Path modeling of factors that predict self-regulated learning: Case Study of a Public University in Nigeria

Jumoke I. Oladele

doi:10.24310/ijne.13.2024.19607

作者

Jumoke I. Oladele University of Johannesburg 南非

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https://doi.org/10.24310/ijne.13.2024.19607

关键词:

Path modeling, academic success, higher education, self-regulated learning, structural equation modeling, technology

摘要

Students can encounter significant challenges when transitioning from high school to university. Students must possess the necessary skills to adjust to the self-directed learning atmosphere of the university, however frequently lack the ability to take responsibility for their own learning. This study employs path-modeling techniques to investigate and analyze the multifaceted relationships between various factors, that can predict self-regulated learning as they impact learners' academic achievements in higher education settings, as informed by an extensive review of existing literature. The population for this study were university undergraduates using a researcher-designed questionnaire for data collection. The data collected was modelled reflectively using partial least squares structural equation modelling (PLS-SEM). Results show that the measurement model assessment showed strong reliability and convergent validity of the latent constructs. However, only technology significantly predicted self-regulated learning as contributing to students' academic success in higher education. The findings from this study contribute significantly to understanding the nuanced pathways through which various learning indicators interact to predict students' self-regulation as influencing students' academic performance in the higher education space. Insights gained from the analysis offer valuable implications for relevant stakeholders aimed at fostering properly tailored conduct that enhances students' academic success in higher education.

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参考

Aletan, S. (2022). Academic Performance in Online Classes of Undergraduates in Education: A Descriptive Study in Africa. International Journal of Educational Excellence, 8(1), 45-64. https://doi.org/10.18562/IJEE.073

Amadioha, S. W. (2009). The importance of instructional materials in our schools an overview. New Era Research Journal of Human, Educational and Sustainable Development, 2(3), 4-9. https://bit.ly/4c55WB9

Araka, E., Maina, E., Gitonga, R., & Oboko, R. (2020). Research trends in measurement and intervention tools for self-regulated learning for e-learning environments—systematic review (2008–2018). Research and Practice in Technology Enhanced Learning, 15, 1-21. https://doi.org/10.1186/s41039-020-00129-5

Ayanwale, M. A., & Ndlovu, M. (2024). Investigating factors of students' behavioral intentions to adopt chatbot technologies in higher education: Perspective from expanded diffusion theory of innovation. Computers in Human Behavior Reports, 100396. https://doi.org/10.1016/j.chbr.2024.100396

Binagwaho, A., Bonciani Nader, H., Brown Burkins, M., Davies, A., Hessen, D. O., Mbow, C., ... & Tong, S. (2022). Knowledge-driven actions: transforming higher education for global sustainability: independent expert group on the universities and the 2030 agenda. UNESCO Publishing. https://doi.org/10.54675/YBTV1653

Binu, P. M. (2016). Self-regulation: Strategies for Lifelong Independent Learning. Vital Issues in English Language Teaching: Papers in Honour of Professor ZN Patil, 132-141. https://bit.ly/48JUkAK

Chankseliani, M., & McCowan, T. (2021). Higher education and the sustainable development goals. Higher Education, 81(1), 1-8. https://doi.org/10.1007/s10734-020-00652-w

Christison, C. (2013). The Benefits of Participating in Extracurricular Activities. BU Journal of Graduate Studies in Education, 5(2), 17-20.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.

Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Routledge.

Dash, G., & Paul, J. (2021). CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting. Technological Forecasting and Social Change, 173, 121092. https://doi.org/10.1016/j.techfore.2021.121092

De Corte, E. (2012). Constructive, self-regulated, situated, and collaborative learning: An approach for the acquisition of adaptive competence. Journal of Education, 192(2-3), 33-47. https://doi.org/10.1177/0022057412192002-307

Delfino, M., Dettori, G., & Persico, D. (2008). Self‐regulated learning in virtual communities. Technology, Pedagogy and Education, 17(3), 195-205.

El-Azar, D. (2022). 4 trends that will shape the future of higher education. February, World Economic Forum. https://bit.ly/3wJI6dS

Elias, M. J. (2019). Helping Students Develop Self-Regulation: Guiding students to create an ongoing cycle of growth in self-regulation starts with having them set explicit goals for themselves. Edutopia https://www.edutopia.org/article/helping-students-develop-self-regulation

Etkin, J. (2018). Understanding Self-Regulation in Education. BU Journal of Graduate Studies in Education, 10(1), 35-39. https://files.eric.ed.gov/fulltext/EJ1230272.pdf

Forsyth, S. B. (2023). What Is Variance-Based Research? October, 6. Medium. https://bit.ly/3VcQDAn

Ginosyan, H., Tuzlukova, V., & Ahmed, F. (2020). An investigation into the role of extracurricular activities in supporting and enhancing students' academic performance in tertiary foundation programs in oman. Theory and Practice in Language Studies, 10(12), 1528-1534.

Grosemans, I., Coertjens, L., & Kyndt, E. (2017). Exploring learning and fit in the transition from higher education to the labour market: A systematic review. Educational Research Review, 21, 67-84. https://doi.org/10.1016/j.edurev.2017.03.001

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate data analysis (7th ed.). Prentice-Hall Inc. https://digitalcommons.kennesaw.edu/facpubs/2925/

Hair, J.F., Ringle, C.M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. The Journal of Marketing Theory and Practice, 19(2), 139-152. https://doi.org/10.2753/MTP1069-6679190202

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019a). Multivariate data analysis (8th ed.). Cengage Learning. https://bit.ly/3wMG24U

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019b). When to use and how to report the results of PLS-SEM. European business review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203

Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., Ray, S., ... & Ray, S. (2021). An introduction to structural equation modeling. Partial least squares structural equation modeling (PLS-SEM) using R: a workbook, 1-29. Classroom Companion: Business. Springer, Cham. https://doi.org/10.1007/978-3-030-80519-7_1

Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., Ketchen, D. J., Hair, J. F., Hult, G. T. M., and Calantone, R. J. 2014. Common Beliefs and Reality about Partial Least Squares: Comments on Rönkkö & Evermann (2013), Organizational Research Methods, 17(2): 182-209. https://doi.org/10.1177/1094428114526928

Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: updated guidelines. Industrial management & data systems, 116(1), 2-20. https://doi.org/10.1108/IMDS-09-2015-0382

Henseler, J. (2017). Partial least squares path modeling. Advanced methods for modeling markets, 361-381. https://doi.org/10.1007/978-3-319-64069-3_2

Higgins, N. L., Rathner, J. A., & Frankland, S. (2023). Development of self-regulated learning: a longitudinal study on academic performance in undergraduate science. Research in Science & Technological Education, 41(4), 1242-1266.

Jin, S. H., Im, K., Yoo, M., Roll, I., & Seo, K. (2023). Supporting students’ self-regulated learning in online learning using artificial intelligence applications. International Journal of Educational Technology in Higher Education, 20(1), 1-21. https://doi.org/10.1186/s41239-023-00406-5

Karlen, Y., & Hertel, S. (2024). Inspiring self-regulated learning in everyday classrooms: teachers’ professional competences and promotion of self-regulated learning. Unterrichtswissenschaft, 1-13. https://doi.org/10.1007/s42010-024-00196-3

Khan, A., Egbue, O., Palkie, B., & Madden, J. (2017). Active learning: Engaging students to maximize learning in an online course. Electronic Journal of e-learning, 15(2), pp107-115. https://search.informit.org/doi/abs/10.3316/ielapa.313660196196001

Khiat, H. V., S. (2022). A self-regulated learning management system: Enhancing performance, motivation and reflection in learning. Journal of University Teaching & Learning Practice, 19(2), 43-59. https://doi.org/10.53761/1.19.2.4

Kurt, S. (2023). Self-Regulated Learning: What It Is, Why It Is Important and Strategies for Implementing It. Educational Technology Consulting Services. https://educationaltechnology.net/self-regulated-learning-what-it-is-why-it-is-important-and-strategies-for-implementing-it/

Laal, M., & Laal, M. (2012). Collaborative learning: what is it?. Procedia-Social and Behavioral Sciences, 31, 491-495. https://doi.org/10.1016/j.sbspro.2011.12.092

Landavere, M., & Mateik, D. (1999, November). Training undergraduates to support technology in the classroom. In Proceedings of the 27th annual ACM SIGUCCS conference on user services: Mile high expectations (pp. 140-143). https://doi.org/10.1145/337043.337128

Latif, K.F. (2024). Understanding R Square, F Square, and Q Square using SMART-PLS. https://bit.ly/49TljLp

Lawal, I. (2022). Leveraging Technology in Tertiary Institutions will enhance quality learning. September, The Guardian. https://bit.ly/3veq1nO

Lodge, J. M., Panadero, E., Broadbent, J., & de Barba, P., G. (2018). Supporting self-regulated learning with learning analytics. In Learning analytics in the classroom (pp. 45-55). Routledge.

Maheta, D. (2022). Structural Model Assessment in SmartPLS-4. September 10, YouTube Video. https://youtu.be/3HbLcvcVJLQ?si=HKWOVMpLowmeMCnh

McCombs, B. (2012). Developing responsible and autonomous learners: A key to motivating students. American Psychological Association. http://www. apa. org/education/k12/learners. aspx.

Mebert, L., Barnes, R., Dalley, J., Gawarecki, L., Ghazi-Nezami, F., Shafer, G., ... & Yezbick, E. (2020). Fostering student engagement through a real-world, collaborative project across disciplines and institutions. Higher Education Pedagogies, 5(1), 30-51. https://doi.org/10.1080/23752696.2020.1750306

Moohr, M. L., Balint-Langel, K., Taylor, J. C., & Rizzo, K. L. (2021). Practicing academic independence: self-regulation strategies for students with emotional and behavioral disorders. Beyond Behavior, 30(2), 85-96. https://doi.org/10.1177/10742956211020666

Mugimu, C. B. (2021). Higher Education Institutions (HEIs) in Africa embracing the “new normal” for knowledge production and innovation: Barriers, realities, and possibilities. In Higher Education- New Approaches to Accreditation, Digitalization, and Globalization in the Age of Covid. IntechOpen. https://doi.org/10.5772/intechopen.101063

Odum, M., Meaney, K., & Knudson, D. V. (2021). Active learning classroom design and student engagement: An exploratory study. Journal of Learning Spaces, 10(1), 27-42. https://files.eric.ed.gov/fulltext/EJ1293141.pdf

Oladele, J. I., & Ndlovu, M. (2023). Digitising Standardised Educational Assessment in Africa Using Computerised Adaptive Testing: Transdisciplinary Framework for Action. In Impact of Disruptive Technologies on the Socio-Economic Development of Emerging Countries (pp. 104-117). IGI Global. https://doi.org/10.4018/978-1-6684-6873-9.ch007

Oladele, J. I., Ndlovu, M., Spangenberg, E. D., Daramola, D. S., & Obimuyiwa, G. A. (2024). Transitioning to Problem-Based Learning in Higher Education: Opportunities for Producing 21st-Century Pre- Service Teachers in Sub-Saharan Africa. Kurdish Studies, 12(2), 609-626. https://kurdishstudies.net/menu-script/index.php/KS/article/view/1838/1290

Olutola, A. T., & Olatoye, R. A. (2020). Enhancing quality of education in the university system: A study of Nigerian education system. Asian Journal of Assessment in Teaching and Learning, 10(2), 55- 61. https://doi.org/10.37134/ajatel.vol10.2.6.2020

Ott, C., Robins, A., Haden, P., & Shephard, K. (2015). Illustrating performance indicators and course characteristics to support students’ self-regulated learning in CS1. Computer Science Education, 25(2), 174-198.

Ozhiganova, G. V. (2018). Self-regulation and self-regulatory capacities: components, levels, models. RUDN Journal of Psychology and Pedagogics, 15(3), 255-270. https://doi.org/10.22363/2313-1683-2018-15-3-255-270

Panadero, E. (2017). A Review of Self-regulated Learning: Six Models and Four Directions for Research [Review]. Frontiers in Psychology, 8. https://doi.org/10.3389/fpsyg.2017.00422

Peel, K. (2019). The Fundamentals for Self-Regulated Learning: A Framework to Guide Analysis and Reflection. Educational Practice and Theory, 41, 23-49. https://doi.org/10.7459/ept/41.1.03

Persico, D. S., K. & Steffens, K. (2017). Self-Regulated Learning in Technology Enhanced Learning Environments. In Technology Enhanced Learning (pp. 115-126).

https://doi.org/10.1007/978-3-319-02600-8_11

Pluck, G., & Johnson, H. L. (2011). Stimulating curiosity to enhance learning. GESJ: Education Sciences and Psychology, 2.

https://www.gesj.internet-academy.org.ge/en/list_artic_en.php?b_sec=edu&issue=2011-12

Portana, H. V., Fronda, J. G., Policarpio, D. G. T., Rigat, K. A. R. C., & Llames, G. A. (2021). Effectiveness and Acceptability of Instructional Materials in the Enhancement of Students’ Academic Achievement. International Journal of Advanced Engineering, Management and Science, 7(1). https://doi.org/10.22161/ijaems.71.2

Puustinen, M., & Pulkkinen, L. (2001). Models of Self-regulated Learning: A review. Scandinavian Journal of Educational Research, 45(3), 269-286. https://doi.org/10.1080/00313830120074206

Quick, J., Motz, B., Israel, J., & Kaetzel, J. (2020, March). What college students say, and what they do: aligning self-regulated learning theory with behavioral logs. In Proceedings of the tenth international conference on learning analytics & knowledge (pp. 534-543). https://doi.org/10.1145/3375462.3375516

Ringle, Christian M., Wende, Sven, & Becker, Jan-Michael. (2024). SmartPLS 4. Monheim am Rhein: SmartPLS. https://www.smartpls.com

Sangaire, E. M. (2012). Self-regulation and cultural orientation on the academic achievement of university students on distance education in Kampala, Uganda. A PhD Dissertation http://hdl.handle.net/20.500.12306/9299

Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural equation modeling. In Handbook of market research (pp. 587-632). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-05542-8_15-1

Shuy, T. O. T. s. (2010). Self-regulated learning. TEAL Center Fact Sheet, 3. The Teaching Excellence in Adult Literacy (TEAL) Center, US Department of Education. https://lincs.ed.gov/sites/default/files/3_TEAL_Self%20Reg%20Learning.pdf

SmartPLS (2024). Fit Measures in SmartPLS. https://www.smartpls.com/documentation/algorithms-and-techniques/model-fit/

Taranto, D., & Buchanan, M. (2020). Sustaining Lifelong Learning: A Self-Regulated Learning (SRL) Approach. Discourse and Communication for Sustainable Education, 11, 5-15. https://doi.org/10.2478/dcse-2020-0002

Timotheou, S., Miliou, O., Dimitriadis, Y., Sobrino, S. V., Giannoutsou, N., Cachia, R., ... & Ioannou, A. (2023). Impacts of digital technologies on education and factors influencing schools' digital capacity and transformation: A literature review. Education and information technologies, 28(6), 6695-6726. https://doi.org/10.1007/s10639-022-11431-8

Torrano Montalvo, F., & González Torres, M. (2004). Self-regulated learning: Current and future directions. J. Fuente, M. A. Eissa (Eds.). In International Handbook on applying self-regulated learning in different Education & Psychology. https://bit.ly/48LsuEe

United Nations (2018). Transforming the Future. Anticipation in the 21st Century. UNESCO, Routledge.

United Nations (2022). The Role of Higher Education Institutions in the Transformation of Future-Fit Education. September, Academic Impact. https://bit.ly/43iCdAz

Virtanen, P., Niemi, H., & Nevgi, A. (2017). Active learning and self-regulation enhance student teachers' professional competences. Australian Journal of Teacher Education (Online), 42(12), 1-20. http://ro.ecu.edu.au/ajte/vol42/iss12/1

Wang, L. (2021). The role of students’ self-regulated learning, grit, and resilience in second language learning. Frontiers in psychology, 12, 800488. https://doi.org/10.3389/fpsyg.2021.800488

Winne, P. H., & Perry, N. E. (2000). Measuring self-regulated learning. In Handbook of self-regulation (pp. 531-566). Elsevier.

Xu, L., Duan, P., Padua, S. A., & Li, C. (2022). The impact of self-regulated learning strategies on academic performance for online learning during COVID-19. Frontiers in Psychology, 13, 1047680.

Yan, Z., & Carless, D. (2022). Self-assessment is about more than self: the enabling role of feedback literacy. Assessment & Evaluation in Higher Education, 47(7), 1116-1128. https://doi.org/10.1080/02602938.2021.2001431

Yin R. K. (2014). Case study research and applications: Design and methods (6th ed.). SAGE Publications.

Zhao, S. R., & Cao, C. H. (2023). Exploring Relationship Among Self-Regulated Learning, Self-Efficacy and Engagement in Blended Collaborative Context. SAGE Open, 13(1). https://doi.org/10.1177/21582440231157240

Zimmerman, B. J. (2015). Self-Regulated Learning: Theories, Measures, and Outcomes. In J. D. Wright (Ed.), International Encyclopedia of the Social & Behavioral Sciences (Second Edition) (pp. 541- 546). Elsevier. https://doi.org/10.1016/B978-0-08-097086-8.26060-1