Linking 21st Century Competencies to Academic Outcomes in Portugal

Linking 21st Century Competencies to Academic Outcomes in Portugal | 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 Linking 21st Century Competencies to Academic Outcomes in Portugal Nathan D Roberson, Michaela Horvathova This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6326658/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 The demands of the 21st century like technological advancement, evolving labor markets, and interconnectedness, highlight the necessity for education systems to emphasize both traditional knowledge and 21st Century Competencies, including critical thinking, collaboration, creativity, resilience and others. They are increasingly recognized for their role in shaping academic success and personal and professional growth. This study examines the relationship between these competencies and academic performance with international students in a Portuguese school using the Competencies Compound Inventory (CCI-21) developed by Beyond Education. A pre- and post-test design with Structural Equation Modeling (SEM) investigates the direct and indirect effects of these competencies on Math, Science, and English outcomes. Findings demonstrate a clear link between 21st Century Competencies and academic outcomes and contribute to a growing evidence base about unpacking specific competencies along with socio-demographic variables. Results inform curriculum and instruction and educational policy to promote equity and holistic development. Figures Figure 1 Introduction In the face of accelerating global challenges, education systems must evolve to address more than academic knowledge. The 21st century has ushered in a new era of global interconnectedness, rapid technological advancement, and evolving workforce demands (Voogt et al., 2013). As a result, there is a growing emphasis on the importance of 21st century competencies, also known as social and emotional skills or non-cognitive domains, in educational and professional settings. These competencies, which include critical thinking, communication, collaboration, and creativity, resilience and others are believed to be essential for success in life and work (Almulla, 2023; National Research Council et al., 2013; OECD, 2024a). Social and emotional learning (SEL) provides a structured approach to fostering these competencies. Research consistently shows that SEL enhances not only academic outcomes but also interpersonal relationships, classroom behavior, and long-term life satisfaction (Weissberg et al., 2015). While the link between 21 st Century Competencies and academic outcomes has been made through large surveys like the OECD study on Social and Emotional Skills, there is still limited research that explicitly explores these relationships, in part due to a limited number of tools measuring these competencies and available data on academic outcomes (Bialik et al., 2016). The present study aims to investigate this link between 21 st Century Competencies and academic outcomes in a late-primary/secondary school setting in Portugal. By examining the relationship between 21st Century Competencies and academic performance, this study highlights the importance of integrating SEL into educational frameworks to support holistic student development. Background In an increasingly interconnected world, the need for a well-rounded education that transcends traditional academic knowledge has become increasingly importance. In an age of AI developments where automation and advanced technologies streamline “knowledge-based” work, it is 21st Century Competencies that remain and become even more important as uniquely human-skills. SEL includes our self-awareness, empathy, and relationship management, and these dimensions play a crucial role in fostering learning and learning how to learn. 21 st Century Competencies, are not only important for academic outcomes, but are also associated with pro-social behaviors and student well-being such as reduced truancy and drop-out rates and mental health (OECD, 2024a; Weissberg et al., 2015). Emotional regulation, for example, has been shown to mitigate the effects of anxiety on test performance, enabling students to focus and perform effectively (Wang et al., 2013). The relationship between these competencies and academic outcomes is often mediated by improved classroom dynamics. Students with strong SEL skills are more likely to engage in constructive peer interactions and maintain positive relationships with teachers, fostering an environment conducive to learning (Weissberg et al., 2015). These benefits extend beyond academics, contributing to personal resilience and social cohesion. The recognition of 21st Century Competencies as critical educational outcomes is relatively recent. Historically, education systems focused on knowledge acquisition, with little attention given to skills like collaboration or creativity. However, shifts in labor market demands and societal expectations have propelled these competencies into the spotlight (Chernyshenko et al., 2018; Cipriano & McCarthy, 2023; Fadel et al., 2024). These competencies are important for learning how to work with others and how to learn with new technologies and the important skills and character of how to use these technologies. The shift towards competency-based education has large implications on our education system. Increasingly countries around the world are integrating competency-based frameworks or similar frameworks into their state-level standards. British Columbia (Canada), Brazil, South Africa, Singapore, and others have all adopted some form of competency framework, which accordingly has implications for how teaching is done in the classroom (OECD, 2024b). Similarly, the OECD has prioritized social and emotional competencies in international assessments, recognizing their significance for academic achievement, mental health, and societal well-being (Linzarini & Silva, 2024; OECD, 2024a). The growing mapping and promotion of these tools helps to provide educators with the necessary resources in order to adopt and implement the shifts towards competency-based education. While multiple frameworks of competency-based education have been put forward with many overlapping elements, these authors make use of the 4-Dimensional model of education, which has been recently revised (Fadel et al., 2015, 2024). The 4D model has been elsewhere described in detail but consists of the Knowledge (what a person knowns or understands); Skills (the way a person uses what they know); Character (how people behave and engage in the world); and Meta-Learning (one’s capacity for self-reflection to adapt and grow their learning). Since the implementation of secular-based education, schools have traditionally focused mostly on the Knowledge dimensions. But with the evolution in work-place dynamics and technology shifts, it is clear that Skills, Character, and Meta-Learning are important as contributors to relationship building, self-management, and adaptability for a change labor market and changing planet (Bialik et al., 2015; Kearney et al., 2024). As educational frameworks adapt to these needs, the integration of social emotional learning (SEL) into curricula emerges as a strategic approach to enhancing student engagement and academic outcomes, ultimately preparing them for success in the 21st-century workplace(Solberg et al., 2020). Meanwhile, it is also clear that our education systems cannot merely replace knowledge-based instruction for competency-based instruction. Rather, as clearly articulated by the Centre for Curriculum Redesign (CCR), competency instruction is woven in and throughout knowledge based dimensions for a more holistic educational framework (Fadel et al., 2024). Academic outcomes, often measured by standardized assessments, are also influenced by the other dimensions; students with well-developed social-emotional competencies are more likely to engage constructively in their studies, leading to improved grades and better retention of knowledge (Solberg et al., 2020). As such, the link between the teaching of competencies and traditional academics needs to be further studied to emphasize the link of holistic advancement and development. In 2023, the OECD Survey on Social and Emotional Skills (SES) was released which in addition to affirming the importance of competency education, begins to unpack the differential way that competencies are expressed (OECD, 2024a). Namely it is not enough to “just” advance competency instruction, but we should also be aware of the way in which specific competencies are related to certain disciplines, that gender and socio-economic disparities exist across certain sets of competencies. For example, gender gaps in academic have been frequently shown (Kankaraš & Moors, 2014; OECD, 2023) as they have been in health and well-being indicators (Kennedy et al., 2020). The SES Survey from OECD found SEL disparities in gender, such as boys reporting high emotional regulation (stress resistance or optimism), trust and self-control on average across sites, while girls reported higher levels of tolerance, empathy, and responsibility (OECD, 2024a). Similarly, students with lower socioeconomic advantage also reported lower levels on the SES survey. The OECD survey, while extensive, only provides us insight of student outcomes at a single-point in time. These disparities highlight the importance of targeted interventions. However, the mechanisms to monitor and track are encumbered by a lack of tools used in educational settings underlying the importance of continued research are 21 st Century Competencies in classroom settings. Methods Measurement Academic outcomes where provided by the school for three subjects: Math, English, and Science and were on a 1 to 9 point scale for both the pre- (fall) and post-test (spring) windows. A composite of student “learner-profile” was also collected for each subject, however given data inconsistency and only available at time 1 was excluded from this analysis. Likewise, the school provided the number of years each student was enrolled at the school. 21 st Century Competencies were measured using the Beyond Education, Competency Compound Inventory for the 21 st Century (CCI-21). Developed by Celume & Maoulida (2022), the CCI-21 is an age-calibrated self-reflective questionnaire, similar to the OECD SES Survey (OECD, 2024a) to assess 12 competencies: Skills (creativity, communication, collaboration, and creativity), Character (curiosity, courage, ethics, leadership, resilience, and mindfulness), and Meta-Learning (meta-cognition and growth mindset) and has a reliability score of .92 using Cronbach’s alpha. The CCI-21 is delivered online and takes approximately 30 minutes to complete. The scale ranges from 3 to 15 per competency with three items per competency, where a higher score indicates higher levels of the competency. The CCI-21 is age-calibrated to assign development-level using an ordinal scale, however, for the sake of parametric analyses performed here, the raw score is used, which is appropriate since we are assessing differences in time and correlations with the academic outcomes. Sample In total 242 students were sampled from a large metropolis region in Portugal. Students were enrolled in an international school with instruction in English as a part of an IB curriculum, which also places emphasis on holistic domains of 21 st Century Learning. Students were spread across three grades (grade 6- 104; grade 7 – 70; and grade 9 – 68) with a mean age of 12.3 (SD=1.4). Methodology In total the research team had 12 different 21 st Century Competencies and 3 academic outcomes at two time-points. Descriptive statistics and Pearson correlations were considered separately at both time 1 and time 2. Likewise, as a preliminary analysis not shown here, OLS regressions were conducted at time 1 and time 2 to investigate any predictive relationship while controlling for other covariates. Covariates included were grade (grade 7 and grade 9 were dummy coded), gender (male = 1, female = 0), and the number of years a student was enrolled in the school (mean = 3.9, SD =2.3). Positive covariates were then included in our final models below. Analyses are considered exploratory in nature and not confirmatory, since we are engaging in theory building given the lack of existing evidence for these specific competencies and subjects, and moreover given no existing evidence for the CCI-21 and academic outcomes. Nevertheless, when reporting linear model results, consideration for multiple comparisons was done using a Bonferroni correction. To account for the multi-variate outcomes per period, we employed a Structural Equation Modeling (SEM) framework to account for the baseline academic performance (time 1), the baseline relationship between competencies and time 1, and their respective predictive outcomes on time 2. See Fig 1. for an example of the path relationship for Critical Thinking (CT) on Science. While the competencies are latent-variables, given the limited sample size and reduced power we consider them as observed variables for this analysis using their respective sum scores. Fit statistics including Chi-squared goodness of fit, RMSEA, CFI, and TLI were used to assess the models. [Insert Figure 1] We are interested in both the direct relationship between the competencies and the academic outcomes at time 1, and both the direct and indirect relationship of the competencies from time 1 (direct and indirect) and time 2 (direct) on the outcomes at time 2. Direct effects between the competencies at time 2 and outcomes at time 2 can be considered as the effect on the academic outcomes as explained by the change in competencies between time 1 and time 2. We anticipate there will be a strong direct relationship between the outcomes between time 1 and time 2. We also anticipate there to be a non-uniform but positive relationship between the 12 competencies and the academic outcomes. Analyses were completed in Stata16. Results Descriptives Descriptive statistics of the academic outcomes (math, science, and English) and the 12 21st Century competencies can be found in Table 1 below. On average, students’ math scores remained the same, their English scores increased (+ .2), and their science scores decreased (-.2). For most competencies, students’ competencies also experienced a slight increased in scores, except for Ethics and Leadership, which remained the same, and Meta-Cognition which decreased by .2 points. Students’ overall CCI-21 raw score increased by 8.9 points from pre- to post-test. Table 1 Summary Statistics of (Non-)Academic Outcomes Post-Test Pre-Test Measure Mean SD Min Max Mean SD Min Max Math 6.9 1.2 2 9 6.9 1.2 2 9 English 6.8 1.1 4 9 6.6 1.1 4 9 Science 7.4 1.6 3 9 7.6 1.6 2 9 CCI-21 134.6 20.5 41 180 125.7 19.9 36 172 Creativity 10.6 2.3 3 15 10.4 2.4 3 15 Critical Thinking 10.7 2.3 3 15 10.5 2.3 3 15 Communication 11.0 2.4 3 15 10.4 2.6 3 15 Collaboration 11.0 2.6 3 15 10.7 2.5 3 15 Mindfulness 10.8 2.2 3 15 10.4 2.3 3 15 Curiosity 10.8 2.7 3 15 10.7 2.6 3 15 Courage 10.7 2.4 3 15 10.4 2.4 3 15 Resilience 10.7 2.3 3 15 10.4 2.6 3 15 Ethics 10.6 2.5 3 15 10.6 2.5 3 15 Leadership 10.6 2.6 3 15 10.6 2.6 3 15 Meta-Cognition 9.2 2.5 3 15 9.4 2.5 3 15 Growth Mindset 11.4 2.3 3 15 11.2 2.5 3 15 Note: N = 242 [Insert Table 1 ] Table 2 below shows the bi-relational Pearson’s correlation of the academic and non-academic outcomes. Nearly all correlations are small to moderate and positive. All correlations on the pre-test were statistically significant, whereas the post-test correlations depended by competency and subject but were not necessarily statistically significant. Two correlations were negative: English and Science pre- (-.04), and Ethics and Science post- (-.04, non-significant). Math and Science were the most strongly correlated (.48 pre, .62 post). Table 2 Correlations of (Non-)Academic Outcomes by time Pre-Test Post-Test Math English Science Math English Science English 0.27 0.49 Science 0.48 -0.04 0.62 0.35 CCI-21 0.32 0.29 0.14 0.27 0.17 0.14 Creativity 0.15 0.06 0.03 0.18 0.02 0.12 Critical Thinking 0.23 0.24 0.07 0.14 0.21 -0.01 Communication 0.38 0.35 0.15 0.29 0.25 0.22 Collaboration 0.13 0.14 0.07 0.10 0.05 0.00 Mindfulness 0.16 0.14 0.04 0.09 0.00 0.08 Curiosity 0.18 0.23 0.08 0.21 0.22 0.19 Courage 0.19 0.21 0.10 0.20 0.11 0.11 Resilience 0.31 0.18 0.17 0.17 0.03 0.16 Ethics 0.13 0.21 0.00 0.15 0.10 -0.04 Leadership 0.29 0.15 0.24 0.24 0.07 0.16 Meta-Cognition 0.10 0.09 0.06 0.13 0.06 0.04 Growth Mindset 0.32 0.29 0.12 0.27 0.20 0.09 Note: N = 242, Pearson’s Correlation, Underlined shows correlations NOT significant at p < .05 [Insert Table 2 ] SEM Pathways Given the number of models considered (36: each competency per academic outcome) we present a summary of the significant competency pathways by academic outcome and time in Table 3 . Full model results can be found in the supplementary materials. Table 3 Summary of SEM Effects by Subject and Competency Effect Math Pre Math Post English Pre English Post Science Pre Science Post Direct CT , CR, CM , CU, ET, CO, RS , MN, LE, GR CL CT, CM, CU , ET, CO, RS , MN, LE, GR CT, CM, CO, RS, LE, GR Indirect - CT , CR, CM, CU , ET, CO, RS , MN, LE, GR - CT, CM, CU , ET, CO, RS, LE, GR - CT, CM, CO, RS, LE, GR Total CT , CR, CM , CU, ET, CO, RS , MN, LE, GR CT, CM , CU, CO , RS, LE, GR CT, CM, CU , ET, CO, RS , MN, LE, GR CT, CM , CL, RS, LE, GR CT, CM, CO, RS, LE, GR CT, CM , CU, CO, RS , MN, LE, GR Δ Comp - CL - CM, CU, GR - Other Variables Direct G9 (-), Years at School (+) Math pre, G9 (-) Male (-), G7 (+), G9 (+) English pre, Male (-), G9 (-) G9 (-) , Years at school (+) Science pre, G9 (-) Indirect - G9 (-), Years at School (+) Male (-), G7 (+), G9 (+) - G9 (-) , Years at school (+) Total G9 (-), Years at School (+) Math pre, G9 (-), Years at School (+) Male (-), G7 (+), G9 (+) English pre, Male (-) G9 (-) , Years at school Science pre, G9 (-) Note: N = 237 (Math) and 241 (Science and English); Listed Competencies are significant at p < .05, and Bolded and italicized competencies are significant after Bonferroni correction for multiple comparisons. Critical Thinking (CT), Creativity (CR), Communication (CM), Collaboration (CL), Curiosity (CU), Ethics (ET), Courage (CO), Resilience (RS), Leadership (LE), Mindfulness (MN), Meta-Cognition (MT), Growth Mindset (GR) [Insert Table 3 ] Significant SEM paths depend heavily on the competency and outcome in question. In general, Critical Thinking, Communication, Curiosity, Resilience, Leadership, and Growth Mindset were the competencies most present and significant across all three academic outcomes for both time periods one and two. In general, Collaboration and Ethics were not a significant pathway. Mindfulness was present as a significant predictor, but was never robust to a correction for multiple comparisons. Meta-cognition was nowhere significant in the SEM models. Our “Δ Comp” variable, assess whether the post-test competency direct effect is significant after already accounting for the pre- and post-test effects of the same competency. That is to say, it represents a change in the competency and its relationship to the academic outcomes. Only four competencies (Collaboration, Communication, Curiosity, and Growth Mindset were present as a change in their competency, but they were not robust to a correction for multiple comparisons. Other moderating variables were also significant. Students’ pre-test academic outcomes were unsurprisingly always predictive of their post-test scores. Male students consistently scored lower in English. Likewise, there were frequently difference across average scores by student grade-level, which was only included as a control. The number of years a student was enrolled in the school was robust and predictive for math outcomes, and some evidence for science, but not for English. Overall fit statics indicated that the SEM models fit best when examining English as an academic outcome with all 12 competencies demonstrating good fit. Model fit for Critical Thinking, Communication, Curiosity and Growth Mindset and Math was poor, while the other competencies were good. Likewise, model fit for Curiosity and Meta-Cognition and Science was adequate, while the rest were good. Discussion The findings from this study have numerous contributions to the field of Social and Emotional Learning (SEL). Consistent with the previously cited research from the OECD and academic research, our findings confirm there is a positive and significant relationship between academic and non-academic outcomes. Our research advances the theory building and research by further clarifying the nature of expected relationships through disaggregation of these claims by subject (math, English, or science) and the 12 competencies measured by the CC-21. Moreover, our research goes one step further by being able to connect the changes in competencies with the changes in academic outcomes as well. Large-scale surveys like the OECD, while robust in terms of sample size and representative samples of students within countries are only able to measure students’ outcomes at a single-point in time, where year-over-year comparisons have many confounding variables. This study, while limited in scope of a single international school, enables a deep investigation of the relationship of 21st Century Competencies and academic outcomes. The findings underscore the critical role of 21st Century Competencies in fostering academic and personal success. Integrating SEL into curricula enables students to develop skills that extend beyond academics, preparing them for future challenges. Likewise, this research confirms the belief that these competencies can be taught given that the number of years a student is enrolled in their school which integrates SEL is in fact predictive of the outcomes. Understanding the nature of SEL programs can mitigate disparities in competency development, particularly among disadvantaged students or groups with known-demographic differences. By focusing on competencies like emotional regulation and perseverance, schools can promote equitable academic outcomes and social mobility (OECD, 2023 ). Future research using the CCI-21 or other measures would benefit from integrating additional demographic moderators like wealth or other outcomes like health measures at multiple time points, which was not available here. Tools like the CCI-21 provide educators with actionable insights by disaggregating what we mean by 21st Century Competencies to enable tailored interventions to meet individual student needs (Cipriano & McCarthy, 2023 ).As thoroughly discussed by Fadel et al. ( 2024 ), this is not a trade-off between teaching knowledge or 21st Century Competencies, rather the art of teaching and learning becomes how to teach 21st Century Competencies within and through knowledge dimensions which remain integral. This research argues that policymakers should continue to prioritize the implementation of SEL frameworks within national education systems. While schools such as the one that participated in this study are becoming increasingly more popular and frequent, they are often exceptions rather than the norm of educational institutions. Policy makers should be aware of how private educational institutions like this one are moving ahead to integrate 21st century competencies into their curriculums, which further underscores the need for system-level change to promote these holistic models. Conclusion The integration of 21st Century Competencies into education systems represents a paradigm shift toward holistic development. By fostering social and emotional skills alongside cognitive abilities, schools can better prepare students for the demands of the modern world. While challenges in measurement and implementation persist, this study contributes to the growing body of evidence supporting SEL’s transformative potential. Future research should continue to explore the nuanced relationships between specific competencies and academic outcomes, informing targeted and effective educational practices. Declarations Funding: No funding was provided Clinical trial number: not applicable Ethics, Consent to Participate, and Consent to Publish declarations: The need for ethical approval was waived off by the ethical committee of BE-LPI because of this study involved the secondary analysis of anonymized data provided by the data controller to the research team, acting as data processors. The data were originally collected in accordance with relevant ethical standards, and no new data collection or direct interaction with human participants took place. Informed consent was obtained from all individual participants involved in the study. No declarations are included, so no consent is required. Author Contribution Roberson: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Supervision, Validation, Writing – original, review, & editing; Horvathova: Funding acquisition, Resources, Writing – review & editing Data Availability The data that support the findings of this study are not available given restrictions apply to the availability of these data, which were used under licence for the current study. References Almulla MA. Constructivism learning theory: A paradigm for students’ critical thinking, creativity, and problem solving to affect academic performance in higher education. 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OpenBU. https://hdl.handle.net/2144/40488 Voogt J, Erstad O, Dede C, Mishra P. Challenges to learning and schooling in the digital networked world of the 21st century. J Comput Assist Learn. 2013;29(5):403–13. https://doi.org/10.1111/jcal.12029 . Wang M-T, Brinkworth M, Eccles J. Moderating effects of teacher–student relationship in adolescent trajectories of emotional and behavioral adjustment. Dev Psychol. 2013;49(4):690–705. https://doi.org/10.1037/a0027916 . Weissberg RP, Durlak JA, Domitrovich CE, Gullotta TP, editors. Social and emotional learning: Past, present, and future. Handbook of social and emotional learning: Research and practice. The Guilford Press; 2015. pp. 3–19. Additional Declarations No competing interests reported. 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The 21st century has ushered in a new era of global interconnectedness, rapid technological advancement, and evolving workforce demands (Voogt et al., 2013). As a result, there is a growing emphasis on the importance of 21st century competencies, also known as social and emotional skills or non-cognitive domains, in educational and professional settings. These competencies, which include critical thinking, communication, collaboration, and creativity, resilience and others are believed to be essential for success in life and work (Almulla, 2023; National Research Council et al., 2013; OECD, 2024a).\u003c/p\u003e\n\u003cp\u003eSocial and emotional learning (SEL) provides a structured approach to fostering these competencies. Research consistently shows that SEL enhances not only academic outcomes but also interpersonal relationships, classroom behavior, and long-term life satisfaction (Weissberg et al., 2015). While the link between 21\u003csup\u003est\u003c/sup\u003e Century Competencies and academic outcomes has been made through large surveys like the OECD study on Social and Emotional Skills, there is still limited research that explicitly explores these relationships, in part due to a limited number of tools measuring these competencies and available data on academic outcomes (Bialik et al., 2016). The present study aims to investigate this link between 21\u003csup\u003est\u003c/sup\u003e Century Competencies and academic outcomes in a late-primary/secondary school setting in Portugal. By examining the relationship between 21st Century Competencies and academic performance, this study highlights the importance of integrating SEL into educational frameworks to support holistic student development.\u003c/p\u003e"},{"header":"Background","content":"\u003cp\u003eIn an increasingly interconnected world, the need for a well-rounded education that transcends traditional academic knowledge has become increasingly importance. In an age of AI developments where automation and advanced technologies streamline \u0026ldquo;knowledge-based\u0026rdquo; work, it is 21st Century Competencies that remain and become even more important as uniquely human-skills. SEL includes our self-awareness, empathy, and relationship management, and these dimensions play a crucial role in fostering learning and learning how to learn. 21\u003csup\u003est\u003c/sup\u003e Century Competencies, are not only important for academic outcomes, but are also associated with pro-social behaviors and student well-being such as reduced truancy and drop-out rates and mental health (OECD, 2024a; Weissberg et al., 2015). Emotional regulation, for example, has been shown to mitigate the effects of anxiety on test performance, enabling students to focus and perform effectively (Wang et al., 2013). The relationship between these competencies and academic outcomes is often mediated by improved classroom dynamics. Students with strong SEL skills are more likely to engage in constructive peer interactions and maintain positive relationships with teachers, fostering an environment conducive to learning (Weissberg et al., 2015). These benefits extend beyond academics, contributing to personal resilience and social cohesion.\u003c/p\u003e\n\u003cp\u003eThe recognition of 21st Century Competencies as critical educational outcomes is relatively recent. Historically, education systems focused on knowledge acquisition, with little attention given to skills like collaboration or creativity. However, shifts in labor market demands and societal expectations have propelled these competencies into the spotlight (Chernyshenko et al., 2018; Cipriano \u0026amp; McCarthy, 2023; Fadel et al., 2024). These competencies are important for learning how to work with others and how to learn with new technologies and the important skills and character of how to use these technologies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe shift towards competency-based education has large implications on our education system. Increasingly countries around the world are integrating competency-based frameworks or similar frameworks into their state-level standards. British Columbia (Canada), Brazil, South Africa, Singapore, and others have all adopted some form of competency framework, which accordingly has implications for how teaching is done in the classroom (OECD, 2024b). Similarly, the OECD has prioritized social and emotional competencies in international assessments, recognizing their significance for academic achievement, mental health, and societal well-being (Linzarini \u0026amp; Silva, 2024; OECD, 2024a). The growing mapping and promotion of these tools helps to provide educators with the necessary resources in order to adopt and implement the shifts towards competency-based education.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhile multiple frameworks of competency-based education have been put forward with many overlapping elements, these authors make use of the 4-Dimensional model of education, which has been recently revised (Fadel et al., 2015, 2024). The 4D model has been elsewhere described in detail but consists of the Knowledge (what a person knowns or understands); Skills (the way a person uses what they know); Character (how people behave and engage in the world); and Meta-Learning (one\u0026rsquo;s capacity for self-reflection to adapt and grow their learning). Since the implementation of secular-based education, schools have traditionally focused mostly on the Knowledge dimensions. But with the evolution in work-place dynamics and technology shifts, it is clear that Skills, Character, and Meta-Learning are important as contributors to relationship building, self-management, and adaptability for a change labor market and changing planet (Bialik et al., 2015; Kearney et al., 2024).\u003c/p\u003e\n\u003cp\u003eAs educational frameworks adapt to these needs, the integration of social emotional learning (SEL) into curricula emerges as a strategic approach to enhancing student engagement and academic outcomes, ultimately preparing them for success in the 21st-century workplace(Solberg et al., 2020). Meanwhile, it is also clear that our education systems cannot merely replace knowledge-based instruction for competency-based instruction. Rather, as clearly articulated by the Centre for Curriculum Redesign (CCR), competency instruction is woven in and throughout knowledge based dimensions for a more holistic educational framework (Fadel et al., 2024). Academic outcomes, often measured by standardized assessments, are also influenced by the other dimensions; students with well-developed social-emotional competencies are more likely to engage constructively in their studies, leading to improved grades and better retention of knowledge (Solberg et al., 2020). As such, the link between the teaching of competencies and traditional academics needs to be further studied to emphasize the link of holistic advancement and development.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn 2023, the OECD Survey on Social and Emotional Skills (SES) was released which in addition to affirming the importance of competency education, begins to unpack the differential way that competencies are expressed (OECD, 2024a). Namely it is not enough to \u0026ldquo;just\u0026rdquo; advance competency instruction, but we should also be aware of the way in which specific competencies are related to certain disciplines, that gender and socio-economic disparities exist across certain sets of competencies. For example, gender gaps in academic have been frequently shown (Kankara\u0026scaron; \u0026amp; Moors, 2014; OECD, 2023) as they have been in health and well-being indicators (Kennedy et al., 2020). The SES Survey from OECD found SEL disparities in gender, such as boys reporting high emotional regulation (stress resistance or optimism), trust and self-control on average across sites, while girls reported higher levels of tolerance, empathy, and responsibility (OECD, 2024a). Similarly, students with lower socioeconomic advantage also reported lower levels on the SES survey. The OECD survey, while extensive, only provides us insight of student outcomes at a single-point in time. These disparities highlight the importance of targeted interventions. However, the mechanisms to monitor and track are encumbered by a lack of tools used in educational settings underlying the importance of continued research are 21\u003csup\u003est\u003c/sup\u003e Century Competencies in classroom settings.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eMeasurement\u003c/h2\u003e\n\u003cp\u003eAcademic outcomes where provided by the school for three subjects: Math, English, and Science and were on a 1 to 9 point scale for both the pre- (fall) and post-test (spring) windows. A composite of student \u0026ldquo;learner-profile\u0026rdquo; was also collected for each subject, however given data inconsistency and only available at time 1 was excluded from this analysis. Likewise, the school provided the number of years each student was enrolled at the school.\u003c/p\u003e\n\u003cp\u003e21\u003csup\u003est\u003c/sup\u003e Century Competencies were measured using the Beyond Education, Competency Compound Inventory for the 21\u003csup\u003est\u003c/sup\u003e Century (CCI-21). Developed by Celume \u0026amp; Maoulida (2022), the CCI-21 is an age-calibrated self-reflective questionnaire, similar to the OECD SES Survey (OECD, 2024a) to assess 12 competencies: Skills (creativity, communication, collaboration, and creativity), Character (curiosity, courage, ethics, leadership, resilience, and mindfulness), and Meta-Learning (meta-cognition and growth mindset) and has a reliability score of .92 using Cronbach\u0026rsquo;s alpha. The CCI-21 is delivered online and takes approximately 30 minutes to complete. \u0026nbsp;The scale ranges from 3 to 15 per competency with three items per competency, where a higher score indicates higher levels of the competency. The CCI-21 is age-calibrated to assign development-level using an ordinal scale, however, for the sake of parametric analyses performed here, the raw score is used, which is appropriate since we are assessing differences in time and correlations with the academic outcomes.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eSample\u003c/h2\u003e\n\u003cp\u003eIn total 242 students were sampled from a large metropolis region in Portugal. Students were enrolled in an international school with instruction in English as a part of an IB curriculum, which also places emphasis on holistic domains of 21\u003csup\u003est\u003c/sup\u003e Century Learning. Students were spread across three grades (grade 6- 104; grade 7 \u0026ndash; 70; and grade 9 \u0026ndash; 68) with a mean age of 12.3 (SD=1.4).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eMethodology\u003c/h2\u003e\n\u003cp\u003eIn total the research team had 12 different 21\u003csup\u003est\u003c/sup\u003e Century Competencies and 3 academic outcomes at two time-points. Descriptive statistics and Pearson correlations were considered separately at both time 1 and time 2. Likewise, as a preliminary analysis not shown here, OLS regressions were conducted at time 1 and time 2 to investigate any predictive relationship while controlling for other covariates. Covariates included were grade (grade 7 and grade 9 were dummy coded), gender (male = 1, female = 0), and the number of years a student was enrolled in the school (mean = 3.9, SD =2.3). Positive covariates were then included in our final models below.\u003c/p\u003e\n\u003cp\u003eAnalyses are considered exploratory in nature and not confirmatory, since we are engaging in theory building given the lack of existing evidence for these specific competencies and subjects, and moreover given no existing evidence for the CCI-21 and academic outcomes. Nevertheless, when reporting linear model results, consideration for multiple comparisons was done using a Bonferroni correction.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo account for the multi-variate outcomes per period, we employed a Structural Equation Modeling (SEM) framework to account for the baseline academic performance (time 1), the baseline relationship between competencies and time 1, and their respective predictive outcomes on time 2. See Fig 1. for an example of the path relationship for Critical Thinking (CT) on Science. While the competencies are latent-variables, given the limited sample size and reduced power we consider them as observed variables for this analysis using their respective sum scores. Fit statistics including Chi-squared goodness of fit, RMSEA, CFI, and TLI were used to assess the models.\u003c/p\u003e\n\u003cp\u003e[Insert Figure 1]\u003c/p\u003e\n\u003cp\u003eWe are interested in both the direct relationship between the competencies and the academic outcomes at time 1, and both the direct and indirect relationship of the competencies from time 1 (direct and indirect) and time 2 (direct) on the outcomes at time 2. Direct effects between the competencies at time 2 and outcomes at time 2 can be considered as the effect on the academic outcomes as explained by the change in competencies between time 1 and time 2. We anticipate there will be a strong direct relationship between the outcomes between time 1 and time 2. We also anticipate there to be a non-uniform but positive relationship between the 12 competencies and the academic outcomes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAnalyses were completed in Stata16.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eDescriptives\u003c/p\u003e \u003cp\u003eDescriptive statistics of the academic outcomes (math, science, and English) and the 12 21st Century competencies can be found in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e below. On average, students\u0026rsquo; math scores remained the same, their English scores increased (+\u0026thinsp;.2), and their science scores decreased (-.2). For most competencies, students\u0026rsquo; competencies also experienced a slight increased in scores, except for Ethics and Leadership, which remained the same, and Meta-Cognition which decreased by .2 points. Students\u0026rsquo; overall CCI-21 raw score increased by 8.9 points from pre- to post-test.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary Statistics of (Non-)Academic Outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ePost-Test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ePre-Test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeasure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e 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\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCI-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e134.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e125.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e172\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreativity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCritical Thinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollaboration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMindfulness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCuriosity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCourage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResilience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeadership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeta-Cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrowth Mindset\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNote: N\u0026thinsp;=\u0026thinsp;242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\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 \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Insert Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below shows the bi-relational Pearson\u0026rsquo;s correlation of the academic and non-academic outcomes. Nearly all correlations are small to moderate and positive. All correlations on the pre-test were statistically significant, whereas the post-test correlations depended by competency and subject but were not necessarily statistically significant. Two correlations were negative: English and Science pre- (-.04), and Ethics and Science post- (-.04, non-significant). Math and Science were the most strongly correlated (.48 pre, .62 post).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\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\u003eCorrelations of (Non-)Academic Outcomes by time\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ePre-Test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003ePost-Test\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEnglish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eScience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEnglish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eScience\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnglish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.27\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 \u003cp\u003e0.49\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCI-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreativity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.02\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.12\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCritical Thinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e-0.01\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollaboration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.10\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.05\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.00\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMindfulness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.09\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.00\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.08\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCuriosity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCourage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.11\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.11\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResilience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.03\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.10\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e-0.04\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeadership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.07\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeta-Cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.06\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.04\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrowth Mindset\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.09\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eNote: N\u0026thinsp;=\u0026thinsp;242, Pearson\u0026rsquo;s Correlation, \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eUnderlined\u003c/span\u003e shows correlations NOT significant at p\u0026thinsp;\u0026lt;\u0026thinsp;.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Insert Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eSEM Pathways\u003c/p\u003e \u003cp\u003eGiven the number of models considered (36: each competency per academic outcome) we present a summary of the significant competency pathways by academic outcome and time in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Full model results can be found in the supplementary materials.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\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\u003eSummary of SEM Effects by Subject and Competency\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eEffect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMath Pre\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMath Post\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEnglish Pre\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEnglish Post\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eScience Pre\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eScience Post\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eCT\u003c/b\u003e, CR, \u003cb\u003eCM\u003c/b\u003e, \u003cb\u003eCU, ET, CO, RS\u003c/b\u003e, MN, \u003cb\u003eLE, GR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eCT, CM, CU\u003c/b\u003e, ET, \u003cb\u003eCO, RS\u003c/b\u003e, MN, \u003cb\u003eLE, GR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eCT, CM, CO, RS, LE, GR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\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\u003eIndirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCT\u003c/b\u003e, CR, \u003cb\u003eCM, CU\u003c/b\u003e, ET, \u003cb\u003eCO, RS\u003c/b\u003e, MN, \u003cb\u003eLE, GR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eCT, CM, CU\u003c/b\u003e, ET, \u003cb\u003eCO, RS, LE, GR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eCT, CM, CO, RS, LE, GR\u003c/b\u003e\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\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eCT\u003c/b\u003e, CR, \u003cb\u003eCM\u003c/b\u003e, \u003cb\u003eCU, ET, CO, RS\u003c/b\u003e, MN, \u003cb\u003eLE, GR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCT, CM\u003c/b\u003e, CU, \u003cem\u003eCO\u003c/em\u003e, \u003cb\u003eRS, LE, GR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eCT, CM, CU\u003c/b\u003e, ET, \u003cb\u003eCO, RS\u003c/b\u003e, MN, \u003cb\u003eLE, GR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eCT, CM\u003c/b\u003e, CL, RS, LE, \u003cb\u003eGR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eCT, CM, CO, RS, LE, GR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eCT, CM\u003c/b\u003e, CU, \u003cb\u003eCO, RS\u003c/b\u003e, MN, \u003cb\u003eLE, GR\u003c/b\u003e\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\u003eΔ Comp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCM, CU, GR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eOther Variables\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eG9 (-), \u003cb\u003eYears at School (+)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eMath pre, G9 (-)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eMale (-), G7 (+), G9 (+)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eEnglish pre, Male (-), G9 (-)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eG9 (-)\u003c/b\u003e, Years at school (+)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eScience pre, G9 (-)\u003c/b\u003e\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\u003eIndirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eG9 (-), Years at School (+)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eMale (-), G7 (+), G9 (+)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eG9 (-)\u003c/b\u003e, Years at school (+)\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\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eG9 (-), \u003cb\u003eYears at School (+)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eMath pre, G9 (-), Years at School (+)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eMale (-), G7 (+), G9 (+)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eEnglish pre, Male (-)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eG9 (-)\u003c/b\u003e, Years at school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eScience pre, G9 (-)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eNote: N\u0026thinsp;=\u0026thinsp;237 (Math) and 241 (Science and English); Listed Competencies are significant at p\u0026thinsp;\u0026lt;\u0026thinsp;.05, and Bolded and italicized competencies are significant after Bonferroni correction for multiple comparisons. Critical Thinking (CT), Creativity (CR), Communication (CM), Collaboration (CL), Curiosity (CU), Ethics (ET), Courage (CO), Resilience (RS), Leadership (LE), Mindfulness (MN), Meta-Cognition (MT), Growth Mindset (GR)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Insert Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eSignificant SEM paths depend heavily on the competency and outcome in question. In general, Critical Thinking, Communication, Curiosity, Resilience, Leadership, and Growth Mindset were the competencies most present and significant across all three academic outcomes for both time periods one and two. In general, Collaboration and Ethics were not a significant pathway. Mindfulness was present as a significant predictor, but was never robust to a correction for multiple comparisons. Meta-cognition was nowhere significant in the SEM models. Our \u0026ldquo;Δ Comp\u0026rdquo; variable, assess whether the post-test competency direct effect is significant after already accounting for the pre- and post-test effects of the same competency. That is to say, it represents a change in the competency and its relationship to the academic outcomes. Only four competencies (Collaboration, Communication, Curiosity, and Growth Mindset were present as a change in their competency, but they were not robust to a correction for multiple comparisons.\u003c/p\u003e \u003cp\u003eOther moderating variables were also significant. Students\u0026rsquo; pre-test academic outcomes were unsurprisingly always predictive of their post-test scores. Male students consistently scored lower in English. Likewise, there were frequently difference across average scores by student grade-level, which was only included as a control. The number of years a student was enrolled in the school was robust and predictive for math outcomes, and some evidence for science, but not for English.\u003c/p\u003e \u003cp\u003eOverall fit statics indicated that the SEM models fit best when examining English as an academic outcome with all 12 competencies demonstrating good fit. Model fit for Critical Thinking, Communication, Curiosity and Growth Mindset and Math was poor, while the other competencies were good. Likewise, model fit for Curiosity and Meta-Cognition and Science was adequate, while the rest were good.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe findings from this study have numerous contributions to the field of Social and Emotional Learning (SEL). Consistent with the previously cited research from the OECD and academic research, our findings confirm there is a positive and significant relationship between academic and non-academic outcomes. Our research advances the theory building and research by further clarifying the nature of expected relationships through disaggregation of these claims by subject (math, English, or science) and the 12 competencies measured by the CC-21. Moreover, our research goes one step further by being able to connect the \u003cem\u003echanges\u003c/em\u003e in competencies with the \u003cem\u003echanges\u003c/em\u003e in academic outcomes as well. Large-scale surveys like the OECD, while robust in terms of sample size and representative samples of students within countries are only able to measure students\u0026rsquo; outcomes at a single-point in time, where year-over-year comparisons have many confounding variables. This study, while limited in scope of a single international school, enables a deep investigation of the relationship of 21st Century Competencies and academic outcomes.\u003c/p\u003e \u003cp\u003eThe findings underscore the critical role of 21st Century Competencies in fostering academic and personal success. Integrating SEL into curricula enables students to develop skills that extend beyond academics, preparing them for future challenges. Likewise, this research confirms the belief that these competencies can be taught given that the number of years a student is enrolled in their school which integrates SEL is in fact predictive of the outcomes. Understanding the nature of SEL programs can mitigate disparities in competency development, particularly among disadvantaged students or groups with known-demographic differences. By focusing on competencies like emotional regulation and perseverance, schools can promote equitable academic outcomes and social mobility (OECD, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Future research using the CCI-21 or other measures would benefit from integrating additional demographic moderators like wealth or other outcomes like health measures at multiple time points, which was not available here.\u003c/p\u003e \u003cp\u003eTools like the CCI-21 provide educators with actionable insights by disaggregating what we mean by 21st Century Competencies to enable tailored interventions to meet individual student needs (Cipriano \u0026amp; McCarthy, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).As thoroughly discussed by Fadel et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), this is not a trade-off between teaching knowledge \u003cem\u003eor\u003c/em\u003e 21st Century Competencies, rather the art of teaching and learning becomes how to teach 21st Century Competencies \u003cem\u003ewithin\u003c/em\u003e and \u003cem\u003ethrough\u003c/em\u003e knowledge dimensions which remain integral.\u003c/p\u003e \u003cp\u003eThis research argues that policymakers should continue to prioritize the implementation of SEL frameworks within national education systems. While schools such as the one that participated in this study are becoming increasingly more popular and frequent, they are often exceptions rather than the norm of educational institutions. Policy makers should be aware of how private educational institutions like this one are moving ahead to integrate 21st century competencies into their curriculums, which further underscores the need for system-level change to promote these holistic models.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe integration of 21st Century Competencies into education systems represents a paradigm shift toward holistic development. By fostering social and emotional skills alongside cognitive abilities, schools can better prepare students for the demands of the modern world. While challenges in measurement and implementation persist, this study contributes to the growing body of evidence supporting SEL\u0026rsquo;s transformative potential. Future research should continue to explore the nuanced relationships between specific competencies and academic outcomes, informing targeted and effective educational practices.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eNo funding was provided\u003c/p\u003e\n\u003cp\u003eClinical trial number: not applicable\u003c/p\u003e\n\u003cp\u003eEthics, Consent to Participate, and Consent to Publish declarations: The need for ethical approval was waived off by the ethical committee of BE-LPI because of this study involved the secondary analysis of anonymized data provided by the data controller to the research team, acting as data processors. The data were originally collected in accordance with relevant ethical standards, and no new data collection or direct interaction with human participants took place. Informed consent was obtained from all individual participants involved in the study. No declarations are included, so no consent is required.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eRoberson: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Supervision, Validation, Writing \u0026ndash; original, review, \u0026amp; editing; Horvathova: Funding acquisition, Resources, Writing \u0026ndash; review \u0026amp; editing\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe data that support the findings of this study are not available given restrictions apply to the availability of these data, which were used under licence for the current study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlmulla MA. Constructivism learning theory: A paradigm for students\u0026rsquo; critical thinking, creativity, and problem solving to affect academic performance in higher education. 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The Guilford Press; 2015. pp. 3\u0026ndash;19.\u003c/span\u003e\u003c/li\u003e\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":"","lastPublishedDoi":"10.21203/rs.3.rs-6326658/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6326658/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe demands of the 21st century like technological advancement, evolving labor markets, and interconnectedness, highlight the necessity for education systems to emphasize both traditional knowledge and 21st Century Competencies, including critical thinking, collaboration, creativity, resilience and others. They are increasingly recognized for their role in shaping academic success and personal and professional growth. This study examines the relationship between these competencies and academic performance with international students in a Portuguese school using the Competencies Compound Inventory (CCI-21) developed by Beyond Education. A pre- and post-test design with Structural Equation Modeling (SEM) investigates the direct and indirect effects of these competencies on Math, Science, and English outcomes. Findings demonstrate a clear link between 21st Century Competencies and academic outcomes and contribute to a growing evidence base about unpacking specific competencies along with socio-demographic variables. Results inform curriculum and instruction and educational policy to promote equity and holistic development.\u003c/p\u003e","manuscriptTitle":"Linking 21st Century Competencies to Academic Outcomes in Portugal","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-04 08:42:48","doi":"10.21203/rs.3.rs-6326658/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":"d0dc7e32-5c30-48b0-8b79-0a8130ea79bb","owner":[],"postedDate":"July 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-28T09:54:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-04 08:42:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6326658","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6326658","identity":"rs-6326658","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}