\u003cp\u003eDespite the study's contributions, several limitations remain and offer opportunities for future research. First, the data were obtained from students belonging to a single public university in northern Mexico, which may limit the generalisability of the results to other institutional contexts or higher education systems. Second, the cross-sectional design of the study prevents examining how perceptions of USR evolve over time or across different stages of students' academic trajectories.\u003c/p\u003e \u003cp\u003eFurthermore, because the scale is based on students' perceptions, the instrument primarily captures the experiential dimension of USR rather than the full architecture of institutional governance. Future research could complement this approach by incorporating analyses of institutional policies or the perspectives of other university stakeholders, such as administrators, faculty members, or administrative staff, to examine more comprehensively how governance structures are translated into institutional practices oriented towards equity.\u003c/p\u003e \u003cp\u003eIn addition, although the scale was validated through rigorous psychometric procedures, its application in other cultural and educational contexts would strengthen the instrument's external validity. Consequently, future research could replicate the model across universities in different countries, compare public and private institutions, or explore relationships between the dimensions of USR and variables such as student retention, academic wellbeing, or educational performance, thereby expanding the analytical potential of the proposed scale.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests:\u003c/h2\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003ch2\u003eEthics approval:\u003c/h2\u003e\n\u003cp\u003eEthical approval for this study was granted by the Research Ethics Committee of CETYS University (Baja California, Mexico) on February 27, 2025. The study was reviewed and approved in accordance with institutional ethical standards and the National Guidelines for the Integration and Functioning of Research Ethics Committees (CONBIO\u0026Eacute;TICA, 2016). All procedures involving human participants were conducted in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments.\u003c/p\u003e\n\u003ch2\u003eConsent to participate:\u003c/h2\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study. Participation was voluntary and all responses were treated as confidential and anonymous.\u003c/p\u003e\n\u003ch2\u003eConsent to publish:\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eThe authors received no financial support for the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eL.R.L. conceived the study and led the qualitative phase, including item generation through focus groups. M.A.S.-A. contributed to the research design, statistical analysis, and interpretation of results. C.A.-A. supervised the study, contributed to the conceptual development, and coordinated the validation process. R.R.-R. contributed to the theoretical framework and critical revision of the manuscript. L.R.L. and M.A.S.-A. drafted the manuscript. All authors reviewed, edited, and approved the final version of the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eThe authors would like to thank the participants for their valuable contributions to this study, as well as the expert reviewers who supported the content validation of the instrument.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe datasets generated and analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAltbach PG, Berdahl RO, Berdahl RO, Gumport PJ. American higher education in the twenty-first century: Social, Political, and Economic Challenges. JHU Press; 2005.\u003c/li\u003e\n\u003cli\u003eSchofer E, Meyer JW. The worldwide expansion of higher education in the twentieth century. American Sociological Review [Internet]. 2005 Dec 1;70(6):898\u0026ndash;920. 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Available from: https://doi.org/10.1097/00006199-198611000-00017\u003c/li\u003e\n\u003cli\u003eBoateng GO, Neilands TB, Frongillo EA, Melgar-Qui\u0026ntilde;onez HR, Young SL. Best Practices for developing and Validating scales for health, Social, and Behavioral Research: A primer. Frontiers in Public Health [Internet]. 2018 Jun 11;6:149. Available from: https://doi.org/10.3389/fpubh.2018.00149\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"diedu","sideBox":"Learn more about [Discover Education](https://www.springer.com/journal/44217)","snPcode":"44217","submissionUrl":"https://submission.nature.com/new-submission/44217/3","title":"Discover Education","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"University social responsibility, Higher education governance, Equity in higher education, Inclusive education, Scale development, Generation Z students","lastPublishedDoi":"10.21203/rs.3.rs-9151678/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9151678/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHigher education systems are undergoing rapid digital and institutional transformation, intensifying concerns about equity, inclusion, and sustainable learning conditions. Although University Social Responsibility (USR) has increasingly been linked to the Sustainable Development Goals, particularly SDG 4, the literature still lacks robust measurement instruments to capture how equity-oriented institutional practices associated with USR are experienced within universities. This study develops and validates a multidimensional scale designed to measure students' perceptions of institutional conditions that support equitable and inclusive learning environments in higher education. The instrument was developed through a sequential mixed-method process. First, qualitative data from five student focus groups (n\u0026thinsp;=\u0026thinsp;40) were analysed to identify key institutional domains associated with socially responsible universities. Second, content validity was evaluated by a panel of five experts in higher education management and psychometrics. Third, a pilot study with undergraduate students (n\u0026thinsp;=\u0026thinsp;154) enabled exploratory factor analysis, followed by confirmatory factor analysis using data from a larger survey of Generation Z students (n\u0026thinsp;=\u0026thinsp;583) enrolled in business programmes at a public university in northern Mexico. Results support a seven-factor structure encompassing learning infrastructure, health and wellbeing, institutional benefits, professional development, social and environmental engagement, integral formation and inclusion, and identity and belonging. The model demonstrates strong psychometric properties, including satisfactory reliability, convergent validity, and discriminant validity. By capturing students' perceptions of institutional conditions related to university social responsibility and educational equity, the proposed scale provides universities with a diagnostic tool to systematically assess and improve inclusive and sustainable learning environments.\u003c/p\u003e","manuscriptTitle":"Operationalising equity in higher education: Development and validation of a university social responsibility scale","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-10 19:39:02","doi":"10.21203/rs.3.rs-9151678/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-17T18:12:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-16T11:39:01+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-14T20:16:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-12T13:31:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"209580784097467967805367166490047231781","date":"2026-04-12T13:27:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"215120068976145478337035723940041967332","date":"2026-04-11T15:46:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"82899243460260681711478543660577556733","date":"2026-04-11T10:48:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"103955977116240691331424170208573051798","date":"2026-04-08T23:37:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-08T08:02:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-07T16:08:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"173933647832973492507441130896960199013","date":"2026-04-06T15:58:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"212996243573484367461618511673082612112","date":"2026-04-06T14:53:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"47323311839485768389679696113322974501","date":"2026-04-06T12:03:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-06T09:31:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"81652630130743034022995877006871256305","date":"2026-04-06T08:48:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"122134927836245912444718953591606285678","date":"2026-04-06T08:32:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-06T07:54:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-21T04:23:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-21T04:22:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Education","date":"2026-03-17T17:51:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"diedu","sideBox":"Learn more about [Discover Education](https://www.springer.com/journal/44217)","snPcode":"44217","submissionUrl":"https://submission.nature.com/new-submission/44217/3","title":"Discover Education","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c8a6344f-fc40-4706-879a-2384acabb330","owner":[],"postedDate":"April 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-09T23:53:16+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-10 19:39:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9151678","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9151678","identity":"rs-9151678","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}