Grading Minds and Shaping Futures: A Multivariate Analysis on the Perceptions of Fairness Anxiety, Feedback Orientation and Motivation in Ghana’s Health Professions Education

Grading Minds and Shaping Futures: A Multivariate Analysis on the Perceptions of Fairness Anxiety, Feedback Orientation and Motivation in Ghana’s Health Professions Education | 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 Grading Minds and Shaping Futures: A Multivariate Analysis on the Perceptions of Fairness Anxiety, Feedback Orientation and Motivation in Ghana’s Health Professions Education Simon Ntumi, Paul Kobina EFFRIM, Clarke Ebow Yalley, Abraham Yeboah, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6958871/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract There is a critical gap in understanding how assessment-related psychological factors influence learning motivation and anxiety among students in Ghana’s health training institutions. The study investigated the relationships among perceived assessment fairness, feedback orientation, assessment anxiety, and academic motivation among students enrolled in health professions education in Ghana. Employing a quantitative approach nested in cross-sectional survey design, data were collected from 575 diploma and undergraduate students across six nursing and midwifery training institutions in the southern, middle, and northern ecological zones of Ghana. Stratified random sampling ensured representativeness across program type, year of study, and gender. Standardized instruments with strong internal consistency (Cronbach’s α ranging from 0.76 to 0.89) were used to measure the key constructs. Descriptive statistics revealed moderate to high levels of perceived fairness (M = 3.72, SD = 0.56), feedback orientation (M = 3.85, SD = 0.64), and academic motivation (M = 3.96, SD = 0.58), with relatively lower levels of assessment anxiety (M = 2.91, SD = 0.72). Pearson correlation analysis showed significant positive relationships between perceived assessment fairness and academic motivation (r = .46, p < .01), as well as between feedback orientation and academic motivation (r = .60, p < .01). Assessment anxiety correlated negatively with both feedback orientation (r = –.28, p < .01) and academic motivation (r = –.41, p < .01). Multiple regression analysis revealed that procedural fairness (β = .11, p = .046), distributive fairness (β = .10, p = .025), and feedback utility (β = .21, p < .001) were significant positive predictors of academic motivation, whereas assessment anxiety (β = –.23, p < .001) was a significant negative predictor. The overall regression model explained 42% of the variance in academic motivation (R² = 0.42, F(6, 568) = 67.39, p < .001), indicating a robust multivariate relationship. These findings highlight the importance of fair assessment practices and constructive feedback in enhancing student motivation while mitigating anxiety. The study has practical implications for assessment reforms and educator training within Ghana’s health education sector, advocating for psychologically informed approaches to curriculum delivery and evaluation. Assessment fairness Feedback orientation Academic motivation Assessment anxiety Health professions education Ghana Introduction Assessment plays a pivotal role in shaping student learning, especially in health professions education, where both formative and summative evaluations inform pedagogical practices, competency development, and progression decisions [11; 10; 24; 35; 1]. Assessment not only serves as a mechanism for measuring the acquisition of knowledge and skills but also guides curriculum refinement, provides accountability, and facilitates professional accreditation [12; 34]. In clinical and pre-clinical training, high-stakes decisions such as licensure, placement, and graduation are often based on the results of summative assessments, while formative assessments offer learners opportunities to receive structured feedback, develop clinical reasoning, and reflect on their learning trajectories [1; 10; 2; 7; 26]. In the Ghanaian context, health education programs ranging from medicine and nursing to allied health sciences rely heavily on rigorous assessments to determine student competence and readiness for professional practice [43; 21; 26]. The structure of these programs often reflects global standards but is delivered within local constraints, including limited clinical exposure, faculty shortages, and variability in assessment literacy among instructors [23; 1; 5; 4]. Consequently, while assessments are intended to drive learning and ensure competence, their design and implementation can significantly affect students’ psychological experiences, particularly in relation to perceptions of fairness, receptivity to feedback, test anxiety, and motivation. Assessment fairness, defined as the perceived justice and transparency in evaluation methods, significantly influences students’ trust in the education system and their academic engagement [9; 32; 3]. When students believe that assessment criteria are objective, consistent, and aligned with course content, they are more likely to adopt mastery-oriented approaches to learning and view assessments as constructive challenges rather than threats [55; 56; 26]. Conversely, in settings where resources are limited and educational equity is still evolving, such as Ghana, perceptions of unfair or biased assessment practices such as inconsistent grading, ambiguous test items, or lack of clear rubrics can deepen academic stress, reduce performance, and erode students’ confidence in the education system [13; 12; 53; 31]. Similarly, feedback orientation, which refers to students’ attitudes and openness to receiving and using feedback, has been identified as a crucial determinant of academic improvement and professional identity formation [7; 9; 8, 3; 26]. Health professions education places considerable emphasis on feedback both in classroom and clinical settings as a means of helping learners calibrate their self-assessments, identify performance gaps, and plan for improvement. However, the effectiveness of feedback is often undermined by factors such as poor timing, lack of specificity, unidirectional delivery, and students’ emotional responses [8; 18]. In Ghana, anecdotal evidence and emerging research suggest that students in health programs may receive limited actionable feedback, often constrained by overcrowded classrooms, high faculty workload, and a culture of summative assessment dominance [ 43 ]. More broadly, the interplay between students’ perceptions of fairness and feedback experiences has critical implications for their psychological wellbeing and academic functioning. Assessment that is perceived as arbitrary or punitive can heighten assessment anxiety, a form of performance-related stress that impairs working memory, lowers self-efficacy, and affects decision-making under pressure [14; 16; 17; 45]. In high-stakes environments such as medical and nursing schools where the consequences of failure are steep assessment anxiety may become chronic, leading to burnout or disengagement [26; 2; 42]. Furthermore, such anxiety often interacts with motivational constructs, such as intrinsic and extrinsic academic motivation, shaping how students approach learning tasks, persist in the face of difficulty, and develop self-regulation [22; 23]. Assessment anxiety, a prevalent issue among students in high-stakes academic environments, has been consistently associated with impaired cognitive functioning, reduced academic performance, and increased psychological distress especially in demanding and competitive disciplines such as the health sciences [10; 12; 11; 30; 40]. This form of anxiety often manifests as physiological symptoms (e.g., rapid heartbeat, sweating), cognitive interference (e.g., intrusive thoughts, worry), and behavioral avoidance, all of which compromise students’ ability to retrieve knowledge and apply critical thinking under pressure [10; 12; 11; 30; 40]. In clinical education settings, where students are evaluated through written exams, practical demonstrations, and clinical rotations, the pressure to perform competently in front of peers and evaluators can amplify performance-related stress. Anxiety levels are particularly heightened when students perceive assessments as unpredictable, overly punitive, or disconnected from clearly communicated instructional goals and learning outcomes [10; 12; 11; 30; 57]. The lack of alignment between teaching and assessment can create a perception of arbitrariness, further exacerbating students’ sense of vulnerability and loss of control. Concurrently, academic motivation, whether intrinsic (driven by curiosity and interest) or extrinsic (driven by grades, rewards, or external approval), plays a critical role in determining how students engage with learning and cope with assessment-related pressures [ 22 ]. Students with strong intrinsic motivation are more likely to approach learning with persistence, deep processing, and resilience, even in the face of challenging evaluations [49; 63; 28]. In contrast, extrinsically motivated students may perform adequately in the short term but are often more susceptible to anxiety, avoidance behaviors, and reduced long-term retention, particularly when rewards are perceived as contingent on high-stakes performance [10; 12; 30; 40]. In academic contexts where summative assessments dominate such as Ghana’s health professions education sector the overemphasis on final grades and pass/fail outcomes may inadvertently shift students’ focus from mastery of content to performance goals, thereby undermining intrinsic motivation and fostering a transactional view of learning [21; 62; 27]. When evaluations are seen primarily as hurdles to be cleared, rather than as integral components of a developmental learning process, students may become disengaged or overly anxious, reducing both their academic effectiveness and psychological well-being. This complex interplay between assessment anxiety and academic motivation underscores the need for balanced assessment systems that integrate formative practices, offer timely and constructive feedback, and cultivate learning environments that support student autonomy and competence [13; 18; 3; 61; 58]. Such approaches are not only pedagogically sound but also essential for nurturing self-regulated learners capable of thriving in the emotionally and cognitively demanding field of health care. Despite the critical role that assessment plays in shaping student learning, especially within health professions education, there remains limited understanding of how psychological factors such as assessment anxiety, perceptions of fairness, feedback orientation, and academic motivation interact to influence student experiences and outcomes particularly in the context of sub-Saharan Africa. Globally, the literature has established that students’ perceptions of assessment fairness and feedback quality are central to engagement, trust, and performance. Moreover, a substantial body of research has demonstrated that high levels of assessment anxiety can hinder cognitive processing, impair academic performance, and even contribute to burnout and attrition in demanding academic programs [14; 10] While these psychological dynamics have been widely examined in Western and high-income countries, relatively few studies have focused on how they manifest in low-resource settings such as Ghana, where educational infrastructures, faculty capacity, and student support services may differ markedly. In Ghana’s health education sector, summative assessments often high-stakes in nature continue to dominate the evaluative landscape, sometimes to the neglect of formative, feedback-rich practices that foster self-regulation and deeper learning [43; 23; 19]. Although efforts are underway to shift toward more competency-based and learner-centered models, the extent to which students perceive these assessment practices as fair, transparent, and supportive remains underexplored. Anecdotal reports and limited local studies suggest that students often express dissatisfaction with unclear assessment criteria, insufficient feedback, and lack of consistency in grading practices [4; 8; 10]. These factors may contribute to elevated levels of test anxiety and diminished motivation, yet empirical investigations linking these variables in Ghanaian health professions education are sparse. This is a significant gap, given the emotionally and cognitively taxing nature of clinical education and the high expectations placed on students preparing for roles in critical sectors such as medicine, nursing, and allied health sciences. Furthermore, most existing studies in Ghana have treated these psychological constructs in isolation focusing solely on test anxiety or feedback mechanisms without examining their interconnected effects within comprehensive assessment systems. The multivariate interplay between perceived fairness, feedback orientation, assessment anxiety, and academic motivation has not been sufficiently theorized or empirically tested in Ghanaian higher education settings, particularly within health training institutions. As such, there is a pressing need for contextually grounded, theory-informed research that investigates how these variables converge to affect student performance, well-being, and professional identity formation. Addressing this gap is crucial for informing the design of more equitable, psychologically supportive, and pedagogically effective assessment practices in Ghana and comparable educational contexts. Theoretical Framework: Self-Determination Theory (SDT) Self-Determination Theory (SDT), developed by [ 22 ], offers a comprehensive framework for understanding human motivation, psychological development, and well-being. At its core, SDT posits that individuals possess innate psychological needs for autonomy, competence, and relatedness. When these needs are supported within a given environment, individuals are more likely to experience self-motivation, engagement, and personal growth. In contrast, when these needs are thwarted, motivation tends to diminish, leading to disengagement and reduced well-being. In educational settings particularly in health professions education where students are often exposed to high-pressure and high-stakes assessment environments SDT provides a valuable lens through which to understand how learners respond to various assessment practices, such as formative and summative assessments. Autonomy, as one of the three central components of SDT, refers to the individual’s need to feel that their actions are self-endorsed and reflect personal choice rather than external pressure [22; 23]. In the context of assessment, autonomy is supported when students perceive that assessments are fair, transparent, and give them the opportunity to demonstrate learning in diverse and meaningful ways. When students are provided with choices in how they engage with assessments or receive feedback that respects their viewpoints and encourages self-reflection, they are more likely to feel autonomous and intrinsically motivated. On the other hand, perceptions of biased, rigid, or punitive assessments can diminish students’ sense of control, undermining their motivation and increasing resistance to learning. The second component, competence, refers to the need to feel effective and capable of achieving desired outcomes. Students in health professions education often operate in academically demanding environments that require mastering complex content and demonstrating clinical proficiency. When assessment practices especially formative assessments provide clear criteria, actionable feedback, and opportunities for improvement, they enhance students’ perceptions of competence [22; 23]. Constructive feedback that highlights strengths, suggests specific improvements, and acknowledges effort can reinforce students’ belief in their ability to succeed. Conversely, vague or overly critical feedback and high-stakes summative assessments that are perceived as unpredictable or unfair may lead to feelings of inadequacy and self-doubt, fostering assessment anxiety and reducing confidence. Relatedness, the third psychological need, involves the desire to feel connected to others and to experience mutual respect and care. In academic settings, relatedness is fostered when students feel that their instructors are approachable, supportive, and genuinely invested in their learning. Feedback plays a critical role in building this connection. When feedback is delivered in a personalized, empathetic, and constructive manner, students are more likely to feel supported and understood. This sense of relatedness not only enhances motivation but also buffers the negative emotional effects of academic stress, such as anxiety and burnout. Conversely, feedback that is impersonal, dismissive, or overly critical can alienate students and hinder engagement [22; 23]. In this study, SDT is applied to understand the interplay between students’ perceptions of assessment fairness, feedback orientation, assessment anxiety, and academic motivation in the context of formative and summative assessment practices within health professions education in Ghana. Assessment fairness is theorized to influence all three psychological needs. When students perceive assessments as fair meaning they believe the procedures, grading, and expectations are consistent and just they are more likely to feel autonomous, competent, and respected. Similarly, feedback orientation, or the extent to which students seek out, value, and use feedback, is closely tied to autonomy and competence [22; 23; 47]. Students who receive feedback that supports learning, rather than simply judging performance, are more likely to remain motivated and take ownership of their academic development. Assessment anxiety is conceptualized within this framework as a psychological response that emerges when one or more of the basic needs is thwarted especially competence and autonomy. High levels of anxiety often reflect students’ fears of being judged unfairly or failing to meet expectations, which can be exacerbated by unclear or rigid assessment systems [22; 23; 46]. In contrast, environments that foster autonomy, build competence, and promote relatedness can help mitigate anxiety and promote resilience. Academic motivation, whether intrinsic (driven by curiosity and mastery) or extrinsic (driven by grades and approval), is thus seen as the outcome of the extent to which these psychological needs are fulfilled within the assessment context. By anchoring the study in SDT, the research highlights the importance of designing and implementing assessment systems in health professions education that do more than measure knowledge they must also support students’ psychological needs. Fair and transparent assessments, feedback that is timely and meaningful, and emotionally supportive interactions with educators all contribute to healthier motivational profiles among students. Such practices can reduce assessment anxiety, encourage academic persistence, and foster a more positive learning climate in demanding academic programmes such as nursing, midwifery, and medical laboratory sciences. In doing so, SDT not only guides the interpretation of empirical findings in this study but also provides actionable insights for educational policy and practice. Research Questions What is the relationship between perceived assessment fairness and academic motivation among health professions students in Ghana? To what extent does feedback orientation predict assessment anxiety among health professions students in Ghana? To what extent do perceived assessment fairness, feedback orientation, and assessment anxiety jointly predict academic motivation among health professions students in Ghana? Methods Research Design The study adopted a cross-sectional survey design to investigate the multivariate relationships among four key psychological constructs: perceived assessment fairness, feedback orientation, assessment anxiety, and academic motivation among students enrolled in health professions education in Ghana. The cross-sectional approach was particularly suitable given the need to collect standardized, self-reported data from a large and diverse sample of students at a single point in time. This design allowed for the examination of both correlational and predictive patterns between variables, facilitating a data-driven understanding of how assessment experiences shape students’ psychological and motivational responses [21; 50]. The choice of a quantitative design was underpinned by the objective of statistically testing predefined hypotheses and identifying generalizable trends that could inform educational policy and assessment reform in the Ghanaian health education sector. Furthermore, this approach aligns with previous research in medical and nursing education, where survey methods have been extensively used to quantify psychological factors affecting student learning and performance [7; 9; 12; 38]. The design also supported the use of multivariate techniques such as multiple regression and structural equation modeling, which are particularly effective for analyzing complex interrelationships among variables. Population and Sampling The target population for this study consisted of diploma and undergraduate students enrolled in accredited nursing and midwifery training institutions in Ghana. To capture a broad and representative sample, the study included students from six major nursing and midwifery training colleges across three ecological zones of the country: Southern Zone : Korle-Bu Nurses and Midwifery Training College (Greater Accra Region) and Cape Coast Nursing and Midwifery Training College (Central Region) Middle Zone : Kumasi Nurses and Midwifery Training College (Ashanti Region) and Kintampo College of Health and Wellbeing (Bono East Region) Northern Zone : Tamale Nurses and Midwifery Training College and Bolgatanga Midwifery Training College (Upper East Region) These institutions were purposively selected to ensure a diverse student demographic in terms of regional background, language, cultural identity, and academic orientation. This strategy also supported the study’s aim to examine psychological responses in varied institutional settings urban, peri-urban, and rural where disparities in resources and instructional quality may influence assessment experiences. A stratified random sampling technique was employed to draw participants across key strata, including program type (nursing vs. midwifery), year of study (first, second, and third year), and gender. This method enhanced the representativeness and precision of the sample while controlling for confounding demographic variables [ 29 ]. Based on [ 17 ] formula for sample size determination in finite populations, and assuming a 95% confidence level with a 5% margin of error, a minimum of 500 students was deemed necessary. An additional 15% was added to account for incomplete responses and dropout, resulting in a target sample size of approximately 575 participants. Institutional research boards and administrative authorities were contacted for permission, and assistance from faculty liaisons and student leaders facilitated access to class email lists and social media platforms for the dissemination of survey links. This large and geographically distributed sample allowed for stronger external validity and the ability to conduct subgroup analyses (e.g., comparing nursing vs. midwifery students, or first-year vs. third-year students), thus enriching the interpretive scope of the findings. Instrumentation The study employed a structured online questionnaire consisting of four validated psychometric scales, each corresponding to one of the study’s key constructs: Perceived Assessment Fairness, Feedback Orientation, Assessment Anxiety, and Academic Motivation. All items were presented in English the medium of instruction in Ghanaian tertiary institutions and formatted using a five-point Likert scale (1 = Strongly Disagree to 5 = Strongly Agree), to allow for nuanced gradations in student responses. Perceived Assessment Fairness : This construct was measured using an adapted version of the Assessment Fairness Perceptions Scale (AFPS) developed by Green et al. (2007). The original items were reviewed and modified for cultural and contextual appropriateness within the Ghanaian health education system. The scale examined students’ perceptions of procedural fairness, grading transparency, and equity in assessment opportunities. Sample items included statements such as “Assessment criteria are applied consistently to all students” and “I understand how my grades are calculated.” Feedback Orientation : Students’ openness to and valuation of feedback were measured using the Feedback Orientation Scale (FOS) developed by [ 36 ]. The scale includes four subdimensions: utility of feedback, feedback self-efficacy, accountability, and social awareness. This instrument has been validated across educational settings and was found to be particularly relevant in professional training contexts where constructive feedback is integral to clinical development [ 60 ]. Assessment Anxiety : The short form of the Test Anxiety Inventory (TAI-SF) by [ 57 ] was used to measure cognitive and emotional responses to assessment situations. This inventory, widely employed in health education research, focuses on worry, emotionality, and interference with task performance. Prior studies have found the TAI-SF to be valid and reliable in populations including nursing and midwifery students [ 15 ]. Academic Motivation : Academic motivation was assessed using the Academic Motivation Scale (AMS) developed by [ 59 ], based on Self-Determination Theory (SDT). This scale captures various forms of motivation: intrinsic motivation (e.g., learning for personal growth), extrinsic motivation (e.g., studying for rewards or recognition), and amotivation. The AMS has been widely validated across disciplines, including in low- and middle-income countries, and was selected for its relevance to educational psychology in culturally diverse contexts [ 22 ]. Before full deployment, a pilot study was conducted with 30 students from a non-participating nursing college to assess comprehension, clarity, and cultural relevance of the survey items. Feedback from the pilot led to minor modifications in phrasing for local terminology and clarity. The internal consistency of each scale was evaluated using Cronbach’s alpha, with values ranging from 0.76 to 0.89, indicating acceptable to excellent reliability [ 11 ]. All instruments were embedded into the Google Forms platform, which supported mobile accessibility and enabled automatic data export for statistical analysis. Data Collection Procedure Data were collected through a self-administered online survey hosted on Google Forms, over a period of four weeks. This approach was chosen primarily for its accessibility, cost-effectiveness, and ethical appropriateness, particularly in the context of ongoing post-COVID-19 and other related health protocols, which discouraged prolonged face-to-face engagements in many academic institutions [20; 10]. The online mode also facilitated the efficient reach of a geographically dispersed sample, as students were enrolled in various institutions across different regions of Ghana. To ensure effective distribution of the survey, institutional gatekeepers, including academic coordinators and heads of departments, were contacted through formal email and phone communication. Upon receiving administrative approval, these gatekeepers disseminated the survey link via institutional mailing lists, official WhatsApp class platforms, and student portals, ensuring wide visibility and engagement across cohorts. The use of digital platforms such as WhatsApp was especially crucial in the Ghanaian context, where students rely heavily on mobile communication for academic and social interaction [ 44 ]. At the beginning of the survey, participants were presented with a detailed informed consent form, explaining the purpose of the study, procedures involved, potential risks and benefits, confidentiality assurances, and voluntary nature of participation. Students were explicitly informed of their right to withdraw from the survey at any point without penalty or academic consequence. Participation required active consent via a checkbox before proceeding to the questionnaire. The survey was designed to take approximately 15–20 minutes to complete. To improve response rates, weekly reminder messages were sent through class representatives and faculty liaisons. Additionally, students were incentivized with an optional entry into a lucky draw for educational materials such as mobile data vouchers or textbook discounts, approved by ethical review committees and communicated transparently in the consent form. Data Analysis Data collected from the online survey were exported directly from Google Forms into IBM SPSS Statistics Version 27.0 for cleaning, coding, and statistical analysis. Prior to formal analysis, data were screened for missing values, outliers, and inconsistencies. Cases with substantial missing data (greater than 20% of items unanswered) were excluded from the analysis to maintain data integrity. Minor missing values were addressed using mean substitution for continuous variables, ensuring minimal distortion of the dataset. Descriptive statistics were computed to summarize the demographic characteristics of participants and central tendencies of the key variables, including means, standard deviations, ranges, and frequency distributions. Internal consistency for each psychometric scale was assessed using Cronbach’s alpha, with all constructs exceeding the recommended threshold of 0.70, indicating good reliability [ 41 ]. To explore associations between variables, Pearson correlation coefficients were calculated. This bivariate analysis provided insight into the direction and strength of relationships among perceived assessment fairness, feedback orientation, assessment anxiety, and academic motivation. Preliminary tests for normality (via Shapiro-Wilk), linearity (via scatterplots), and multicollinearity (using Variance Inflation Factor - VIF) were conducted to meet the assumptions required for parametric testing. Subsequently, multiple linear regression analysis was conducted to assess the predictive power of the independent variables (perceived assessment fairness, feedback orientation, and assessment anxiety) on the dependent variable (academic motivation). This approach allowed for an understanding of the unique and combined contributions of each predictor, while controlling for potential overlap. Statistical significance was evaluated at p < .05, and standardized beta coefficients were used to compare the relative strength of the predictors. The findings were interpreted within the theoretical frameworks of Self-Determination Theory [ 22 ], which explains how intrinsic and extrinsic motivators influence student behavior. The analysis ultimately provided empirical evidence regarding the psychological factors that underpin motivation among health professions students in Ghana, offering insights for policy, curriculum development, and student support services in nursing and midwifery education. Ethical Considerations Ethical approval for the study was obtained from the Research Ethics Committee of the University of Education, Winneba, with further institutional permission granted by the participating nursing and midwifery colleges, including Korle-Bu Nurses Training College, Cape Coast Nursing and Midwifery Training College, and Tamale Nurses and Midwifery Training College. All ethical procedures conformed to the guidelines of the Declaration of Helsinki [ 61 ] and the Ghana Health Service Research Ethics Policy. Prior to data collection, an informed consent form was included as the first section of the online questionnaire. Participants were informed about the purpose of the study, the nature of their participation, the expected time commitment, and their rights to confidentiality, anonymity, and voluntary withdrawal without penalty. Only students who actively consented by ticking a checkbox were able to proceed with the questionnaire. Data were collected anonymously, and no identifying information such as names, student numbers, or IP addresses was recorded. All responses were stored in a password-protected digital folder, accessible only to the principal researcher and co-investigators. Participants were also informed that the data would be used strictly for academic purposes and would be reported in aggregate form to prevent the identification of individuals or institutions. To mitigate any potential distress arising from reflection on personal anxiety or motivational issues, contact information for institutional counseling services was provided at the end of the survey. Students were encouraged to seek support if the survey content triggered discomfort or academic concerns. In all, ethical rigor was maintained throughout the research process to uphold the dignity, privacy, and welfare of participants, particularly given the sensitive psychological variables under investigation. Results This aspect of the study presents the key empirical findings derived from the statistical analysis of the dataset. The analysis was guided by the study’s main objectives: to examine the relationships among perceived assessment fairness (PAF), feedback orientation (FO), assessment anxiety (AA), and academic motivation (AM) among respondents. The presentation begins with an assessment of the reliability and internal consistency of the measurement instruments used. This is followed by descriptive statistics for each of the major constructs and their subcomponents, offering insights into central tendencies, dispersion, and distribution characteristics. Subsequently, correlation analyses are reported to explore the strength and direction of associations among the variables. This is followed by multiple regression analysis to identify the predictive power of PAF, FO, and AA on AM. Finally, mediation and moderation analyses are conducted to further clarify the indirect and conditional relationships between the variables. The findings are presented in tabular format and discussed with reference to statistical significance, effect sizes, and confidence intervals. Table 1 Reliability Results Scale Cronbach’s Alpha M SD SEM Min Max Skew Kur R CV (%) 95% CI PAF 0.82 3.72 0.56 0.032 1.80 4.90 -0.41 0.12 3.10 15.05 3.66–3.78 FO 0.85 3.85 0.64 0.037 2.10 4.80 -0.58 0.45 2.70 16.62 3.77–3.93 AA 0.76 2.91 0.72 0.042 1.50 4.70 0.29 -0.44 3.20 24.75 2.82–3.00 AM 0.89 3.96 0.58 0.033 2.30 4.90 -0.67 0.68 2.60 14.65 3.90–4.02 Note. Cronbach’s alpha (α) values for all scales exceeded the acceptable threshold of 0.70, indicating good internal consistency. Descriptive statistics show that responses were moderately dispersed, with acceptable skewness and kurtosis values supporting normality assumptions. Coefficient of Variation (CV) highlights the relative variability, with Assessment Anxiety (AA) being the most variable construct. In Table 1 , the internal consistency reliability of all constructs was acceptable to excellent, as shown by Cronbach’s alpha values. Academic Motivation (AM) demonstrated the highest reliability (α = 0.89), followed by Feedback Orientation (FO; α = 0.85), Perceived Assessment Fairness (PAF; α = 0.82), and Assessment Anxiety (AA; α = 0.76). These coefficients indicate that the scales used were psychometrically robust and suitable for further analysis. The means for the constructs ranged from 2.91 (AA) to 3.96 (AM), suggesting generally moderate to high levels of the studied psychological constructs among respondents. The standard deviations were all below 1.00, indicating moderate dispersion, with AA showing the greatest variability (SD = 0.72). The standard error of the mean (SEM) values were low across all constructs, suggesting high precision in the mean estimates. Skewness and kurtosis values were within acceptable ranges for normal distribution assumptions (between − 1 and + 1). All constructs, except AA (which was slightly positively skewed), demonstrated slight negative skewness indicating that more respondents rated these variables at the higher end of the scale. The coefficient of variation (CV) further highlighted the relative variability of the constructs, with AA showing the greatest variability (CV = 24.75%) and AM showing the least (CV = 14.65%). Table 2 Descriptive Statistics for Key Constructs and Subscales Construct / Sub-Variable Mean SD Min Max Skewness Kurtosis 95% CI (Lower–Upper) Perceived Assessment Fairness (Total) 3.72 0.56 1.80 4.90 -0.41 0.12 3.65–3.79 – Procedural Fairness 3.68 0.60 1.80 4.90 -0.36 -0.02 3.60–3.76 – Distributive Fairness 3.74 0.58 2.00 4.80 -0.43 0.17 3.66–3.82 – Interactional Fairness 3.74 0.59 2.10 4.85 -0.45 0.21 3.66–3.82 Feedback Orientation (Total) 3.85 0.64 2.10 4.80 -0.58 0.45 3.77–3.93 – Utility of Feedback 3.88 0.67 2.30 4.80 -0.54 0.19 3.79–3.97 – Feedback Accountability 3.79 0.62 2.10 4.70 -0.61 0.40 3.71–3.87 – Feedback Self-Efficacy 3.88 0.65 2.30 4.80 -0.49 0.23 3.79–3.97 Assessment Anxiety (Total) 2.91 0.72 1.50 4.70 0.29 -0.44 2.82–3.00 – Worry 2.97 0.74 1.60 4.70 0.22 -0.36 2.87–3.07 – Emotionality 2.85 0.70 1.50 4.60 0.34 -0.47 2.76–2.94 Academic Motivation (Total) 3.96 0.58 2.30 4.90 -0.67 0.68 3.88–4.03 – Intrinsic Motivation 4.01 0.60 2.50 4.90 -0.69 0.61 3.93–4.09 – Extrinsic Motivation 3.91 0.61 2.30 4.80 -0.63 0.56 3.83–3.99 Note. Mean scores reflect moderate to high levels across constructs. Skewness and kurtosis values are within normal limits (|1.0|), supporting the assumption of normality. The 95% confidence intervals provide precise estimates of population means for each variable. Breaking the constructs into their sub-components in Table 2 revealed additional insights. For PAF, Distributive Fairness and Interactional Fairness scored slightly higher (M = 3.74 each) than Procedural Fairness (M = 3.68). All subscales showed similarly low variability (SDs ~ 0.58–0.60) and acceptable normality indicators. This suggests a balanced perception of fairness dimensions. For FO, all three subscales Utility of Feedback, Feedback Accountability, and Feedback Self-Efficacy were rated relatively high (M = ~ 3.79 to 3.88). The high inter-subscale means suggest students value feedback and perceive themselves as capable of engaging with it effectively. Assessment Anxiety subcomponents (Worry and Emotionality) had nearly identical means (2.97 and 2.85), indicating moderate levels of test-related distress. Both showed low skewness and moderate variability, consistent with previous studies on student anxiety. Lastly, Academic Motivation sub-dimensions showed that Intrinsic Motivation (M = 4.01) slightly exceeded Extrinsic Motivation (M = 3.91), suggesting that internal drives were more salient than external rewards in this student population. Table 3 Pearson Correlation Matrix for Main Constructs and Sub-Variables Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 Procedural Fairness 1.00 Distributive Fairness .81** 1.00 Interactional Fairness .78** .80** 1.00 Feedback Utility .52** .49** .53** 1.00 Feedback Accountability .45** .47** .46** .67** 1.00 Feedback Self-Efficacy .48** .50** .49** .71** .69** 1.00 Worry − .33** − .36** − .34** − .28** − .26** − .25** 1.00 Emotionality − .31** − .35** − .32** − .24** − .23** − .21** .78** 1.00 Intrinsic Motivation .44** .47** .46** .56** .52** .53** − .39** − .36** 1.00 Extrinsic Motivation .41** .43** .44** .53** .50** .51** − .37** − .35** .76** 1.00 PAF Total .89** .90** .91** .50** .46** .48** − .35** − .34** .45** .42** 1.00 FO Total .51** .49** .52** .87** .84** .86** − .29** − .27** .58** .56** .48** 1.00 AA Total − .34** − .36** − .35** − .26** − .25** − .24** .89** .91** − .39** − .37** − .36** − .28** 1.00 AM Total .47** .49** .48** .58** .55** .56** − .42** − .40** .93** .91** .46** .60** − .41** Note. p < .01 (2-tailed) . All significant correlations indicate meaningful associations between variables. High positive intercorrelations among fairness and feedback subscales suggest convergent relationships, while negative correlations with anxiety indicate divergent trends. The bivariate correlations in Table 3 offered compelling evidence for the interplay among the constructs. All three dimensions of Perceived Assessment Fairness were highly interrelated (r = .78 to .81), which is consistent with the theoretical integration of fairness concepts. FO subcomponents (Feedback Utility, Accountability, and Self-Efficacy) correlated strongly with each other (r = .67 to .71), confirming their convergent structure. Similarly, the strong correlation between Worry and Emotionality (r = .78**) underlined the coherence of AA as a unified factor. Importantly, negative correlations emerged between AA subcomponents and both FO and PAF variables (r = -0.21 to -0.36), indicating that higher perceived fairness and stronger feedback engagement were associated with lower test anxiety. In terms of motivation, both Intrinsic and Extrinsic Motivation were strongly and positively correlated with FO (r = .53 to .56) and PAF (r = .44 to .47), while showing moderate negative correlations with AA (r = -0.35 to -0.39). The total Academic Motivation (AM) score was strongly associated with FO (r = .60**), PAF (r = .46**), and inversely with AA (r = -0.41**). These patterns suggest that fairness and feedback enhance motivation, whereas anxiety undermines it. Finally, the high correlations between the subscales and their corresponding total scores (e.g., PAF Total with sub-dimensions r = .89 to .91) validate the internal structure of the instruments. Table 4 Multiple Regression Predicting Academic Motivation from Key Constructs Predictor Variable Unstd. B SE B Std. β t-v p-value 95% CI (L–U) Cohen’s f² Tol. VIF Procedural Fairness 0.10 0.05 0.11 2.00 0.046** 0.002–0.20 0.01 0.73 1.37 Distributive Fairness 0.09 0.04 0.10 2.25 0.025** 0.01–0.17 0.01 0.78 1.28 Interactional Fairness 0.13 0.05 0.14 2.60 0.010** 0.03–0.23 0.02 0.70 1.43 Utility of Feedback 0.14 0.06 0.13 2.33 0.021** 0.02–0.26 0.02 0.76 1.31 Feedback Accountability 0.11 0.05 0.12 2.20 0.029** 0.01–0.21 0.01 0.72 1.39 Feedback Self-Efficacy 0.16 0.06 0.15 2.67 0.008** 0.04–0.28 0.03 0.71 1.41 Worry (Anxiety Subscale) -0.17 0.05 -0.16 -3.40 0.001** -0.27 – -0.07 0.03 0.77 1.30 Emotionality (Anxiety Sub) -0.14 0.05 -0.14 -2.80 0.006** -0.24 – -0.04 0.02 0.75 1.33 Note. p < .05. All predictors significantly contributed to the model. Tolerance (Tol.) and Variance Inflation Factor (VIF) values indicate no multicollinearity issues (VIF < 5). Effect sizes (Cohen’s f² ) indicate small to moderate effects per predictor. This regression analysis in Table 4 investigates the extent to which key constructs dimensions of perceived assessment fairness, feedback orientation, and assessment anxiety predict students’ academic motivation (AM). The model shows that all predictors significantly contribute to academic motivation, as reflected in their statistically significant p-values (all < 0.05). Specifically, interactional fairness (B = 0.13, β = 0.14, p = 0.010) emerges as the strongest fairness-related predictor, indicating that respectful and considerate treatment during assessment processes has a meaningful positive effect on motivation. Procedural fairness (B = 0.10, β = 0.11, p = 0.046) and distributive fairness (B = 0.09, β = 0.10, p = 0.025) also show positive but relatively smaller effects. In terms of feedback orientation, feedback self-efficacy (B = 0.16, β = 0.15, p = 0.008) is the most influential predictor, suggesting that students who feel capable of using feedback effectively are more motivated academically. Feedback utility (B = 0.14, β = 0.13, p = 0.021) and feedback accountability (B = 0.11, β = 0.12, p = 0.029) also contribute positively to motivation. Conversely, assessment anxiety components worry (B = -0.17, β = -0.16, p = 0.001) and emotionality (B = -0.14, β = -0.14, p = 0.006) negatively predict academic motivation. This indicates that higher levels of cognitive concern and emotional distress related to assessments significantly lower students’ academic motivation. All tolerance and VIF values fall within acceptable ranges (Tol > 0.70; VIF < 2), indicating no multicollinearity. Cohen’s f² effect sizes are generally small (0.01–0.03), suggesting that while the effects are statistically significant, they are modest in magnitude individually. Table 5 Mediation Analysis Model ( Perceived Assessment Fairness → Assessment Anxiety → Academic Motivation) Path Coefficient (B) SE t-value p-value 95% CI (Lower–Upper) PAF → Assessment Anxiety (a-path) -0.39 0.06 -6.50 0.000 -0.51 – -0.27 Assessment Anxiety → AM (b-path) -0.42 0.07 -6.00 0.000 -0.56 – -0.28 PAF → AM (direct effect, c’) 0.21 0.06 3.50 0.001 0.09–0.33 PAF → AM (total effect, c) 0.37 0.05 7.40 0.000 0.27–0.47 Indirect effect (a × b) 0.16 0.04 - 0.000 0.09–0.24 (bootstrapped CI) Note. p < .001. Mediation was significant as shown by a significant indirect effect. The total effect (c) of Perceived Assessment Fairness on Academic Motivation was partially mediated by Assessment Anxiety, as both direct (c’) and indirect (a × b) paths were significant with bootstrapped confidence intervals excluding zero. This mediation model in Table 5 tests whether the relationship between perceived assessment fairness (PAF) and academic motivation is explained through its impact on assessment anxiety. The results show that: The a-path from PAF to anxiety is significant and negative (B = -0.39, p < 0.001), indicating that students who perceive assessments as fair report less anxiety. The b-path from anxiety to academic motivation is also significantly negative (B = -0.42, p < 0.001), showing that anxiety substantially reduces motivation. The direct effect of PAF on motivation (c’ path) remains significant (B = 0.21, p = 0.001), but is smaller than the total effect (c = 0.37, p < 0.001), confirming partial mediation. The indirect effect via anxiety is B = 0.16 (95% CI = 0.09–0.24), statistically significant based on bootstrapped confidence intervals. This means that part of the reason fair assessments improve motivation is because they alleviate assessment-related anxiety. The mediation pathway is both statistically robust and practically meaningful. Table 6 Moderation Analysis Model ( Feedback Orientation moderates the effect of Assessment Anxiety on Academic Motivation ) Path/Interaction B β (Std.) SE t-value p-value 95% CI ΔR² f² VIF Assessment Anxiety -0.31 -0.29 0.07 -4.43 0.000** -0.45 – -0.17 0.185 0.23 1.42 Feedback Orientation 0.29 0.27 0.06 4.83 0.000** 0.17–0.41 0.107 0.12 1.39 Assessment Anxiety × Feedback Orientation 0.12 0.14 0.05 2.40 0.017** 0.02–0.22 0.018 0.02 1.21 Note. p < .05. The interaction term (Assessment Anxiety × Feedback Orientation) was statistically significant, indicating that Feedback Orientation moderates the negative effect of Assessment Anxiety on Academic Motivation. ΔR² indicates the proportion of variance explained by the interaction beyond the main effects. This moderation model in Table 6 assesses whether feedback orientation ( FO ) moderates the negative effect of assessment anxiety on academic motivation. The main effect of assessment anxiety is significantly negative (B = -0.31, β = -0.29, p < 0.001), affirming earlier findings that anxiety reduces motivation. However, feedback orientation has a positive main effect (B = 0.29, β = 0.27, p < 0.001), suggesting that students with stronger feedback orientation are generally more motivated. Critically, the interaction term (Assessment Anxiety × Feedback Orientation) is statistically significant (B = 0.12, β = 0.14, p = 0.017), indicating a moderating effec t . This means that feedback orientation buffers the negative impact of anxiety on academic motivation in other words, students who are more feedback-oriented are less affected by anxiety in terms of motivation. The change in R² due to the interaction is small (ΔR² = 0.018), and Cohen’s f² for the interaction is also small (f² = 0.02), yet the effect is statistically meaningful. VIF values remain low, indicating no collinearity concerns. Table 7 Simple Slope and Conditional Effects Analysis of Predictors on Academic Motivation (AM) (Moderated by Feedback Orientation) Predictor Variable Feedback Orientation Level Effect on AM (B) Std. β SE t p-value 95% CI (Lower–Upper) AA Low (-1 SD) -0.45 -0.42 0.07 -6.43 0.000 -0.60 – -0.30 Mean -0.31 -0.29 0.07 -4.43 0.000 -0.45 – -0.17 High (+ 1 SD) -0.17 -0.16 0.07 -2.36 0.019 -0.31 – -0.03 PAF Low (-1 SD) 0.18 0.16 0.06 2.96 0.003 0.06–0.30 Mean 0.28 0.26 0.07 4.21 0.000 0.15–0.41 High (+ 1 SD) 0.37 0.34 0.07 5.43 0.000 0.24–0.50 FO Low (-1 SD) 0.22 0.20 0.06 3.55 0.001 0.10–0.34 Mean 0.35 0.32 0.07 5.03 0.000 0.21–0.49 High (+ 1 SD) 0.47 0.43 0.07 6.71 0.000 0.33–0.61 Note. Analysis confirms that the relationship between Assessment Anxiety and Academic Motivation is conditional on levels of Feedback Orientation. Higher Feedback Orientation attenuates the negative effect of Anxiety on Motivation. Table 7 presents the results of a conditional effects (simple slope) analysis to determine how the relationships between key predictors Assessment Anxiety (AA), Perceived Assessment Fairness (PAF), and Feedback Orientation (FO) and Academic Motivation (AM) vary at different levels of feedback orientation. Specifically, the analysis assessed the strength and direction of these relationships when FO was low (− 1 SD), average (mean), and high (+ 1 SD). For Assessment Anxiety (AA), the negative association with Academic Motivation was statistically significant at all levels of FO. When FO was low, the effect of AA on AM was most pronounced (B = -0.45, β = -0.42, p < .001), indicating that students who were less open to feedback and experienced high levels of anxiety demonstrated the lowest levels of academic motivation. As FO increased to the mean level, the strength of this negative relationship weakened but remained significant (B = -0.31, β = -0.29, p < .001). At high levels of FO, the negative effect of AA on AM was further attenuated (B = -0.17, β = -0.16, p = .019). These results suggest that FO functions as a moderating or buffering variable, lessening the detrimental impact of assessment-related anxiety on motivation. In practical terms, students who are more open to and accepting of feedback appear more resilient in the face of anxiety, maintaining higher motivation levels compared to their counterparts with low FO. Similarly, Perceived Assessment Fairness (PAF) showed a consistently positive and statistically significant effect on AM across all levels of FO. At low FO, the effect of PAF on AM was modest (B = 0.18, β = 0.16, p = .003), indicating that even students less inclined to embrace feedback still derive motivational benefit from perceived fairness in assessment. However, this effect grew stronger at mean (B = 0.28, β = 0.26, p < .001) and high levels of FO (B = 0.37, β = 0.34, p < .001). This pattern reinforces the idea that the positive impact of perceived fairness on student motivation is amplified among students with greater feedback receptiveness. Students who value feedback and believe assessments are fair tend to be more academically motivated, suggesting a synergistic effect between fairness perceptions and feedback orientation. Furthermore, FO itself significantly and positively predicted academic motivation at all levels. At low FO, the effect size was B = 0.22 (β = 0.20, p = .001); at the mean level, the effect was B = 0.35 (β = 0.32, p < .001); and at high FO, it rose to B = 0.47 (β = 0.43, p < .001). These results underscore the critical role of feedback orientation as a personal disposition that directly enhances motivation. Students who are more open to feedback are not only less vulnerable to the demotivating effects of anxiety but also more likely to perceive assessments positively and derive motivational gains. Overall, Table 7 highlights the interactive and conditional nature of student motivation, emphasizing the importance of psychological and contextual factors such as anxiety, fairness perceptions, and feedback receptivity. These findings have important implications for educational practice, suggesting that interventions aimed at enhancing FO such as building a feedback-positive classroom culture may help bolster student motivation, especially for those who struggle with anxiety. Table 8 Comprehensive Model Summary for Predicting Academic Motivation Model Predictors / Interaction Term B β SE t p-value 95% CI R² ΔR² Adj. R² F Chg AIC BIC VIF Tol. f² Effect 1 (AA) -0.31 -0.29 0.07 -4.43 0.000** -0.45 – -0.17 0.213 – 0.210 – 485.10 498.22 1.42 0.70 0.27 (M) 2 + (PAF) 0.28 0.26 0.07 4.21 0.000** 0.15–0.41 1.37 0.73 0.18 (S–M) + (FO) 0.35 0.32 0.07 5.03 0.000** 0.21–0.49 0.376 0.163 0.368 28.21 459.75 479.18 1.44 0.69 0.30 (M) 3 + AA × (Interaction Term) 0.12 – 0.05 2.40 0.017** 0.02–0.22 0.392 0.016 0.381 5.76 456.91 481.64 1.11 0.90 0.03 (S) Notes : • f² Effect Size Thresholds : Small = .02, Medium = .15, Large = .35 • Adjusted R² accounts for model complexity • AIC/BIC used for comparing model parsimony All predictors were mean-centered before creating interaction terms Table 8 presents a series of hierarchical regression models that explore the cumulative and interactive effects of Assessment Anxiety (AA), Perceived Assessment Fairness (PAF), and Feedback Orientation (FO) on Academic Motivation (AM). This model-building approach allows for an in-depth understanding of how individual predictors and their interactions contribute to explaining the variance in AM. Model 1 includes AA as the sole predictor of academic motivation. The results indicate that AA had a significant and negative impact on AM (B = -0.31, β = -0.29, p < .001), accounting for 21.3% of the variance in AM (R² = 0.213). The corresponding effect size (f² = 0.27) falls within the medium range, suggesting that assessment anxiety alone is a moderate but meaningful predictor of decreased motivation. This confirms prior research indicating that high anxiety levels undermine students’ confidence and enthusiasm for academic tasks. In Model 2, PAF and FO were added to the regression equation. The inclusion of these variables significantly improved the model’s explanatory power, raising the R² to 0.376, with an R² change (ΔR²) of 0.163. Both PAF (B = 0.28, β = 0.26, p < .001) and FO (B = 0.35, β = 0.32, p < .001) emerged as strong positive predictors of AM, demonstrating that students who perceive assessments as fair and are receptive to feedback tend to be more motivated. The adjusted R² for this model was 0.368, indicating robustness even after accounting for model complexity. The model’s improved parsimony is also supported by lower AIC (459.75) and BIC (479.18) values. The effect size in this model was f² = 0.30, which also qualifies as medium, affirming the substantive contribution of these additional predictors. Model 3 introduced the interaction term between AA and FO (AA × FO) to assess whether FO moderates the relationship between anxiety and motivation. The interaction term was statistically significant (B = 0.12, p = .017), indicating that the impact of anxiety on motivation indeed varies depending on the level of FO. The inclusion of this interaction increased the model’s R² slightly to 0.392, with a ΔR² of 0.016 and an adjusted R² of 0.381. Although the effect size of the interaction was small (f² = 0.03), its significance is practically relevant it provides empirical evidence that FO serves a protective function in the context of assessment anxiety. The model also showed continued improvement in model fit based on decreasing AIC (456.91) and BIC (481.64). Overall, the final comprehensive model (Model 3) offers the most complete understanding of the predictors of academic motivation. It not only identifies direct negative and positive effects of AA, PAF, and FO, respectively, but also reveals that feedback orientation plays a critical moderating role, mitigating the harmful influence of anxiety on motivation. This suggests that interventions aimed at increasing students’ feedback orientation could serve as a strategic lever to improve academic engagement and resilience, particularly for students prone to anxiety in evaluative settings. Discussion of Results The purpose of this study was to investigate the relationships among perceived assessment fairness (PAF), feedback orientation (FO), assessment anxiety (AA), and academic motivation (AM) among university students. The results reveal significant direct, indirect, and interaction effects across these constructs, with implications for both theory and practice in educational psychology and assessment. The internal consistency reliability of all scales used was acceptable to excellent, with Cronbach’s alpha coefficients ranging from 0.76 (Assessment Anxiety) to 0.89 (Academic Motivation). This confirms the psychometric soundness of the instruments, consistent with standards set by [41; 38], who recommend an alpha of 0.70 or above for established scales. The relatively higher reliability for Academic Motivation and Feedback Orientation scales aligns with previous studies [e.g. 23; 48; 30; 10; 12], affirming their robustness across contexts. Descriptive data suggest that students generally perceived assessment practices as fair and felt positively oriented toward feedback. Mean scores for all fairness and FO subscales hovered above the midpoint (M > 3.5), indicating high engagement with these constructs. Conversely, the lower mean score for Assessment Anxiety (M = 2.91) is indicative of moderate anxiety levels, which could be interpreted in the context of supportive learning environments or adaptive coping mechanisms as posited by [64). The correlation matrix revealed several notable patterns. Perceived assessment fairness dimensions procedural, distributive, and interactional were highly intercorrelated (r = .78 to .81), corroborating prior findings that fairness is a multidimensional but interconnected construct [55; 56]. This high intercorrelation suggests that students do not compartmentalize fairness dimensions in isolation but rather evaluate assessment fairness holistically. This mirrors findings by [ 16 ], who found that in educational settings, students’ perceptions of fairness in grading and instructor behavior often blend procedural and interactional elements. All three fairness dimensions were also significantly positively associated with both feedback orientation and academic motivation, while being negatively correlated with assessment anxiety. These findings reinforce [ 31 ] assertion that procedural justice in educational contexts enhances learners’ psychological safety, leading to more engagement and less stress. A meta-analysis by [18; 25] similarly found that perceived fairness across various justice domains was positively related to motivation and negatively associated with anxiety and counterproductive behavior. Furthermore, the positive relationship between fairness perceptions and feedback orientation aligns with the work of [33; 29], who found that employees (and by extension students) who perceive performance evaluations as fair are more open to receiving and acting on feedback. This is echoed by [ 62 ], who demonstrated in a university sample that perceptions of fairness during feedback interactions predicted both feedback acceptance and student satisfaction with learning outcomes. Feedback orientation subscales including utility, accountability, and self-efficacy were positively related to academic motivation and negatively related to anxiety, supporting [10; 11] feedback-seeking model, which argues that individuals who seek feedback are more confident in their ability to improve, thus reducing anxiety about performance outcomes. More recent work by [ 5 ] confirms that individuals with a high feedback orientation demonstrate stronger goal-setting behavior and adaptive responses to academic challenges. The strong correlation between intrinsic and extrinsic motivation (r = .76) also warrants attention. Although these are theoretically distinct constructs, [22; 23] argue in their Self-Determination Theory (SDT) that they often coexist within learners, especially in structured environments like universities, where both autonomous and controlled motivations are at play. [ 48 ] similarly report that extrinsically motivated students can internalize academic goals over time, thus aligning external pressures with intrinsic values a process referred to as integrated regulation. Moving beyond correlations, multiple regression analysis demonstrated that all three fairness dimensions significantly predicted academic motivation, with interactional fairness (β = .14, p = .010) and feedback self-efficacy (β = .15, p = .008) emerging as the strongest contributors. These results align with the findings of [ 39 ], who emphasized that students’ sense of being respected and heard core components of interactional fairness are essential for promoting intrinsic motivation. In a study by [ 53 ], students’ perceptions of teacher autonomy support and respectful treatment were positively associated with higher academic motivation and lower burnout. Additionally, [ 37 ] found that perceived fairness in classroom assessment significantly influenced students’ goal orientations and engagement, further strengthening the claim that fairness is not only an ethical necessity but a motivational catalyst. Similarly, [48; 10] observed that students who believed their grades reflected fair evaluations were more likely to express satisfaction and enthusiasm about course content and instructor feedback. Feedback orientation variables particularly utility and self-efficacy also predicted AM significantly, aligning with findings from [ 37 ], who noted that students who perceive feedback as useful and feel capable of acting on it demonstrate higher motivation and academic engagement. Anxiety subscales (worry and emotionality) negatively predicted academic motivation, supporting the well-established inverse relationship between anxiety and motivation [ 51 , 52 ]. The stronger impact of worry (β = -0.16, p = .001) suggests that cognitive components of anxiety may be more detrimental to motivation than physiological arousal, consistent with Cassady & Johnson (2022). Assessment anxiety was found to partially mediate the relationship between perceived assessment fairness and academic motivation. Specifically, PAF reduced anxiety (a-path: B = -0.39, p < .001), and lower anxiety, in turn, enhanced AM (b-path: B = -0.42, p < .001), with a significant indirect effect (ab = 0.16, CI [0.09, 0.24]). This mediating role of anxiety is supported by [10; 12] control-value theory, which suggests that students’ appraisal of fairness influences emotional experiences, which subsequently affect motivation. When assessment procedures are viewed as equitable and transparent, students are less likely to experience debilitating stress, thereby fostering better motivation. Feedback orientation significantly moderated the relationship between assessment anxiety and academic motivation. Specifically, high FO attenuated the negative impact of anxiety on motivation (interaction term: B = 0.12, p = .017). This implies that students with a positive feedback orientation are better able to regulate the adverse effects of anxiety on their motivation levels. This finding aligns with [ 48 ] model of self-regulation, which posits that feedback is a crucial mechanism through which individuals evaluate progress and adjust behavior. High FO learners are likely to reinterpret anxiety-inducing feedback as constructive, leading to adaptive coping and sustained motivation [ 2 ]. The conditional effects analysis further clarified the interaction pattern, showing that the negative effect of anxiety on motivation was strongest when FO was low. When FO was high, the detrimental effect of anxiety on motivation was significantly reduced. This moderation effect illustrates the buffering role of metacognitive attitudes toward feedback, consistent with the work of [ 33 ], who found that the perceived utility of feedback determines its psychological impact. Conclusion This study examined how students in health professions education in Ghana perceive assessment fairness, orient themselves toward feedback, and how these factors influence their academic motivation and levels of assessment anxiety. The findings revealed that procedural, distributive, and interactional fairness are strongly interrelated and significantly associated with both academic motivation and feedback orientation. Students who perceived assessments as fair reported higher motivation and lower anxiety levels. Among the fairness dimensions, interactional fairness had the strongest influence on motivation, suggesting that respectful and supportive treatment during assessments plays a critical role in shaping students’ attitudes and engagement. Feedback orientation also emerged as a key factor. Students who felt confident in using feedback and valued it reported higher motivation and reduced anxiety. The results further showed that both intrinsic and extrinsic motivation are strongly linked, reflecting the complexity of students’ motivational drives in high-stakes academic settings. Overall, the study concludes that students’ perceptions of fairness and feedback experiences significantly impact their psychological responses to assessment. Creating a fair, transparent, and feedback-rich assessment environment can promote academic motivation and help reduce anxiety among students in health-related programs. Recommendations Based on the findings of this study, it is recommended that educational institutions in Ghana’s health professions sector prioritize the development and implementation of assessment practices that are perceived as fair by students. Lecturers and examination committees should ensure that procedures for both formative and summative assessments are transparent, consistent, and aligned with clearly communicated criteria. Special attention should be paid to interactional fairness how students are treated during the assessment process by fostering respectful, supportive, and inclusive communication. When students feel heard and respected, they are more likely to be motivated and less likely to experience debilitating anxiety. Secondly, there is a need to strengthen students’ feedback orientation through systematic integration of feedback literacy into the curriculum. Lecturers should be trained not only to provide timely and constructive feedback but also to actively guide students on how to interpret and apply it for academic improvement. Institutions may consider introducing workshops or mentorship programs that promote feedback-seeking behaviors and boost students’ confidence in using feedback effectively. This is essential for nurturing self-directed learning and reducing negative emotional responses to assessment. Furthermore, academic support services should be enhanced to address assessment-related anxiety. This may include psychological counseling, stress management workshops, and academic coaching tailored to the needs of health professions students. Since the study found that fair assessment and positive feedback experiences reduce anxiety, these services should work collaboratively with faculty to create a learning climate where assessment is seen as a developmental tool rather than a source of fear. Finally, institutional policies should reflect a commitment to continuous improvement in assessment fairness and feedback processes. This can be achieved through regular student evaluations, faculty development programs, and feedback loops that involve both staff and learners in refining assessment strategies. By embedding fairness and constructive feedback at the heart of assessment design, institutions can enhance both the academic performance and emotional well-being of future health professionals in Ghana. Limitations of the Study Although this study offers valuable insights into the psychological dynamics of assessment practices among health professions students in Ghana, some limitations should be recognized. First, the cross-sectional design limits the ability to draw causal inferences about the relationships among perceived fairness, feedback orientation, assessment anxiety, and academic motivation. Longitudinal research would be better suited to examine how these variables evolve over time and interact across different stages of students’ academic journeys. Additionally, self-reported data may be subject to social desirability bias, with participants possibly overstating or understating their true experiences due to perceived expectations or personal discomfort. Secondly, while the study employed stratified random sampling to enhance representativeness, the sample was limited to six public nursing and midwifery training institutions, which may not fully capture the experiences of students in private institutions or those pursuing other health-related programs such as medicine, pharmacy, or public health. Regional and institutional differences in assessment culture, faculty practices, and resource availability could influence students’ perceptions and psychological responses in ways not fully accounted for in this study. Future research could address these limitations by incorporating a broader range of institutions, adopting mixed methods approaches, and exploring the roles of faculty and institutional policies in shaping assessment-related outcomes. Abbreviations HPE – Health Professions Education, SPSS – Statistical Package for the Social Sciences, SD – Standard Deviation, M – Mean, α – Cronbach’s Alpha (internal consistency coefficient), r – Pearson’s Correlation Coefficient, β – Standardized Beta Coefficient (from regression), R² – Coefficient of Determination, df – Degrees of Freedom, p – Probability Value (Statistical Significance), PAF – Perceived Assessment Fairness, FO – Feedback Orientation, AA – Assessment Anxiety, AM – Academic Motivation, VIF – Variance Inflation Factor Declarations Ethics Approval and Consent to Participate This study was conducted in full compliance with the ethical guidelines of the Declaration of Helsinki and relevant institutional and national research ethics regulations. Ethical approval was obtained from the Ethics Review Committee of the University of Education, Winneba (Protocol Ref: UEW/IRB/2024/08), as well as from the ethical review boards of all six participating nursing and midwifery training institutions across Ghana’s southern, middle, and northern ecological zones. Prior to data collection, participants were provided with detailed information about the purpose of the study, the voluntary nature of their participation, data confidentiality, and the right to withdraw without penalty. Written informed consent was obtained from all participants. Data were anonymized, securely stored, and accessible only to the principal investigators to ensure participant privacy and data protection. Consent for Publication Not applicable. This study did not involve the publication of personal images, identifiable clinical information, or any data that could compromise participant anonymity. Availability of Data and Materials The datasets generated and analyzed during the current study are available from the corresponding author, Simon Ntumi, upon reasonable request. Due to ethical and institutional constraints concerning participant confidentiality, raw data will not be made publicly available. All data access requests will be assessed in accordance with institutional ethical policies to ensure data security and anonymity. Competing Interests The authors declare that they have no competing interests. The design, execution, and reporting of this study were conducted independently and were not influenced by any external funding agency, institution, or commercial interest. Funding This research was fully self-funded by the authors. No external financial support was received for the conceptualization, data collection, analysis, or dissemination of the findings. Acknowledgments The authors express sincere appreciation to the administrators, faculty, and students of the participating nursing and midwifery training institutions for their cooperation and trust. Special thanks to the institutional ethics boards and research coordinators who facilitated approvals and logistics across the ecological zones. We are also grateful to the respondents and data cleaning personnel whose diligence contributed to the quality of this research. Clinical Trial Number Not applicable. Author Contributions Simon Ntumi: Led the conceptualization and design of the study, developed the research methodology, supervised the overall project, performed advanced statistical data analysis, interpreted findings, drafted the initial manuscript, coordinated revisions, and served as the corresponding author responsible for communication with the journal and stakeholders. Paul Kobina EFFRIM: Provided proficient consultation on the study, supported data analysis and interpretation, contributed to the discussion of results, and assisted in ensuring the robustness and validity of the study’s findings. Clarke Ebow Yalley: Played a key role in conducting the literature review, contributed to the design of data collection instruments, supervised data collection procedures, assisted with data interpretation, and provided critical revisions and edits to improve the intellectual content of the manuscript. Abraham Yeboah: Provided expert consultation on statistical methods and multivariate analysis techniques, supported data analysis and interpretation, contributed to the discussion of results, and assisted in ensuring the robustness and validity of the study’s quantitative findings. Divine Agbovor: Coordinated participant recruitment and data collection, managed data coding and organization, contributed to data analysis, and supported the drafting of sections related to data collection and methodology. Emmanuel Ohene Amezah: Reviewed and strengthened the theoretical framework underpinning the study, contributed to contextualizing findings within existing research, and conducted thorough proofreading and editorial review to ensure clarity and coherence of the manuscript. Frank Henry Bonsi: Assisted with managing and cleaning the data set, supported preliminary statistical analyses, contributed to data visualization efforts such as values and tables, and reviewed the results section to ensure accuracy. Abdul-Razak Ishaaq: Contributed to the synthesis of relevant literature, assisted in refining the manuscript’s structure and flow, ensured adherence to formatting guidelines, and collaborated in the final manuscript preparation. References Agyeman, D. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6958871","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":488880960,"identity":"da8c2994-ac3a-4fd2-b0f4-8280b20b2014","order_by":0,"name":"Simon Ntumi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIiWNgGAWjYNACAxsIzQNiE1bODFKWRrIWhsMkaJGf3X9M6kbB+cR+iQTGB2/bGOy2E9JicOcwm3SOwe3EmTMSmA3ntjEk72wgpEUiGaJlw+0ENmleoBaDA4QcNgOs5Vzi/tsJ7L+J0sJwA6zlQOIG6QQ2ZqAWO4JaDG4kG1vnGCQbz7j/sFlyzjmJBCIclvjwds4fO9n+nsMHP7wps7En7DAEYGwAEhKJDcTrgAJ7knWMglEwCkbBsAcAdVc9xofsEDAAAAAASUVORK5CYII=","orcid":"","institution":"University of Education, Winneba (UEW)","correspondingAuthor":true,"prefix":"","firstName":"Simon","middleName":"","lastName":"Ntumi","suffix":""},{"id":488880961,"identity":"ad743504-3e69-47c8-9108-6bcf24579884","order_by":1,"name":"Paul Kobina EFFRIM","email":"","orcid":"","institution":"University of Education, Winneba (UEW)","correspondingAuthor":false,"prefix":"","firstName":"Paul","middleName":"Kobina","lastName":"EFFRIM","suffix":""},{"id":488880962,"identity":"bd260c63-564d-4a4b-a7c6-8a0e2c7a57e9","order_by":2,"name":"Clarke Ebow Yalley","email":"","orcid":"","institution":"University of Education, Winneba (UEW)","correspondingAuthor":false,"prefix":"","firstName":"Clarke","middleName":"Ebow","lastName":"Yalley","suffix":""},{"id":488880963,"identity":"b8f3be56-d442-4214-a4a9-2a5bb149a03f","order_by":3,"name":"Abraham Yeboah","email":"","orcid":"","institution":"Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development (AAMUSTED)","correspondingAuthor":false,"prefix":"","firstName":"Abraham","middleName":"","lastName":"Yeboah","suffix":""},{"id":488880964,"identity":"434f525b-ef46-4210-8623-797b6d987b0a","order_by":4,"name":"Divine Agbovor","email":"","orcid":"","institution":"University of Education, Winneba (UEW)","correspondingAuthor":false,"prefix":"","firstName":"Divine","middleName":"","lastName":"Agbovor","suffix":""},{"id":488880965,"identity":"fa0fa612-f3de-4a9b-bcd5-9304576822cc","order_by":5,"name":"Emmanuel Ohene Amezah","email":"","orcid":"","institution":"University of Education, Winneba (UEW)","correspondingAuthor":false,"prefix":"","firstName":"Emmanuel","middleName":"Ohene","lastName":"Amezah","suffix":""},{"id":488880966,"identity":"98bbcb09-1822-41f3-a409-8d8a369fe9fb","order_by":6,"name":"Frank Henry Bonsi","email":"","orcid":"","institution":"University of Education, Winneba (UEW)","correspondingAuthor":false,"prefix":"","firstName":"Frank","middleName":"Henry","lastName":"Bonsi","suffix":""},{"id":488880967,"identity":"51c9cd1a-a3ec-4964-8cde-01f5cec9b6df","order_by":7,"name":"Abdul-Razak Ishaaq","email":"","orcid":"","institution":"University of Education, Winneba (UEW)","correspondingAuthor":false,"prefix":"","firstName":"Abdul-Razak","middleName":"","lastName":"Ishaaq","suffix":""}],"badges":[],"createdAt":"2025-06-23 17:08:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6958871/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6958871/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87518288,"identity":"8f43c340-6a7c-4c5f-b852-2425f06d0d2c","added_by":"auto","created_at":"2025-07-24 17:01:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1523486,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6958871/v1/39048a64-ea4a-4f47-9349-d23cc78b7bc4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Grading Minds and Shaping Futures: A Multivariate Analysis on the Perceptions of Fairness Anxiety, Feedback Orientation and Motivation in Ghana’s Health Professions Education","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAssessment plays a pivotal role in shaping student learning, especially in health professions education, where both formative and summative evaluations inform pedagogical practices, competency development, and progression decisions [11; 10; 24; 35; 1]. Assessment not only serves as a mechanism for measuring the acquisition of knowledge and skills but also guides curriculum refinement, provides accountability, and facilitates professional accreditation [12; 34]. In clinical and pre-clinical training, high-stakes decisions such as licensure, placement, and graduation are often based on the results of summative assessments, while formative assessments offer learners opportunities to receive structured feedback, develop clinical reasoning, and reflect on their learning trajectories [1; 10; 2; 7; 26]. In the Ghanaian context, health education programs ranging from medicine and nursing to allied health sciences rely heavily on rigorous assessments to determine student competence and readiness for professional practice [43; 21; 26]. The structure of these programs often reflects global standards but is delivered within local constraints, including limited clinical exposure, faculty shortages, and variability in assessment literacy among instructors [23; 1; 5; 4]. Consequently, while assessments are intended to drive learning and ensure competence, their design and implementation can significantly affect students’ psychological experiences, particularly in relation to perceptions of fairness, receptivity to feedback, test anxiety, and motivation.\u003c/p\u003e\u003cp\u003eAssessment fairness, defined as the perceived justice and transparency in evaluation methods, significantly influences students’ trust in the education system and their academic engagement [9; 32; 3]. When students believe that assessment criteria are objective, consistent, and aligned with course content, they are more likely to adopt mastery-oriented approaches to learning and view assessments as constructive challenges rather than threats [55; 56; 26]. Conversely, in settings where resources are limited and educational equity is still evolving, such as Ghana, perceptions of unfair or biased assessment practices such as inconsistent grading, ambiguous test items, or lack of clear rubrics can deepen academic stress, reduce performance, and erode students’ confidence in the education system [13; 12; 53; 31]. Similarly, feedback orientation, which refers to students’ attitudes and openness to receiving and using feedback, has been identified as a crucial determinant of academic improvement and professional identity formation [7; 9; 8, 3; 26]. Health professions education places considerable emphasis on feedback both in classroom and clinical settings as a means of helping learners calibrate their self-assessments, identify performance gaps, and plan for improvement. However, the effectiveness of feedback is often undermined by factors such as poor timing, lack of specificity, unidirectional delivery, and students’ emotional responses [8; 18]. In Ghana, anecdotal evidence and emerging research suggest that students in health programs may receive limited actionable feedback, often constrained by overcrowded classrooms, high faculty workload, and a culture of summative assessment dominance [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMore broadly, the interplay between students’ perceptions of fairness and feedback experiences has critical implications for their psychological wellbeing and academic functioning. Assessment that is perceived as arbitrary or punitive can heighten assessment anxiety, a form of performance-related stress that impairs working memory, lowers self-efficacy, and affects decision-making under pressure [14; 16; 17; 45]. In high-stakes environments such as medical and nursing schools where the consequences of failure are steep assessment anxiety may become chronic, leading to burnout or disengagement [26; 2; 42]. Furthermore, such anxiety often interacts with motivational constructs, such as intrinsic and extrinsic academic motivation, shaping how students approach learning tasks, persist in the face of difficulty, and develop self-regulation [22; 23]. Assessment anxiety, a prevalent issue among students in high-stakes academic environments, has been consistently associated with impaired cognitive functioning, reduced academic performance, and increased psychological distress especially in demanding and competitive disciplines such as the health sciences [10; 12; 11; 30; 40]. This form of anxiety often manifests as physiological symptoms (e.g., rapid heartbeat, sweating), cognitive interference (e.g., intrusive thoughts, worry), and behavioral avoidance, all of which compromise students’ ability to retrieve knowledge and apply critical thinking under pressure [10; 12; 11; 30; 40]. In clinical education settings, where students are evaluated through written exams, practical demonstrations, and clinical rotations, the pressure to perform competently in front of peers and evaluators can amplify performance-related stress. Anxiety levels are particularly heightened when students perceive assessments as unpredictable, overly punitive, or disconnected from clearly communicated instructional goals and learning outcomes [10; 12; 11; 30; 57]. The lack of alignment between teaching and assessment can create a perception of arbitrariness, further exacerbating students’ sense of vulnerability and loss of control. Concurrently, academic motivation, whether intrinsic (driven by curiosity and interest) or extrinsic (driven by grades, rewards, or external approval), plays a critical role in determining how students engage with learning and cope with assessment-related pressures [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Students with strong intrinsic motivation are more likely to approach learning with persistence, deep processing, and resilience, even in the face of challenging evaluations [49; 63; 28].\u003c/p\u003e\u003cp\u003eIn contrast, extrinsically motivated students may perform adequately in the short term but are often more susceptible to anxiety, avoidance behaviors, and reduced long-term retention, particularly when rewards are perceived as contingent on high-stakes performance [10; 12; 30; 40]. In academic contexts where summative assessments dominate such as Ghana’s health professions education sector the overemphasis on final grades and pass/fail outcomes may inadvertently shift students’ focus from mastery of content to performance goals, thereby undermining intrinsic motivation and fostering a transactional view of learning [21; 62; 27]. When evaluations are seen primarily as hurdles to be cleared, rather than as integral components of a developmental learning process, students may become disengaged or overly anxious, reducing both their academic effectiveness and psychological well-being. This complex interplay between assessment anxiety and academic motivation underscores the need for balanced assessment systems that integrate formative practices, offer timely and constructive feedback, and cultivate learning environments that support student autonomy and competence [13; 18; 3; 61; 58]. Such approaches are not only pedagogically sound but also essential for nurturing self-regulated learners capable of thriving in the emotionally and cognitively demanding field of health care. Despite the critical role that assessment plays in shaping student learning, especially within health professions education, there remains limited understanding of how psychological factors such as assessment anxiety, perceptions of fairness, feedback orientation, and academic motivation interact to influence student experiences and outcomes particularly in the context of sub-Saharan Africa. Globally, the literature has established that students’ perceptions of assessment fairness and feedback quality are central to engagement, trust, and performance. Moreover, a substantial body of research has demonstrated that high levels of assessment anxiety can hinder cognitive processing, impair academic performance, and even contribute to burnout and attrition in demanding academic programs [14; 10] While these psychological dynamics have been widely examined in Western and high-income countries, relatively few studies have focused on how they manifest in low-resource settings such as Ghana, where educational infrastructures, faculty capacity, and student support services may differ markedly.\u003c/p\u003e\u003cp\u003eIn Ghana’s health education sector, summative assessments often high-stakes in nature continue to dominate the evaluative landscape, sometimes to the neglect of formative, feedback-rich practices that foster self-regulation and deeper learning [43; 23; 19]. Although efforts are underway to shift toward more competency-based and learner-centered models, the extent to which students perceive these assessment practices as fair, transparent, and supportive remains underexplored. Anecdotal reports and limited local studies suggest that students often express dissatisfaction with unclear assessment criteria, insufficient feedback, and lack of consistency in grading practices [4; 8; 10]. These factors may contribute to elevated levels of test anxiety and diminished motivation, yet empirical investigations linking these variables in Ghanaian health professions education are sparse. This is a significant gap, given the emotionally and cognitively taxing nature of clinical education and the high expectations placed on students preparing for roles in critical sectors such as medicine, nursing, and allied health sciences. Furthermore, most existing studies in Ghana have treated these psychological constructs in isolation focusing solely on test anxiety or feedback mechanisms without examining their interconnected effects within comprehensive assessment systems. The multivariate interplay between perceived fairness, feedback orientation, assessment anxiety, and academic motivation has not been sufficiently theorized or empirically tested in Ghanaian higher education settings, particularly within health training institutions. As such, there is a pressing need for contextually grounded, theory-informed research that investigates how these variables converge to affect student performance, well-being, and professional identity formation. Addressing this gap is crucial for informing the design of more equitable, psychologically supportive, and pedagogically effective assessment practices in Ghana and comparable educational contexts.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTheoretical Framework: Self-Determination Theory (SDT)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSelf-Determination Theory (SDT), developed by [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], offers a comprehensive framework for understanding human motivation, psychological development, and well-being. At its core, SDT posits that individuals possess innate psychological needs for autonomy, competence, and relatedness. When these needs are supported within a given environment, individuals are more likely to experience self-motivation, engagement, and personal growth. In contrast, when these needs are thwarted, motivation tends to diminish, leading to disengagement and reduced well-being. In educational settings particularly in health professions education where students are often exposed to high-pressure and high-stakes assessment environments SDT provides a valuable lens through which to understand how learners respond to various assessment practices, such as formative and summative assessments. Autonomy, as one of the three central components of SDT, refers to the individual’s need to feel that their actions are self-endorsed and reflect personal choice rather than external pressure [22; 23]. In the context of assessment, autonomy is supported when students perceive that assessments are fair, transparent, and give them the opportunity to demonstrate learning in diverse and meaningful ways. When students are provided with choices in how they engage with assessments or receive feedback that respects their viewpoints and encourages self-reflection, they are more likely to feel autonomous and intrinsically motivated. On the other hand, perceptions of biased, rigid, or punitive assessments can diminish students’ sense of control, undermining their motivation and increasing resistance to learning.\u003c/p\u003e\u003cp\u003eThe second component, competence, refers to the need to feel effective and capable of achieving desired outcomes. Students in health professions education often operate in academically demanding environments that require mastering complex content and demonstrating clinical proficiency. When assessment practices especially formative assessments provide clear criteria, actionable feedback, and opportunities for improvement, they enhance students’ perceptions of competence [22; 23]. Constructive feedback that highlights strengths, suggests specific improvements, and acknowledges effort can reinforce students’ belief in their ability to succeed. Conversely, vague or overly critical feedback and high-stakes summative assessments that are perceived as unpredictable or unfair may lead to feelings of inadequacy and self-doubt, fostering assessment anxiety and reducing confidence. Relatedness, the third psychological need, involves the desire to feel connected to others and to experience mutual respect and care. In academic settings, relatedness is fostered when students feel that their instructors are approachable, supportive, and genuinely invested in their learning. Feedback plays a critical role in building this connection. When feedback is delivered in a personalized, empathetic, and constructive manner, students are more likely to feel supported and understood. This sense of relatedness not only enhances motivation but also buffers the negative emotional effects of academic stress, such as anxiety and burnout. Conversely, feedback that is impersonal, dismissive, or overly critical can alienate students and hinder engagement [22; 23].\u003c/p\u003e\u003cp\u003eIn this study, SDT is applied to understand the interplay between students’ perceptions of assessment fairness, feedback orientation, assessment anxiety, and academic motivation in the context of formative and summative assessment practices within health professions education in Ghana. Assessment fairness is theorized to influence all three psychological needs. When students perceive assessments as fair meaning they believe the procedures, grading, and expectations are consistent and just they are more likely to feel autonomous, competent, and respected. Similarly, feedback orientation, or the extent to which students seek out, value, and use feedback, is closely tied to autonomy and competence [22; 23; 47]. Students who receive feedback that supports learning, rather than simply judging performance, are more likely to remain motivated and take ownership of their academic development. Assessment anxiety is conceptualized within this framework as a psychological response that emerges when one or more of the basic needs is thwarted especially competence and autonomy. High levels of anxiety often reflect students’ fears of being judged unfairly or failing to meet expectations, which can be exacerbated by unclear or rigid assessment systems [22; 23; 46]. In contrast, environments that foster autonomy, build competence, and promote relatedness can help mitigate anxiety and promote resilience. Academic motivation, whether intrinsic (driven by curiosity and mastery) or extrinsic (driven by grades and approval), is thus seen as the outcome of the extent to which these psychological needs are fulfilled within the assessment context. By anchoring the study in SDT, the research highlights the importance of designing and implementing assessment systems in health professions education that do more than measure knowledge they must also support students’ psychological needs. Fair and transparent assessments, feedback that is timely and meaningful, and emotionally supportive interactions with educators all contribute to healthier motivational profiles among students. Such practices can reduce assessment anxiety, encourage academic persistence, and foster a more positive learning climate in demanding academic programmes such as nursing, midwifery, and medical laboratory sciences. In doing so, SDT not only guides the interpretation of empirical findings in this study but also provides actionable insights for educational policy and practice.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResearch Questions\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eWhat is the relationship between perceived assessment fairness and academic motivation among health professions students in Ghana?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTo what extent does feedback orientation predict assessment anxiety among health professions students in Ghana?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTo what extent do perceived assessment fairness, feedback orientation, and assessment anxiety jointly predict academic motivation among health professions students in Ghana?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eResearch Design\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe study adopted a cross-sectional survey design to investigate the multivariate relationships among four key psychological constructs: perceived assessment fairness, feedback orientation, assessment anxiety, and academic motivation among students enrolled in health professions education in Ghana. The cross-sectional approach was particularly suitable given the need to collect standardized, self-reported data from a large and diverse sample of students at a single point in time. This design allowed for the examination of both correlational and predictive patterns between variables, facilitating a data-driven understanding of how assessment experiences shape students’ psychological and motivational responses [21; 50]. The choice of a quantitative design was underpinned by the objective of statistically testing predefined hypotheses and identifying generalizable trends that could inform educational policy and assessment reform in the Ghanaian health education sector. Furthermore, this approach aligns with previous research in medical and nursing education, where survey methods have been extensively used to quantify psychological factors affecting student learning and performance [7; 9; 12; 38]. The design also supported the use of multivariate techniques such as multiple regression and structural equation modeling, which are particularly effective for analyzing complex interrelationships among variables.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePopulation and Sampling\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe target population for this study consisted of diploma and undergraduate students enrolled in accredited nursing and midwifery training institutions in Ghana. To capture a broad and representative sample, the study included students from six major nursing and midwifery training colleges across three ecological zones of the country:\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cem\u003eSouthern Zone\u003c/em\u003e: Korle-Bu Nurses and Midwifery Training College (Greater Accra Region) and Cape Coast Nursing and Midwifery Training College (Central Region)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cem\u003eMiddle Zone\u003c/em\u003e: Kumasi Nurses and Midwifery Training College (Ashanti Region) and Kintampo College of Health and Wellbeing (Bono East Region)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cem\u003eNorthern Zone\u003c/em\u003e: Tamale Nurses and Midwifery Training College and Bolgatanga Midwifery Training College (Upper East Region)\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThese institutions were purposively selected to ensure a diverse student demographic in terms of regional background, language, cultural identity, and academic orientation. This strategy also supported the study’s aim to examine psychological responses in varied institutional settings urban, peri-urban, and rural where disparities in resources and instructional quality may influence assessment experiences. A stratified random sampling technique was employed to draw participants across key strata, including program type (nursing vs. midwifery), year of study (first, second, and third year), and gender. This method enhanced the representativeness and precision of the sample while controlling for confounding demographic variables [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Based on [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] formula for sample size determination in finite populations, and assuming a 95% confidence level with a 5% margin of error, a minimum of 500 students was deemed necessary. An additional 15% was added to account for incomplete responses and dropout, resulting in a target sample size of approximately 575 participants. Institutional research boards and administrative authorities were contacted for permission, and assistance from faculty liaisons and student leaders facilitated access to class email lists and social media platforms for the dissemination of survey links. This large and geographically distributed sample allowed for stronger external validity and the ability to conduct subgroup analyses (e.g., comparing nursing vs. midwifery students, or first-year vs. third-year students), thus enriching the interpretive scope of the findings.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInstrumentation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe study employed a structured online questionnaire consisting of four validated psychometric scales, each corresponding to one of the study’s key constructs: Perceived Assessment Fairness, Feedback Orientation, Assessment Anxiety, and Academic Motivation. All items were presented in English the medium of instruction in Ghanaian tertiary institutions and formatted using a five-point Likert scale (1 = Strongly Disagree to 5 = Strongly Agree), to allow for nuanced gradations in student responses.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cem\u003ePerceived Assessment Fairness\u003c/em\u003e: This construct was measured using an adapted version of the Assessment Fairness Perceptions Scale (AFPS) developed by Green et al. (2007). The original items were reviewed and modified for cultural and contextual appropriateness within the Ghanaian health education system. The scale examined students’ perceptions of procedural fairness, grading transparency, and equity in assessment opportunities. Sample items included statements such as \u003cem\u003e“Assessment criteria are applied consistently to all students”\u003c/em\u003e and \u003cem\u003e“I understand how my grades are calculated.”\u003c/em\u003e\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cem\u003eFeedback Orientation\u003c/em\u003e: Students’ openness to and valuation of feedback were measured using the Feedback Orientation Scale (FOS) developed by [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The scale includes four subdimensions: utility of feedback, feedback self-efficacy, accountability, and social awareness. This instrument has been validated across educational settings and was found to be particularly relevant in professional training contexts where constructive feedback is integral to clinical development [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cem\u003eAssessment Anxiety\u003c/em\u003e: The short form of the Test Anxiety Inventory (TAI-SF) by [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] was used to measure cognitive and emotional responses to assessment situations. This inventory, widely employed in health education research, focuses on worry, emotionality, and interference with task performance. Prior studies have found the TAI-SF to be valid and reliable in populations including nursing and midwifery students [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cem\u003eAcademic Motivation\u003c/em\u003e: Academic motivation was assessed using the Academic Motivation Scale (AMS) developed by [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e], based on Self-Determination Theory (SDT). This scale captures various forms of motivation: intrinsic motivation (e.g., learning for personal growth), extrinsic motivation (e.g., studying for rewards or recognition), and amotivation. The AMS has been widely validated across disciplines, including in low- and middle-income countries, and was selected for its relevance to educational psychology in culturally diverse contexts [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eBefore full deployment, a pilot study was conducted with 30 students from a non-participating nursing college to assess comprehension, clarity, and cultural relevance of the survey items. Feedback from the pilot led to minor modifications in phrasing for local terminology and clarity. The internal consistency of each scale was evaluated using Cronbach’s alpha, with values ranging from 0.76 to 0.89, indicating acceptable to excellent reliability [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. All instruments were embedded into the Google Forms platform, which supported mobile accessibility and enabled automatic data export for statistical analysis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData Collection Procedure\u003c/b\u003e\u003c/p\u003e\u003cp\u003eData were collected through a self-administered online survey hosted on Google Forms, over a period of four weeks. This approach was chosen primarily for its accessibility, cost-effectiveness, and ethical appropriateness, particularly in the context of ongoing post-COVID-19 and other related health protocols, which discouraged prolonged face-to-face engagements in many academic institutions [20; 10]. The online mode also facilitated the efficient reach of a geographically dispersed sample, as students were enrolled in various institutions across different regions of Ghana. To ensure effective distribution of the survey, institutional gatekeepers, including academic coordinators and heads of departments, were contacted through formal email and phone communication. Upon receiving administrative approval, these gatekeepers disseminated the survey link via institutional mailing lists, official WhatsApp class platforms, and student portals, ensuring wide visibility and engagement across cohorts. The use of digital platforms such as WhatsApp was especially crucial in the Ghanaian context, where students rely heavily on mobile communication for academic and social interaction [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. At the beginning of the survey, participants were presented with a detailed informed consent form, explaining the purpose of the study, procedures involved, potential risks and benefits, confidentiality assurances, and voluntary nature of participation. Students were explicitly informed of their right to withdraw from the survey at any point without penalty or academic consequence. Participation required active consent via a checkbox before proceeding to the questionnaire. The survey was designed to take approximately 15–20 minutes to complete. To improve response rates, weekly reminder messages were sent through class representatives and faculty liaisons. Additionally, students were incentivized with an optional entry into a lucky draw for educational materials such as mobile data vouchers or textbook discounts, approved by ethical review committees and communicated transparently in the consent form.\u003c/p\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eData collected from the online survey were exported directly from Google Forms into IBM SPSS Statistics Version 27.0 for cleaning, coding, and statistical analysis. Prior to formal analysis, data were screened for missing values, outliers, and inconsistencies. Cases with substantial missing data (greater than 20% of items unanswered) were excluded from the analysis to maintain data integrity. Minor missing values were addressed using mean substitution for continuous variables, ensuring minimal distortion of the dataset. Descriptive statistics were computed to summarize the demographic characteristics of participants and central tendencies of the key variables, including means, standard deviations, ranges, and frequency distributions. Internal consistency for each psychometric scale was assessed using Cronbach’s alpha, with all constructs exceeding the recommended threshold of 0.70, indicating good reliability [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. To explore associations between variables, Pearson correlation coefficients were calculated. This bivariate analysis provided insight into the direction and strength of relationships among perceived assessment fairness, feedback orientation, assessment anxiety, and academic motivation. Preliminary tests for normality (via Shapiro-Wilk), linearity (via scatterplots), and multicollinearity (using Variance Inflation Factor - VIF) were conducted to meet the assumptions required for parametric testing. Subsequently, multiple linear regression analysis was conducted to assess the predictive power of the independent variables (perceived assessment fairness, feedback orientation, and assessment anxiety) on the dependent variable (academic motivation). This approach allowed for an understanding of the unique and combined contributions of each predictor, while controlling for potential overlap. Statistical significance was evaluated at p \u0026lt; .05, and standardized beta coefficients were used to compare the relative strength of the predictors. The findings were interpreted within the theoretical frameworks of Self-Determination Theory [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], which explains how intrinsic and extrinsic motivators influence student behavior. The analysis ultimately provided empirical evidence regarding the psychological factors that underpin motivation among health professions students in Ghana, offering insights for policy, curriculum development, and student support services in nursing and midwifery education.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEthical Considerations\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\u003cp\u003e for the study was obtained from the Research Ethics Committee of the University of Education, Winneba, with further institutional permission granted by the participating nursing and midwifery colleges, including Korle-Bu Nurses Training College, Cape Coast Nursing and Midwifery Training College, and Tamale Nurses and Midwifery Training College. All ethical procedures conformed to the guidelines of the Declaration of Helsinki [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e] and the Ghana Health Service Research Ethics Policy. Prior to data collection, an informed consent form was included as the first section of the online questionnaire. Participants were informed about the purpose of the study, the nature of their participation, the expected time commitment, and their rights to confidentiality, anonymity, and voluntary withdrawal without penalty. Only students who actively consented by ticking a checkbox were able to proceed with the questionnaire. Data were collected anonymously, and no identifying information such as names, student numbers, or IP addresses was recorded. All responses were stored in a password-protected digital folder, accessible only to the principal researcher and co-investigators. Participants were also informed that the data would be used strictly for academic purposes and would be reported in aggregate form to prevent the identification of individuals or institutions. To mitigate any potential distress arising from reflection on personal anxiety or motivational issues, contact information for institutional counseling services was provided at the end of the survey. Students were encouraged to seek support if the survey content triggered discomfort or academic concerns. In all, ethical rigor was maintained throughout the research process to uphold the dignity, privacy, and welfare of participants, particularly given the sensitive psychological variables under investigation.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThis aspect of the study presents the key empirical findings derived from the statistical analysis of the dataset. The analysis was guided by the study’s main objectives: to examine the relationships among perceived assessment fairness (PAF), feedback orientation (FO), assessment anxiety (AA), and academic motivation (AM) among respondents. The presentation begins with an assessment of the reliability and internal consistency of the measurement instruments used. This is followed by descriptive statistics for each of the major constructs and their subcomponents, offering insights into central tendencies, dispersion, and distribution characteristics. Subsequently, correlation analyses are reported to explore the strength and direction of associations among the variables. This is followed by multiple regression analysis to identify the predictive power of PAF, FO, and AA on AM. Finally, mediation and moderation analyses are conducted to further clarify the indirect and conditional relationships between the variables. The findings are presented in tabular format and discussed with reference to statistical significance, effect sizes, and confidence intervals.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\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\u003eReliability Results\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"12\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScale\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCronbach’s Alpha\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSEM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMin\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMax\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSkew\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eKur\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eCV (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePAF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e3.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e15.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e3.66–3.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e2.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e16.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e3.77–3.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e-0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e3.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e24.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e2.82–3.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e2.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e14.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e3.90–4.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"12\"\u003eNote. \u003cem\u003eCronbach’s alpha (α) values for all scales exceeded the acceptable threshold of 0.70, indicating good internal consistency. Descriptive statistics show that responses were moderately dispersed, with acceptable skewness and kurtosis values supporting normality assumptions. Coefficient of Variation (CV) highlights the relative variability, with Assessment Anxiety (AA) being the most variable construct.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the internal consistency reliability of all constructs was acceptable to excellent, as shown by Cronbach’s alpha values. Academic Motivation (AM) demonstrated the highest reliability (α = 0.89), followed by Feedback Orientation (FO; α = 0.85), Perceived Assessment Fairness (PAF; α = 0.82), and Assessment Anxiety (AA; α = 0.76). These coefficients indicate that the scales used were psychometrically robust and suitable for further analysis. The means for the constructs ranged from 2.91 (AA) to 3.96 (AM), suggesting generally moderate to high levels of the studied psychological constructs among respondents. The standard deviations were all below 1.00, indicating moderate dispersion, with AA showing the greatest variability (SD = 0.72). The standard error of the mean (SEM) values were low across all constructs, suggesting high precision in the mean estimates. Skewness and kurtosis values were within acceptable ranges for normal distribution assumptions (between − 1 and + 1). All constructs, except AA (which was slightly positively skewed), demonstrated slight negative skewness indicating that more respondents rated these variables at the higher end of the scale. The coefficient of variation (CV) further highlighted the relative variability of the constructs, with AA showing the greatest variability (CV = 24.75%) and AM showing the least (CV = 14.65%).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDescriptive Statistics for Key Constructs and Subscales\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstruct / Sub-Variable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMin\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMax\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSkewness\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eKurtosis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e95% CI (Lower–Upper)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerceived Assessment Fairness (Total)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3.65–3.79\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e– Procedural Fairness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3.60–3.76\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e– Distributive Fairness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3.66–3.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e– Interactional Fairness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3.66–3.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeedback Orientation (Total)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3.77–3.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e– Utility of Feedback\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3.79–3.97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e– Feedback Accountability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3.71–3.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e– Feedback Self-Efficacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3.79–3.97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAssessment Anxiety (Total)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2.82–3.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e– Worry\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2.87–3.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e– Emotionality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2.76–2.94\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcademic Motivation (Total)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3.88–4.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e– Intrinsic Motivation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3.93–4.09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e– Extrinsic Motivation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3.83–3.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cem\u003eNote. Mean scores reflect moderate to high levels across constructs. Skewness and kurtosis values are within normal limits (|1.0|), supporting the assumption of normality. The 95% confidence intervals provide precise estimates of population means for each variable.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eBreaking the constructs into their sub-components in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e revealed additional insights. For PAF, Distributive Fairness and Interactional Fairness scored slightly higher (M = 3.74 each) than Procedural Fairness (M = 3.68). All subscales showed similarly low variability (SDs ~ 0.58–0.60) and acceptable normality indicators. This suggests a balanced perception of fairness dimensions. For FO, all three subscales Utility of Feedback, Feedback Accountability, and Feedback Self-Efficacy were rated relatively high (M = ~ 3.79 to 3.88). The high inter-subscale means suggest students value feedback and perceive themselves as capable of engaging with it effectively. Assessment Anxiety subcomponents (Worry and Emotionality) had nearly identical means (2.97 and 2.85), indicating moderate levels of test-related distress. Both showed low skewness and moderate variability, consistent with previous studies on student anxiety. Lastly, Academic Motivation sub-dimensions showed that Intrinsic Motivation (M = 4.01) slightly exceeded Extrinsic Motivation (M = 3.91), suggesting that internal drives were more salient than external rewards in this student population.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePearson Correlation Matrix for Main Constructs and Sub-Variables\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"14\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProcedural Fairness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDistributive Fairness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.81**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInteractional Fairness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.78**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.80**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeedback Utility\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.52**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.49**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.53**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeedback Accountability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.45**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.47**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.46**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.67**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeedback Self-Efficacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.48**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.50**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.49**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.71**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.69**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWorry\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e− .33**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e− .36**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e− .34**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e− .28**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e− .26**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e− .25**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmotionality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e− .31**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e− .35**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e− .32**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e− .24**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e− .23**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e− .21**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.78**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntrinsic Motivation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.44**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.47**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.46**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.56**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.52**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.53**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e− .39**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e− .36**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExtrinsic Motivation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.41**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.43**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.44**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.53**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.50**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.51**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e− .37**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e− .35**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.76**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePAF Total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.89**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.90**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.91**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.50**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.46**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.48**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e− .35**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e− .34**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.45**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.42**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFO Total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.51**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.49**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.52**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.87**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.84**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.86**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e− .29**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e− .27**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.58**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.56**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e.48**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAA Total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e− .34**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e− .36**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e− .35**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e− .26**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e− .25**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e− .24**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.89**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e.91**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e− .39**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e− .37**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e− .36**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e− .28**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAM Total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.47**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.49**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.48**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.58**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.55**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.56**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e− .42**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e− .40**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.93**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.91**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e.46**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e.60**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e\u003cp\u003e− .41**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"14\"\u003eNote. \u003cb\u003ep \u0026lt; .01 (2-tailed)\u003c/b\u003e. \u003cem\u003eAll significant correlations indicate meaningful associations between variables. High positive intercorrelations among fairness and feedback subscales suggest convergent relationships, while negative correlations with anxiety indicate divergent trends.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe bivariate correlations in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e offered compelling evidence for the interplay among the constructs. All three dimensions of Perceived Assessment Fairness were highly interrelated (r = .78 to .81), which is consistent with the theoretical integration of fairness concepts. FO subcomponents (Feedback Utility, Accountability, and Self-Efficacy) correlated strongly with each other (r = .67 to .71), confirming their convergent structure. Similarly, the strong correlation between Worry and Emotionality (r = .78**) underlined the coherence of AA as a unified factor. Importantly, negative correlations emerged between AA subcomponents and both FO and PAF variables (r = -0.21 to -0.36), indicating that higher perceived fairness and stronger feedback engagement were associated with lower test anxiety. In terms of motivation, both Intrinsic and Extrinsic Motivation were strongly and positively correlated with FO (r = .53 to .56) and PAF (r = .44 to .47), while showing moderate negative correlations with AA (r = -0.35 to -0.39). The total Academic Motivation (AM) score was strongly associated with FO (r = .60**), PAF (r = .46**), and inversely with AA (r = -0.41**). These patterns suggest that fairness and feedback enhance motivation, whereas anxiety undermines it. Finally, the high correlations between the subscales and their corresponding total scores (e.g., PAF Total with sub-dimensions r = .89 to .91) validate the internal structure of the instruments.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultiple Regression Predicting Academic Motivation from Key Constructs\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePredictor Variable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnstd. B\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE B\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStd. β\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003et-v\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e95% CI (L–U)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eCohen’s f²\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eTol.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eVIF\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProcedural Fairness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.046**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.002–0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDistributive Fairness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.025**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.01–0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInteractional Fairness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.010**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.03–0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUtility of Feedback\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.021**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.02–0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeedback Accountability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.029**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.01–0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeedback Self-Efficacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.008**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.04–0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWorry (Anxiety Subscale)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-3.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.001**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.27 – -0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmotionality (Anxiety Sub)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-2.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.006**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.24 – -0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003eNote. \u003cb\u003ep \u0026lt; .05.\u003c/b\u003e \u003cem\u003eAll predictors significantly contributed to the model. Tolerance (Tol.) and Variance Inflation Factor (VIF) values indicate no multicollinearity issues (VIF \u0026lt; 5). Effect sizes (Cohen’s\u003c/em\u003e f²\u003cem\u003e) indicate small to moderate effects per predictor.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThis regression analysis in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e investigates the extent to which key constructs dimensions of perceived assessment fairness, feedback orientation, and assessment anxiety predict students’ academic motivation (AM). The model shows that all predictors significantly contribute to academic motivation, as reflected in their statistically significant p-values (all \u0026lt; 0.05). Specifically, interactional fairness (B = 0.13, β = 0.14, p = 0.010) emerges as the strongest fairness-related predictor, indicating that respectful and considerate treatment during assessment processes has a meaningful positive effect on motivation. Procedural fairness (B = 0.10, β = 0.11, p = 0.046) and distributive fairness (B = 0.09, β = 0.10, p = 0.025) also show positive but relatively smaller effects. In terms of feedback orientation, feedback self-efficacy (B = 0.16, β = 0.15, p = 0.008) is the most influential predictor, suggesting that students who feel capable of using feedback effectively are more motivated academically. Feedback utility (B = 0.14, β = 0.13, p = 0.021) and feedback accountability (B = 0.11, β = 0.12, p = 0.029) also contribute positively to motivation. Conversely, assessment anxiety components worry (B = -0.17, β = -0.16, p = 0.001) and emotionality (B = -0.14, β = -0.14, p = 0.006) negatively predict academic motivation. This indicates that higher levels of cognitive concern and emotional distress related to assessments significantly lower students’ academic motivation. All tolerance and VIF values fall within acceptable ranges (Tol \u0026gt; 0.70; VIF \u0026lt; 2), indicating no multicollinearity. Cohen’s f² effect sizes are generally small (0.01–0.03), suggesting that while the effects are statistically significant, they are modest in magnitude individually.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cb\u003eMediation Analysis Model\u003c/b\u003e (\u003cb\u003ePerceived Assessment Fairness\u003c/b\u003e → \u003cb\u003eAssessment Anxiety\u003c/b\u003e → \u003cb\u003eAcademic Motivation)\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePath\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCoefficient (B)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003et-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% CI (Lower–Upper)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePAF → Assessment Anxiety (a-path)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-6.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.51 – -0.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAssessment Anxiety → AM (b-path)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-6.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.56 – -0.28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePAF → AM (direct effect, c’)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.09–0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePAF → AM (total effect, c)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.27–0.47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndirect effect (a × b)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.09–0.24 (bootstrapped CI)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote. \u003cb\u003ep \u0026lt; .001.\u003c/b\u003e \u003cem\u003eMediation was significant as shown by a significant indirect effect. The total effect (c) of Perceived Assessment Fairness on Academic Motivation was partially mediated by Assessment Anxiety, as both direct (c’) and indirect (a × b) paths were significant with bootstrapped confidence intervals excluding zero.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThis mediation model in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e tests whether the relationship between perceived assessment fairness (PAF) and academic motivation is explained through its impact on assessment anxiety. The results show that: The \u003cb\u003ea-path\u003c/b\u003e from PAF to anxiety is significant and negative (B = -0.39, p \u0026lt; 0.001), indicating that students who perceive assessments as fair report less anxiety. The \u003cb\u003eb-path\u003c/b\u003e from anxiety to academic motivation is also significantly negative (B = -0.42, p \u0026lt; 0.001), showing that anxiety substantially reduces motivation. The direct effect of PAF on motivation (c’ path) remains significant (B = 0.21, p = 0.001), but is smaller than the total effect (c = 0.37, p \u0026lt; 0.001), confirming partial mediation. The indirect effect via anxiety is B = 0.16 (95% CI = 0.09–0.24), statistically significant based on bootstrapped confidence intervals. This means that part of the reason fair assessments improve motivation is because they alleviate assessment-related anxiety. The mediation pathway is both statistically robust and practically meaningful.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cb\u003eModeration Analysis Model\u003c/b\u003e (\u003cb\u003eFeedback Orientation moderates the effect of Assessment Anxiety\u003c/b\u003e on \u003cb\u003eAcademic Motivation\u003c/b\u003e)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePath/Interaction\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eβ (Std.)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003et-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eΔR²\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003ef²\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eVIF\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAssessment Anxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-4.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.000**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-0.45 – -0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeedback Orientation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.000**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.17–0.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAssessment Anxiety × Feedback Orientation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.017**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.02–0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003eNote. \u003cb\u003ep \u0026lt; .05.\u003c/b\u003e \u003cem\u003eThe interaction term (Assessment Anxiety × Feedback Orientation) was statistically significant, indicating that Feedback Orientation moderates the negative effect of Assessment Anxiety on Academic Motivation. ΔR² indicates the proportion of variance explained by the interaction beyond the main effects.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThis moderation model in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e assesses whether feedback orientation \u003cb\u003e(\u003c/b\u003eFO\u003cb\u003e)\u003c/b\u003e moderates the negative effect of assessment anxiety on academic motivation. The main effect of assessment anxiety is significantly negative (B = -0.31, β = -0.29, p \u0026lt; 0.001), affirming earlier findings that anxiety reduces motivation. However, feedback orientation has a positive main effect (B = 0.29, β = 0.27, p \u0026lt; 0.001), suggesting that students with stronger feedback orientation are generally more motivated. Critically, the interaction term (Assessment Anxiety × Feedback Orientation) is statistically significant (B = 0.12, β = 0.14, p = 0.017), indicating a moderating effec\u003cb\u003et\u003c/b\u003e. This means that feedback orientation buffers the negative impact of anxiety on academic motivation in other words, students who are more feedback-oriented are less affected by anxiety in terms of motivation. The change in R² due to the interaction is small (ΔR² = 0.018), and Cohen’s f² for the interaction is also small (f² = 0.02), yet the effect is statistically meaningful. VIF values remain low, indicating no collinearity concerns.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSimple Slope and Conditional Effects Analysis of Predictors on Academic Motivation (AM) \u003cem\u003e(Moderated by Feedback Orientation)\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePredictor Variable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFeedback Orientation Level\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEffect on AM (B)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStd. β\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003et\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e95% CI (Lower–Upper)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow (-1 SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-6.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.60 – -0.30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-4.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.45 – -0.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh (+ 1 SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-2.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.31 – -0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePAF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow (-1 SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.06–0.30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.15–0.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh (+ 1 SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.24–0.50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow (-1 SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.10–0.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.21–0.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh (+ 1 SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.33–0.61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cem\u003eNote. Analysis confirms that the relationship between Assessment Anxiety and Academic Motivation is conditional on levels of Feedback Orientation. Higher Feedback Orientation attenuates the negative effect of Anxiety on Motivation.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e presents the results of a conditional effects (simple slope) analysis to determine how the relationships between key predictors Assessment Anxiety (AA), Perceived Assessment Fairness (PAF), and Feedback Orientation (FO) and Academic Motivation (AM) vary at different levels of feedback orientation. Specifically, the analysis assessed the strength and direction of these relationships when FO was low (− 1 SD), average (mean), and high (+ 1 SD). For Assessment Anxiety (AA), the negative association with Academic Motivation was statistically significant at all levels of FO. When FO was low, the effect of AA on AM was most pronounced (B = -0.45, β = -0.42, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001), indicating that students who were less open to feedback and experienced high levels of anxiety demonstrated the lowest levels of academic motivation. As FO increased to the mean level, the strength of this negative relationship weakened but remained significant (B = -0.31, β = -0.29, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). At high levels of FO, the negative effect of AA on AM was further attenuated (B = -0.17, β = -0.16, \u003cem\u003ep\u003c/em\u003e = .019). These results suggest that FO functions as a moderating or buffering variable, lessening the detrimental impact of assessment-related anxiety on motivation. In practical terms, students who are more open to and accepting of feedback appear more resilient in the face of anxiety, maintaining higher motivation levels compared to their counterparts with low FO.\u003c/p\u003e\u003cp\u003eSimilarly, Perceived Assessment Fairness (PAF) showed a consistently positive and statistically significant effect on AM across all levels of FO. At low FO, the effect of PAF on AM was modest (B = 0.18, β = 0.16, \u003cem\u003ep\u003c/em\u003e = .003), indicating that even students less inclined to embrace feedback still derive motivational benefit from perceived fairness in assessment. However, this effect grew stronger at mean (B = 0.28, β = 0.26, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001) and high levels of FO (B = 0.37, β = 0.34, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). This pattern reinforces the idea that the positive impact of perceived fairness on student motivation is amplified among students with greater feedback receptiveness. Students who value feedback and believe assessments are fair tend to be more academically motivated, suggesting a synergistic effect between fairness perceptions and feedback orientation. Furthermore, FO itself significantly and positively predicted academic motivation at all levels. At low FO, the effect size was B = 0.22 (β = 0.20, \u003cem\u003ep\u003c/em\u003e = .001); at the mean level, the effect was B = 0.35 (β = 0.32, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001); and at high FO, it rose to B = 0.47 (β = 0.43, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). These results underscore the critical role of feedback orientation as a personal disposition that directly enhances motivation. Students who are more open to feedback are not only less vulnerable to the demotivating effects of anxiety but also more likely to perceive assessments positively and derive motivational gains. Overall, Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e highlights the interactive and conditional nature of student motivation, emphasizing the importance of psychological and contextual factors such as anxiety, fairness perceptions, and feedback receptivity. These findings have important implications for educational practice, suggesting that interventions aimed at enhancing FO such as building a feedback-positive classroom culture may help bolster student motivation, especially for those who struggle with anxiety.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComprehensive Model Summary for Predicting Academic Motivation\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"17\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePredictors / Interaction Term\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003et\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eR²\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eΔR²\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eAdj. R²\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eF Chg\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003eAIC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u003cp\u003eBIC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c15\"\u003e\u003cp\u003eVIF\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c16\"\u003e\u003cp\u003eTol.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c17\"\u003e\u003cp\u003ef² Effect\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(AA)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-4.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.000**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.45 – -0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.213\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e–\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.210\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e–\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e485.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e\u003cp\u003e498.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e\u003cp\u003e1.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\u003cp\u003e0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e0.27 (M)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+ (PAF)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.000**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.15–0.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e\u003cp\u003e1.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e0.18 (S–M)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+ (FO)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.000**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.21–0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.376\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.163\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.368\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e28.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e459.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e\u003cp\u003e479.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e\u003cp\u003e1.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e0.30 (M)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+ AA × (Interaction Term)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e–\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.017**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.02–0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.392\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.381\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e5.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e456.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e\u003cp\u003e481.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e\u003cp\u003e1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\u003cp\u003e0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e0.03 (S)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"17\"\u003e\u003cb\u003eNotes\u003c/b\u003e:\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"17\"\u003e• \u003cb\u003ef² Effect Size Thresholds\u003c/b\u003e: \u003cem\u003eSmall = .02, Medium = .15, Large = .35\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"17\"\u003e• \u003cem\u003eAdjusted R² accounts for model complexity\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"17\"\u003e• \u003cem\u003eAIC/BIC used for comparing model parsimony\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cem\u003eAll predictors were mean-centered before creating interaction terms\u003c/em\u003e\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e presents a series of hierarchical regression models that explore the cumulative and interactive effects of Assessment Anxiety (AA), Perceived Assessment Fairness (PAF), and Feedback Orientation (FO) on Academic Motivation (AM). This model-building approach allows for an in-depth understanding of how individual predictors and their interactions contribute to explaining the variance in AM. Model 1 includes AA as the sole predictor of academic motivation. The results indicate that AA had a significant and negative impact on AM (B = -0.31, β = -0.29, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001), accounting for 21.3% of the variance in AM (R² = 0.213). The corresponding effect size (f² = 0.27) falls within the medium range, suggesting that assessment anxiety alone is a moderate but meaningful predictor of decreased motivation. This confirms prior research indicating that high anxiety levels undermine students’ confidence and enthusiasm for academic tasks.\u003c/p\u003e\u003cp\u003eIn Model 2, PAF and FO were added to the regression equation. The inclusion of these variables significantly improved the model’s explanatory power, raising the R² to 0.376, with an R² change (ΔR²) of 0.163. Both PAF (B = 0.28, β = 0.26, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001) and FO (B = 0.35, β = 0.32, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001) emerged as strong positive predictors of AM, demonstrating that students who perceive assessments as fair and are receptive to feedback tend to be more motivated. The adjusted R² for this model was 0.368, indicating robustness even after accounting for model complexity. The model’s improved parsimony is also supported by lower AIC (459.75) and BIC (479.18) values. The effect size in this model was f² = 0.30, which also qualifies as medium, affirming the substantive contribution of these additional predictors. Model 3 introduced the interaction term between AA and FO (AA × FO) to assess whether FO moderates the relationship between anxiety and motivation. The interaction term was statistically significant (B = 0.12, \u003cem\u003ep\u003c/em\u003e = .017), indicating that the impact of anxiety on motivation indeed varies depending on the level of FO. The inclusion of this interaction increased the model’s R² slightly to 0.392, with a ΔR² of 0.016 and an adjusted R² of 0.381. Although the effect size of the interaction was small (f² = 0.03), its significance is practically relevant it provides empirical evidence that FO serves a protective function in the context of assessment anxiety. The model also showed continued improvement in model fit based on decreasing AIC (456.91) and BIC (481.64). Overall, the final comprehensive model (Model 3) offers the most complete understanding of the predictors of academic motivation. It not only identifies direct negative and positive effects of AA, PAF, and FO, respectively, but also reveals that feedback orientation plays a critical moderating role, mitigating the harmful influence of anxiety on motivation. This suggests that interventions aimed at increasing students’ feedback orientation could serve as a strategic lever to improve academic engagement and resilience, particularly for students prone to anxiety in evaluative settings.\u003c/p\u003e"},{"header":"Discussion of Results","content":"\u003cp\u003eThe purpose of this study was to investigate the relationships among perceived assessment fairness (PAF), feedback orientation (FO), assessment anxiety (AA), and academic motivation (AM) among university students. The results reveal significant direct, indirect, and interaction effects across these constructs, with implications for both theory and practice in educational psychology and assessment. The internal consistency reliability of all scales used was acceptable to excellent, with Cronbach’s alpha coefficients ranging from 0.76 (Assessment Anxiety) to 0.89 (Academic Motivation). This confirms the psychometric soundness of the instruments, consistent with standards set by [41; 38], who recommend an alpha of 0.70 or above for established scales. The relatively higher reliability for Academic Motivation and Feedback Orientation scales aligns with previous studies [e.g. 23; 48; 30; 10; 12], affirming their robustness across contexts. Descriptive data suggest that students generally perceived assessment practices as fair and felt positively oriented toward feedback. Mean scores for all fairness and FO subscales hovered above the midpoint (M \u0026gt; 3.5), indicating high engagement with these constructs. Conversely, the lower mean score for Assessment Anxiety (M = 2.91) is indicative of moderate anxiety levels, which could be interpreted in the context of supportive learning environments or adaptive coping mechanisms as posited by [64).\u003c/p\u003e\u003cp\u003eThe correlation matrix revealed several notable patterns. Perceived assessment fairness dimensions procedural, distributive, and interactional were highly intercorrelated (r = .78 to .81), corroborating prior findings that fairness is a multidimensional but interconnected construct [55; 56]. This high intercorrelation suggests that students do not compartmentalize fairness dimensions in isolation but rather evaluate assessment fairness holistically. This mirrors findings by [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], who found that in educational settings, students’ perceptions of fairness in grading and instructor behavior often blend procedural and interactional elements. All three fairness dimensions were also significantly positively associated with both feedback orientation and academic motivation, while being negatively correlated with assessment anxiety. These findings reinforce [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] assertion that procedural justice in educational contexts enhances learners’ psychological safety, leading to more engagement and less stress. A meta-analysis by [18; 25] similarly found that perceived fairness across various justice domains was positively related to motivation and negatively associated with anxiety and counterproductive behavior.\u003c/p\u003e\u003cp\u003eFurthermore, the positive relationship between fairness perceptions and feedback orientation aligns with the work of [33; 29], who found that employees (and by extension students) who perceive performance evaluations as fair are more open to receiving and acting on feedback. This is echoed by [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e], who demonstrated in a university sample that perceptions of fairness during feedback interactions predicted both feedback acceptance and student satisfaction with learning outcomes. Feedback orientation subscales including utility, accountability, and self-efficacy were positively related to academic motivation and negatively related to anxiety, supporting [10; 11] feedback-seeking model, which argues that individuals who seek feedback are more confident in their ability to improve, thus reducing anxiety about performance outcomes. More recent work by [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] confirms that individuals with a high feedback orientation demonstrate stronger goal-setting behavior and adaptive responses to academic challenges. The strong correlation between intrinsic and extrinsic motivation (r = .76) also warrants attention. Although these are theoretically distinct constructs, [22; 23] argue in their Self-Determination Theory (SDT) that they often coexist within learners, especially in structured environments like universities, where both autonomous and controlled motivations are at play. [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] similarly report that extrinsically motivated students can internalize academic goals over time, thus aligning external pressures with intrinsic values a process referred to as integrated regulation. Moving beyond correlations, multiple regression analysis demonstrated that all three fairness dimensions significantly predicted academic motivation, with interactional fairness (β = .14, \u003cem\u003ep\u003c/em\u003e = .010) and feedback self-efficacy (β = .15, \u003cem\u003ep\u003c/em\u003e = .008) emerging as the strongest contributors. These results align with the findings of [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], who emphasized that students’ sense of being respected and heard core components of interactional fairness are essential for promoting intrinsic motivation. In a study by [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], students’ perceptions of teacher autonomy support and respectful treatment were positively associated with higher academic motivation and lower burnout. Additionally, [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] found that perceived fairness in classroom assessment significantly influenced students’ goal orientations and engagement, further strengthening the claim that fairness is not only an ethical necessity but a motivational catalyst. Similarly, [48; 10] observed that students who believed their grades reflected fair evaluations were more likely to express satisfaction and enthusiasm about course content and instructor feedback.\u003c/p\u003e\u003cp\u003eFeedback orientation variables particularly utility and self-efficacy also predicted AM significantly, aligning with findings from [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], who noted that students who perceive feedback as useful and feel capable of acting on it demonstrate higher motivation and academic engagement. Anxiety subscales (worry and emotionality) negatively predicted academic motivation, supporting the well-established inverse relationship between anxiety and motivation [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. The stronger impact of worry (β = -0.16, \u003cem\u003ep\u003c/em\u003e = .001) suggests that cognitive components of anxiety may be more detrimental to motivation than physiological arousal, consistent with Cassady \u0026amp; Johnson (2022). Assessment anxiety was found to partially mediate the relationship between perceived assessment fairness and academic motivation. Specifically, PAF reduced anxiety (a-path: B = -0.39, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001), and lower anxiety, in turn, enhanced AM (b-path: B = -0.42, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001), with a significant indirect effect (ab = 0.16, CI [0.09, 0.24]). This mediating role of anxiety is supported by [10; 12] control-value theory, which suggests that students’ appraisal of fairness influences emotional experiences, which subsequently affect motivation. When assessment procedures are viewed as equitable and transparent, students are less likely to experience debilitating stress, thereby fostering better motivation. Feedback orientation significantly moderated the relationship between assessment anxiety and academic motivation. Specifically, high FO attenuated the negative impact of anxiety on motivation (interaction term: B = 0.12, \u003cem\u003ep\u003c/em\u003e = .017). This implies that students with a positive feedback orientation are better able to regulate the adverse effects of anxiety on their motivation levels. This finding aligns with [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] model of self-regulation, which posits that feedback is a crucial mechanism through which individuals evaluate progress and adjust behavior. High FO learners are likely to reinterpret anxiety-inducing feedback as constructive, leading to adaptive coping and sustained motivation [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The conditional effects analysis further clarified the interaction pattern, showing that the negative effect of anxiety on motivation was strongest when FO was low. When FO was high, the detrimental effect of anxiety on motivation was significantly reduced. This moderation effect illustrates the buffering role of metacognitive attitudes toward feedback, consistent with the work of [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], who found that the perceived utility of feedback determines its psychological impact.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study examined how students in health professions education in Ghana perceive assessment fairness, orient themselves toward feedback, and how these factors influence their academic motivation and levels of assessment anxiety. The findings revealed that procedural, distributive, and interactional fairness are strongly interrelated and significantly associated with both academic motivation and feedback orientation. Students who perceived assessments as fair reported higher motivation and lower anxiety levels. Among the fairness dimensions, interactional fairness had the strongest influence on motivation, suggesting that respectful and supportive treatment during assessments plays a critical role in shaping students\u0026rsquo; attitudes and engagement. Feedback orientation also emerged as a key factor. Students who felt confident in using feedback and valued it reported higher motivation and reduced anxiety. The results further showed that both intrinsic and extrinsic motivation are strongly linked, reflecting the complexity of students\u0026rsquo; motivational drives in high-stakes academic settings. Overall, the study concludes that students\u0026rsquo; perceptions of fairness and feedback experiences significantly impact their psychological responses to assessment. Creating a fair, transparent, and feedback-rich assessment environment can promote academic motivation and help reduce anxiety among students in health-related programs.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRecommendations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBased on the findings of this study, it is recommended that educational institutions in Ghana\u0026rsquo;s health professions sector prioritize the development and implementation of assessment practices that are perceived as fair by students. Lecturers and examination committees should ensure that procedures for both formative and summative assessments are transparent, consistent, and aligned with clearly communicated criteria. Special attention should be paid to interactional fairness how students are treated during the assessment process by fostering respectful, supportive, and inclusive communication. When students feel heard and respected, they are more likely to be motivated and less likely to experience debilitating anxiety. Secondly, there is a need to strengthen students\u0026rsquo; feedback orientation through systematic integration of feedback literacy into the curriculum. Lecturers should be trained not only to provide timely and constructive feedback but also to actively guide students on how to interpret and apply it for academic improvement. Institutions may consider introducing workshops or mentorship programs that promote feedback-seeking behaviors and boost students\u0026rsquo; confidence in using feedback effectively. This is essential for nurturing self-directed learning and reducing negative emotional responses to assessment. Furthermore, academic support services should be enhanced to address assessment-related anxiety. This may include psychological counseling, stress management workshops, and academic coaching tailored to the needs of health professions students. Since the study found that fair assessment and positive feedback experiences reduce anxiety, these services should work collaboratively with faculty to create a learning climate where assessment is seen as a developmental tool rather than a source of fear. Finally, institutional policies should reflect a commitment to continuous improvement in assessment fairness and feedback processes. This can be achieved through regular student evaluations, faculty development programs, and feedback loops that involve both staff and learners in refining assessment strategies. By embedding fairness and constructive feedback at the heart of assessment design, institutions can enhance both the academic performance and emotional well-being of future health professionals in Ghana.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations of the Study\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAlthough this study offers valuable insights into the psychological dynamics of assessment practices among health professions students in Ghana, some limitations should be recognized. First, the cross-sectional design limits the ability to draw causal inferences about the relationships among perceived fairness, feedback orientation, assessment anxiety, and academic motivation. Longitudinal research would be better suited to examine how these variables evolve over time and interact across different stages of students\u0026rsquo; academic journeys. Additionally, self-reported data may be subject to social desirability bias, with participants possibly overstating or understating their true experiences due to perceived expectations or personal discomfort. Secondly, while the study employed stratified random sampling to enhance representativeness, the sample was limited to six public nursing and midwifery training institutions, which may not fully capture the experiences of students in private institutions or those pursuing other health-related programs such as medicine, pharmacy, or public health. Regional and institutional differences in assessment culture, faculty practices, and resource availability could influence students\u0026rsquo; perceptions and psychological responses in ways not fully accounted for in this study. Future research could address these limitations by incorporating a broader range of institutions, adopting mixed methods approaches, and exploring the roles of faculty and institutional policies in shaping assessment-related outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eHPE\u003c/strong\u003e \u0026ndash; Health Professions Education, \u0026nbsp;\u003cstrong\u003eSPSS\u003c/strong\u003e \u0026ndash; Statistical Package for the Social Sciences, \u003cstrong\u003eSD\u003c/strong\u003e \u0026ndash; Standard Deviation, \u003cstrong\u003eM\u003c/strong\u003e \u0026ndash; Mean, \u003cstrong\u003e\u0026alpha;\u003c/strong\u003e \u0026ndash; Cronbach\u0026rsquo;s Alpha (internal consistency coefficient), \u003cstrong\u003er\u003c/strong\u003e \u0026ndash; Pearson\u0026rsquo;s Correlation Coefficient, \u003cstrong\u003e\u0026beta;\u003c/strong\u003e \u0026ndash; Standardized Beta Coefficient (from regression), \u003cstrong\u003eR\u0026sup2;\u003c/strong\u003e \u0026ndash; Coefficient of Determination, \u003cstrong\u003edf\u003c/strong\u003e \u0026ndash; Degrees of Freedom, \u003cstrong\u003ep\u003c/strong\u003e \u0026ndash; Probability Value (Statistical Significance), \u003cstrong\u003ePAF\u003c/strong\u003e \u0026ndash; Perceived Assessment Fairness, \u003cstrong\u003eFO\u003c/strong\u003e \u0026ndash; Feedback Orientation, \u003cstrong\u003eAA\u003c/strong\u003e \u0026ndash; Assessment Anxiety, \u003cstrong\u003eAM\u003c/strong\u003e \u0026ndash; Academic Motivation, \u003cstrong\u003eVIF\u003c/strong\u003e \u0026ndash; Variance Inflation Factor\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in full compliance with the ethical guidelines of the Declaration of Helsinki and relevant institutional and national research ethics regulations. Ethical approval was obtained from the Ethics Review Committee of the University of Education, Winneba (Protocol Ref: UEW/IRB/2024/08), as well as from the ethical review boards of all six participating nursing and midwifery training institutions across Ghana\u0026rsquo;s southern, middle, and northern ecological zones. Prior to data collection, participants were provided with detailed information about the purpose of the study, the voluntary nature of their participation, data confidentiality, and the right to withdraw without penalty. Written informed consent was obtained from all participants. Data were anonymized, securely stored, and accessible only to the principal investigators to ensure participant privacy and data protection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This study did not involve the publication of personal images, identifiable clinical information, or any data that could compromise participant anonymity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are available from the corresponding author, Simon Ntumi, upon reasonable request. Due to ethical and institutional constraints concerning participant confidentiality, raw data will not be made publicly available. All data access requests will be assessed in accordance with institutional ethical policies to ensure data security and anonymity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests. The design, execution, and reporting of this study were conducted independently and were not influenced by any external funding agency, institution, or commercial interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was fully self-funded by the authors. No external financial support was received for the conceptualization, data collection, analysis, or dissemination of the findings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express sincere appreciation to the administrators, faculty, and students of the participating nursing and midwifery training institutions for their cooperation and trust. Special thanks to the institutional ethics boards and research coordinators who facilitated approvals and logistics across the ecological zones. We are also grateful to the respondents and data cleaning personnel whose diligence contributed to the quality of this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\u003ch3\u003eAuthor Contributions\u003c/h3\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eSimon Ntumi:\u003c/strong\u003e Led the conceptualization and design of the study, developed the research methodology, supervised the overall project, performed advanced statistical data analysis, interpreted findings, drafted the initial manuscript, coordinated revisions, and served as the corresponding author responsible for communication with the journal and stakeholders.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ePaul Kobina EFFRIM:\u0026nbsp;\u003c/strong\u003eProvided proficient consultation on the study, supported data analysis and interpretation, contributed to the discussion of results, and assisted in ensuring the robustness and validity of the study\u0026rsquo;s findings.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eClarke Ebow Yalley:\u003c/strong\u003e Played a key role in conducting the literature review, contributed to the design of data collection instruments, supervised data collection procedures, assisted with data interpretation, and provided critical revisions and edits to improve the intellectual content of the manuscript.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAbraham Yeboah:\u003c/strong\u003e Provided expert consultation on statistical methods and multivariate analysis techniques, supported data analysis and interpretation, contributed to the discussion of results, and assisted in ensuring the robustness and validity of the study\u0026rsquo;s quantitative findings.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eDivine Agbovor:\u003c/strong\u003e Coordinated participant recruitment and data collection, managed data coding and organization, contributed to data analysis, and supported the drafting of sections related to data collection and methodology.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eEmmanuel Ohene Amezah:\u003c/strong\u003e Reviewed and strengthened the theoretical framework underpinning the study, contributed to contextualizing findings within existing research, and conducted thorough proofreading and editorial review to ensure clarity and coherence of the manuscript.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eFrank Henry Bonsi:\u003c/strong\u003e Assisted with managing and cleaning the data set, supported preliminary statistical analyses, contributed to data visualization efforts such as values and tables, and reviewed the results section to ensure accuracy.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAbdul-Razak Ishaaq:\u003c/strong\u003e Contributed to the synthesis of relevant literature, assisted in refining the manuscript\u0026rsquo;s structure and flow, ensured adherence to formatting guidelines, and collaborated in the final manuscript preparation.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAgyeman, D. 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Springer.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Assessment fairness, Feedback orientation, Academic motivation, Assessment anxiety, Health professions education, Ghana","lastPublishedDoi":"10.21203/rs.3.rs-6958871/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6958871/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThere is a critical gap in understanding how assessment-related psychological factors influence learning motivation and anxiety among students in Ghana’s health training institutions. The study investigated the relationships among perceived assessment fairness, feedback orientation, assessment anxiety, and academic motivation among students enrolled in health professions education in Ghana. Employing a quantitative approach nested in cross-sectional survey design, data were collected from 575 diploma and undergraduate students across six nursing and midwifery training institutions in the southern, middle, and northern ecological zones of Ghana. Stratified random sampling ensured representativeness across program type, year of study, and gender. Standardized instruments with strong internal consistency (Cronbach’s α ranging from 0.76 to 0.89) were used to measure the key constructs. Descriptive statistics revealed moderate to high levels of perceived fairness (M = 3.72, SD = 0.56), feedback orientation (M = 3.85, SD = 0.64), and academic motivation (M = 3.96, SD = 0.58), with relatively lower levels of assessment anxiety (M = 2.91, SD = 0.72). Pearson correlation analysis showed significant positive relationships between perceived assessment fairness and academic motivation (r = .46, p \u0026lt; .01), as well as between feedback orientation and academic motivation (r = .60, p \u0026lt; .01). Assessment anxiety correlated negatively with both feedback orientation (r = –.28, p \u0026lt; .01) and academic motivation (r = –.41, p \u0026lt; .01). Multiple regression analysis revealed that procedural fairness (β = .11, p = .046), distributive fairness (β = .10, p = .025), and feedback utility (β = .21, p \u0026lt; .001) were significant positive predictors of academic motivation, whereas assessment anxiety (β = –.23, p \u0026lt; .001) was a significant negative predictor. The overall regression model explained 42% of the variance in academic motivation (R² = 0.42, F(6, 568) = 67.39, p \u0026lt; .001), indicating a robust multivariate relationship. These findings highlight the importance of fair assessment practices and constructive feedback in enhancing student motivation while mitigating anxiety. The study has practical implications for assessment reforms and educator training within Ghana’s health education sector, advocating for psychologically informed approaches to curriculum delivery and evaluation.\u003c/p\u003e","manuscriptTitle":"Grading Minds and Shaping Futures: A Multivariate Analysis on the Perceptions of Fairness Anxiety, Feedback Orientation and Motivation in Ghana’s Health Professions Education","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-23 16:54:27","doi":"10.21203/rs.3.rs-6958871/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"df558aa1-0baa-4621-999d-f290722dd07f","owner":[],"postedDate":"July 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-24T16:53:39+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-23 16:54:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6958871","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6958871","identity":"rs-6958871","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}