Journal of Uludag University Faculty of Education 2667-6788 Bursa Uludağ University 10.19171/uefad.1717697 Measurement Theories and Applications in Education and Psychology National and International Success Comparisons Measurement and Evaluation in Education (Other) Eğitimde ve Psikolojide Ölçme Teorileri ve Uygulamaları Ulusal ve Uluslararası Başarı Karşılaştırmaları Eğitimde Ölçme ve Değerlendirme (Diğer) Examining Students’ Socio-Emotional Skills Profiles During the Early Post-COVID-19 Period and Their Relationships with Self-Directed Learning Self-Efficacy Öğrencilerin COVID-19 Sonrası Erken Dönemdeki Sosyo-Duygusal Beceri Profilleri ve Öz-Yönelimli Öğrenme Öz-Yeterliği ile İlişkileri https://orcid.org/0000-0002-8565-215X Teke Bedirhan KİLİS 7 ARALIK ÜNİVERSİTESİ 04 30 2026 39 1 160 177 06 11 2025 11 23 2025 Copyright © 1986, Journal of Uludag University Faculty of Education 1986 Journal of Uludag University Faculty of Education

This study, consistent with Self-Determination Theory, aims to determine students’ socio-emotional skill profiles and the corresponding levels of self-efficacy for self-directed learning. For the analyses, data from 7206 Turkish students in the Program for International Student Assessment (PISA) 2022 were used to conduct a Latent Profile Analysis. The results revealed that the students in this study could be classified into five distinct profiles based on their socio-emotional skills. In particular, the profiles differed statistically significantly in self-efficacy for self-directed learning; in particular, the self-directed learning self-efficacy levels of those in the optimal need satisfaction profile were higher than those in the other profiles. Despite this, 64% of the participants have shown below-average confidence in self-directed learning. These findings not only enhance our understanding of students' socio-emotional development but also highlight the need for educational interventions that prioritize the holistic development of students' socio-emotional skills.

Bu çalışma, öz-belirleme teorisi ile tutarlı olarak, öğrencilerin sosyo-duygusal beceri profillerini ve öz-yönelimli öğrenme için öz-yeterlik düzeylerini belirlemeyi amaçlamaktadır. Analizler için 7206 Türk öğrenciye ait 2022 Uluslararası Öğrenci Değerlendirme Programı (PISA) verisi kullanılarak Örtük Profil Analizi yapılmıştır. Sonuçlar, bu çalışmadaki öğrencilerin sosyo-duygusal becerileri açısından beş özel profilde sınıflandırılabileceğini ortaya koymuştur. Özellikle, profiller öz-yönelimli öğrenmeye yönelik öz-yeterlik açısından istatistiksel olarak anlamlı bir şekilde farklılaşmıştır; optimal ihtiyaç tatmini profilinde yer alanların öz-yönelimli öğrenme öz-yeterlik düzeyleri diğer profillere kıyasla daha yüksektir. Buna rağmen, katılımcıların %64'ünün öz-yönelimli öğrenme konusunda ortalamanın altında güvene sahip olduğu ortaya çıkmıştır. Bu bulgular, öğrencilerin sosyo-duygusal gelişimine ilişkin anlayışımızı geliştirmekle kalmayıp, aynı zamanda öğrencilerin sosyo-duygusal becerilerinin bütünsel gelişimine öncelik veren eğitim müdahalelerine duyulan acil ihtiyacı da vurgulamaktadır.

 Latent profile analysis Self-determination theory Self-directed learning Self-directed learning self-efficacy Socio-emotional skills Örtük profil analizi Öz-belirleme kuramı Öz-yönelimli öğrenme Öz-yönelimli öğrenme öz-yeterliği Sosyo-duygusal beceriler Abrahams, L., Pancorbo, G., Primi, R., Santos, D., Kyllonen, P., John, O. P., & De Fruyt, F. (2019). Social-emotional skill assessment in children and adolescents: Advances and challenges in personality, clinical, and educational contexts. Psychological Assessment, 31(4), 460-473. https://doi.org/10.1037/pas0000591 Asparouhov, T., & Muthén, B. (2014). Auxiliary variables in mixture modeling: Three-step approaches using M plus. Structural equation modeling: A Multidisciplinary Journal, 21(3), 329-341. https://doi.org/10.1080/10705511.2014.915181 Baars, M., Wijnia, L., & Paas, F. (2017). The association between motivation, affect, and self-regulated learning when solving problems. Frontiers in Psychology, 8, 1346. https://doi.org/10.3389/fpsyg.2017.01346 Bae, S. H., Jo, M. G., & Han, S. I. (2024). Unmasking Student Dynamics: The impact of COVID-19 on social-emotional development and learning engagement. IJREE–International Journal for Research on Extended Education, 11(2), 46-71. https://doi.org/10.3224/ijree.v11i2.05 Berg, J., Osher, D., Same, M. R., Nolan, E., Benson, D., & Jacobs, N. (2017). Identifying, defining, and measuring social and emotional competencies. American Institutes for Research. Bonk, C. J., & Lee, M. M. (2017). Motivations, achievements, and challenges of selfdirected informal learners in open educational environments and MOOCs. Journal of Learning for Development, 4(1). https://doi.org/10.56059/jl4d.v4i1.195 Castro-Kemp, S., Palikara, O., Gaona, C., Eirinaki, V., & Furlong, M. J. (2019). The role of psychological sense of school membership and postcode as predictors of profiles of socio-emotional health in primary school children in England. School Mental Health, 12, 284-295. https://doi.org/10.1007/s12310-019-09349-7 Cerutti, J., Burt, K. B., Moeller, R. W., & Seehuus, M. (2024). Declines in social–emotional skills in college students during the COVID-19 pandemic. Frontiers in Psychology, 15, 1392058. https://doi.org/10.3389/fpsyg.2024.1392058 Chen, C. C., Xu, Y., LoCasale-Crouch, J., Xia, Y., Rudasill, K., Xie, L., ... & Askue-Collins, J. (2024). Social–Emotional Profiles of Preschool Children: An Investigation of Demographic Disparities and Intersectionality. International Journal of Environmental Research and Public Health, 21(8), 1100. https://doi.org/10.3390/ijerph21081100 Chernyshenko, O. S., Kankaraš, M., and Drasgow, F. (2018). Social and emotional skills for student success and well-being. OECD Publishing. Collie, R. J., Martin, A. J., Nassar, N., & Roberts, C. L. (2019). Social and emotional behavioral profiles in kindergarten: A population-based latent profile analysis of links to socio-educational characteristics and later achievement. Journal of Educational Psychology, 111(1), 170–187. https://doi.org/10.1037/edu0000262 Deming, D. J. (2017). The growing importance of social skills in the labor market. Quarterly Journal of Economics, 132(4), 1593–1640. https://doi.org/10.1093/qje/qjx022 Demuyakor, J. (2020). Coronavirus (COVID-19) and online learning in higher institutions of education: A survey of the perceptions of Ghanaian international students in China. Online Journal of Communication and Media Technologies, 10(3), e202018. https://doi.org/10.29333/ojcmt/8286 Doctoroff, G. L., P. H. Fisher, B. M. Burrows, and M. T. Edman. (2016). Preschool Children’s Interest, Social-emotional Skills, and Emergent Mathematics Skills. Psychology in the Schools, 53(4), 390-403. https://doi.org/10.1002/pits.21912 Ferguson, S.L., & Hull, D.M. (2019). Exploring science career interest: Latent profile analysis of high school occupational preferences for science. Journal of Career Development, 46(5), 583-598. https://doi.org/10.1177/0894845318783873 Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education. McGraw Hill. Gamboa, V., Rodrigues, S., Bértolo, F., Marcelo, B., & Paixão, O. (2023). Socio-emotional skills profiles and their relations with career exploration and perceived parental support among 8th grade students. Frontiers in Psychology, 14, 1214395. https://doi.org/10.3389/fpsyg.2023.1214395 Goh, H. H., Wong, H. M., & Kwek, D. (2023). Home-based learning during school closure in Singapore: perceptions from the language classrooms. Educational Research for Policy and Practice, 22(3), 367-387. https://doi.org/10.1007/s10671-023-09329-4 Hawkins, J. D., Catalano, R. F., Arthur, M. W., Egan, E., Brown, E. C., Abbott, R. D., & Murray, D. M. (2008). Testing communities that care: The rationale, design and behavioral baseline equivalence of the community youth development study. Prevention Science, 9(3) 178-190. https://doi.org/10.1007/s11121-008-0092-y Hipp, J., & Bauer, D. (2006). Local solution in the estimation of growth mixture models. Psychological Methods, 11, 36-53. Huang, C., & Zeng, X. (2023). Social and emotional development of disadvantaged students and its relationship with academic performance: Evidence from China. Frontiers in Psychology, 14, 1170656. https://doi.org/10.3389/fpsyg.2023.1170656 Jandigulov, A., Abdallah, A. K., Tikhonova, Y., & Gorozhanina, E. (2023). Management and leadership in online learning. Education and Information Technologies, 28(10), 13423-13437. https://doi.org/10.1007/s10639-023-11699-4 John, O., & De Fruyt, F. (2015). Framework for the longitudinal study of social and emotional skills in cities. OECD Publishing. John, O., L. Naumann & C. Soto (2008). Paradigm shift to the integrative Big-Five trait taxonomy: History, measurement, and conceptual issues. In John, O., R. Robins and L. Pervin (Eds.), Handbook of Personality: Theory and Research (pp 114-158). The Guilford Press. Kankaraš, M., & Suarez-Alvarez, J. (2019). Assessment framework of the OECD study on social and emotional skills. OECD education working papers. OECD Publishing. Knowles M. S. (1975). Self-directed learning: A guide for learners and teachers. Association Press. Lemmo, A., & Maffia, A. (2022). High school students' use of digital general resources during lockdown. European Journal of Science and Mathematics Education, 10(1), 139-153. https://doi.org/10.30935/scimath/11465 Lippman, L.H., R. Ryberg, R. Carney, & K.A. Moore. (2015). Key “soft skills” that foster youth workforce success: Toward a consensus across fields. Child Trends. Liu, Q., & Lin, D. (2024). The impact of distance education on the socialization of college students in the Covid-19 era: Problems in communication and impact on mental health. BMC Medical Education, 24(1), 575. https://doi.org/10.1186/s12909-024-05551-7 Liu, T. H., & Sullivan, A. M. (2021). A story half told: a qualitative study of medical students’ self-directed learning in the clinical setting. BMC Medical Education, 21, 494. https://doi.org/10.1186/s12909-021-02913-3 Lo, Y., Mendell, N. R., & Rubin, D. B. (2001). Testing the number of components in a normal mixture. Biometrika, 88(3), 767-778. https://doi.org/10.1093/biomet/88.3.767 Longhi, M.T., Behar, P.A., Machado, L.S.R. (2024). Socio-Affective competence in virtual learning environments: A view from the empathetic subject. In Guralnick, D., Auer, M.E., Poce, A. (Eds.), Creative Approaches to Technology-Enhanced Learning for the Workplace and Higher Education (pp. 350-362). Springer. https://doi.org/10.1007/978-3-031-73427-4_34 Lubke, G. H., & Muthén, B. (2005). Investigating population heterogeneity with factor mixture models. Psychological Methods, 10(1), 21-39. https://doi.org/10.1037/1082-989X.10.1.21 Luo, Y., Lin, J., & Yang, Y. (2021). Students’ motivation and continued intention with online self-regulated learning: A self-determination theory perspective. Zeitschrift für Erziehungswissenschaft, 24(6), 1379-1399. https://doi.org/10.1007/s11618-021-01042-3 Marsh, H. W., Lüdtke, O., Trautwein, U., & Morin, A. J. (2009). Classical latent profile analysis of academic self-concept dimensions: Synergy of person-and variable-centered approaches to theoretical models of self-concept. Structural Equation Modeling, 16(2), 191-225. https://doi.org/10.1080/10705510902751010 Ministry of National Education (MoNE). (2024). PISA 2022 Türkiye raporu. https://pisa.meb.gov.tr/www/pisa-2022-turkiye-raporu-yayimlandi/icerik/11 Muthen, L. K., & Muthen, B. (2012). 1998-2012. Mplus user’s guide (7th ed.). Muthen&Muthen. Nylund, K.L., Asparouhov, T., & Muthén, B.O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling: A Multidisciplinary Journal, 14(4), 535-569. https://doi.org/10.1080/10705510701575396 Nylund-Gibson, K., Grimm, R. P., & Masyn, K. E. (2019). Prediction from latent classes: A demonstration of different approaches to include distal outcomes in mixture models. Structural equation modeling: A multidisciplinary Journal, 26(6), 967-985. https://doi.org/10.1080/10705511.2019.1590146 Organisation for Economic Co-operation and Development (OECD). (2015). Skills for social progress: The power of social and emotional skills. OECD Skills Studies. OECD Publishing. https://doi.org/10.1787/9789264226159-en Organisation for Economic Co-operation and Development (OECD). (2024a). PISA 2022 technical report. OECD Publishing. https://www.oecd.org/pisa/data/pisa2022technicalreport/ Organisation for Economic Co-operation and Development (OECD). (2024b). PISA 2022 results (Volume V): Learning strategies and attitudes for life. OECD Publishing. https://doi.org/10.1787/c2e44201-en Organisation for Economic Co-operation and Development (OECD). (2024c). Social and emotional skills for better lives: Findings from the OECD survey on social and emotional skills 2023. OECD Publishing. https://doi.org/10.1787/35ca7b7c-en Organisation for Economic Co-operation and Development (OECD). (2021). Beyond academic learning: First results from the survey of social and emotional skills. OECD Publishing. Park, J. M., Seo, H. J., Kim, S. M., Kang, H., & Lee, S. J. (2023). Association between COVID-19-related stress and self-directed learning ability among Korean nursing students. Nurse Education in Practice, 69, 103613. https://doi.org/10.1016/j.nepr.2023.103613 Ponton, M. K., & Dondlinger, M. J. (2022). A socio-cognitive discussion of learning resource selection in self-directed learning. International Journal of Learning and Development, 12(2), 46-56. https://doi.org/10.5296/ijld.v12i2.19924 Primi, R., Santos, D., John, O. P., & de Fruyt, F. (2016). Development of an inventory assessing social and emotional skills in Brazilian youth. European Journal of Psychological Assessment, 32(1), 516. https://doi.org/10.1027/1015-5759/a000343 Robinson, J. D., & Persky, A. M. (2020). Developing self-directed learners. American Journal of Pharmaceutical Education, 84(3), 847512. https://doi.org/10.5688/ajpe847512 Rodriguez-Monge, M., Isabela, I. P., & Chiappelli, F. (2023). CoViD-19 effects on social-emotional development: impact of early intervention. Bioinformation, 19(9), 889-892. 10.6026/97320630019889 Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary educational psychology, 61, 101860. https://doi.org/10.1016/j.cedpsych.2019.101831 Ryan, R. M., Vansteenkiste, M., & Soenens, B. (2019). Reflections on self-determination theory as an organizing framework for personality psychology: Interfaces, integrations, issues, and unfinished business. Journal of Personality, 87(1), 115-145. https://doi.org/10.1111/jopy.12440 Ryan, R.M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. The American Psychologist, 55(1), 68-78. https://doi.org/10.1037/0003-066x.55.1.68 Ryan, R.M., & Deci, E. L. (2019). Chapter four-brick by brick: the origins, development, and future of self-determination theory. In A. J. Elliot (Ed.), Advances in motivation science (pp. 111-156). Elsevier. Saleem, S., Burns, S., & Perlman, M. (2024). Cultivating young minds: Exploring the relationship between child socio-emotional competence, early childhood education and care quality, creativity and self-directed learning. Learning and Individual Differences, 111, 102440. https://doi.org/10.1016/j.lindif.2024.102440 Shal, T. (2024). Parents' perceptions of online learning during covid-19 pandemic: The road ahead. Online Learning, 28(1), 69-86. https://doi.org/10.24059/olj.v28i1.3860 Soto, C. J., Napolitano, C. M., Sewell, M. N., Yoon, H. J., & Roberts, B. W. (2024). Going beyond traits: Social, emotional, and behavioral skills matter for adolescents’ success. Social Psychological and Personality Science, 15(1), 33-45. https://doi.org/10.1177/19485506221127483 Teke, B., & Çalışıcı, H. (2025). Using inquiry-based learning approach in the teaching process of divisibility rules. Asia Pacific Educ. Rev., 26, 519-538. https://doi.org/10.1007/s12564-025-10036-3 The Collaborative for Academic, Social, and Emotional Learning (CASEL). (2020). Casel’s sel framework: What are the core competence areas and where are they promoted? https://casel.org/casel-sel-framework-11-2020/ Thomson, K. C., Guhn, M., Richardson, C. G., Ark, T. K., & Shoveller, J. (2017). Profiles of children's social–emotional health at school entry and associated income, gender and language inequalities: A cross-sectional population-based study in British Columbia, Canada. BMJ open, 7(7), e015353. http://dx.doi.org/10.1136/bmjopen-2016-015353 Tze, V. M., Li, J. C. H., & Daniels, L. M. (2022). Similarities and differences in social and emotional profiles among students in Canada, USA, China, and Singapore: PISA 2015. Research Papers in Education, 37(4), 560-586. https://doi.org/10.1080/02671522.2020.1864760 Vermunt J. K. (2010). Latent class modeling with covariates: Two improved three-step approaches. Political Analysis, 18(4), 450-469. https://doi.org/10.1093/pan/mpq025 Videla, R., Rossel, S., Muñoz, C., & Aguayo, C. (2022). Online mathematics education during the COVID-19 pandemic: Didactic strategies, educational resources, and educational contexts. Education Sciences, 12(7), 492. https://doi.org/10.3390/educsci12070492 Weissberg, R. P., & Cascarino, J. (2013). Academic learning+ social-emotional learning= national priority. Phi Delta Kappan, 95(2), 8-13. https://doi.org/10.1177/003172171309500 Yang, C., Zhu, Y., Jiang, H., & Qu, B. (2021). Influencing factors of self-directed learning abilities of medical students of mainland China: A cross-sectional study. BMJ open, 11(10), e051590. https://doi.org/10.1136/bmjopen-2021-051590 Zhoc, K. C., Chung, T. S., & King, R. B. (2018). Emotional intelligence (EI) and self‐directed learning: Examining their relation and contribution to better student learning outcomes in higher education. British Educational Research Journal, 44(6), 982-1004. https://doi.org/10.1002/berj.3472