Self-Regulated Learning in the Digital Age: A Systematic Review of Strategies, Technologies, Benefits, and Challenges
DOI:
https://doi.org/10.19173/irrodl.v26i2.8119Keywords:
self-regulated learning strategies, self-directed learning strategies, educational technologies, systematic literature reviewAbstract
When students enter higher education, self-regulated learning (SRL) involving goal setting, planning, monitoring, and reflection is crucial for academic success. This study systematically reviews SRL strategies, supporting technologies, and their impacts, especially with the shift to online learning due to the COVID-19 pandemic. Following Kitchenham’s guidelines, 121 articles from ScienceDirect and Scopus were reviewed. Key SRL strategies include goal setting, cognitive and metacognitive processes, time management, self-reflection, help-seeking, and monitoring. Technologies such as learning management systems (LMS), massive open online courses (MOOCs), artificial intelligence (AI), collaborative platforms, and learning analytics support SRL by providing personalized feedback and facilitating autonomous learning. Benefits include improved performance, motivation, and engagement, while challenges involve limited access to digital resources, technical issues, resistance to change, and inadequate instructor training. Addressing these barriers is essential for optimizing SRL implementation, guiding future research and educational practice.
References
Abbasi, S., Ayoob, T., Malik, A., & Memon, S. I. (2020). Perceptions of students regarding e-learning during Covid-19 at a private medical college: Perceptions of students regarding e-learning. Pakistan Journal of Medical Sciences, 36(COVID19-S4), S57–S61. https://doi.org/10.12669/pjms.36.COVID19-S4.2766
Abdullah, S. I. N. W., Arokiyasamy, K., Goh, S. L., Culas, A. J., & Manaf, N. M. A. (2022). University students’ satisfaction and future outlook towards forced remote learning during a global pandemic. Smart Learning Environments, 9, Article 15. https://doi.org/10.1186/s40561-022-00197-8
Abduvakhidov, A. M., Mannapova, E. T., & Akhmetshin, E. M. (2021). Digital development of education and universities: Global challenges of the digital economy. International Journal of Instruction, 14(1), 743–760. https://doi.org/10.29333/iji.2021.14145a
Adnan, M., & Anwar, K. (2020). Online learning amid the COVID-19 pandemic: Students’ perspectives. Journal of Pedagogical Sociology and Psychology, 2(1), 45–51. https://doi.org/10.33902/JPSP.2020261309
Alhalafawy, W. S., & Tawfiq Zaki, M. Z. (2022). How has gamification within digital platforms affected self-regulated learning skills during the COVID-19 pandemic? Mixed-methods research. International Journal of Emerging Technologies in Learning (IJET), 17(6), 123–151. https://doi.org/10.3991/ijet.v17i06.28885
Almaiah, M. A., Al-Khasawneh, A., & Althunibat, A. (2020). Exploring the critical challenges and factors influencing the e-learning system usage during COVID-19 pandemic. Education and Information Technologies, 25(6), 5261–5280. https://doi.org/10.1007/s10639-020-10219-y
Alotumi, M. (2021). EFL college junior and senior students’ self-regulated motivation for improving English speaking: A survey study. Heliyon, 7(4), Article e06664. https://doi.org/10.1016/j.heliyon.2021.e06664
Alqahtani, T., Badreldin, H. A., Alrashed, M., Alshaya, A. I., Alghamdi, S. S., bin Saleh, K., Alowais, S. A., Alshaya, O. A., Rahman, I., Al Yami, M. S., & Albekairy, A. M. (2023). The emergent role of artificial intelligence, natural language processing, and large language models in higher education and research. Research in Social and Administrative Pharmacy, 19(8), 1236–1242. https://doi.org/10.1016/j.sapharm.2023.05.016
Al-Shaye, S. (2021). Digital storytelling for improving critical reading skills, critical thinking skills, and self-regulated learning skills. Kıbrıslı Eğitim Bilimleri Dergisi, 16(4), 2049–2069, https://doi.org/10.18844/cjes.v16i4.6074
Amiruddin, A., Baharuddin, F. R., Takbir, T., Setialaksana, W., & Hasim, M. (2023). Pedagogy-andragogy continuum with cybergogy to promote self-regulated learning: A structural equation model approach. European Journal of Educational Research, 12(2), 811–824. https://doi.org/10.12973/eu-jer.12.2.811
Anthonysamy, L., Ah Choo, K., & Soon Hin, H. (2021). Investigating self-regulated learning strategies for digital learning relevancy. Malaysian Journal of Learning and Instruction, 18(1), 29–64. https://doi.org/10.32890/mjli2021.18.1.2
Apridayani, A., Han, W., & Waluyo, B. (2023). Understanding students’ self-regulated learning and anxiety in online English courses in higher education. Heliyon, 9(6), Article e17469. https://doi.org/10.1016/j.heliyon.2023.e17469
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, Article 6. https://doi.org/10.1186/s41039-020-00129-5
Bacher-Hicks, A., Goodman, J., & Mulhern, C. (2021). Inequality in household adaptation to schooling shocks: Covid-induced online learning engagement in real time. Journal of Public Economics, 193, Article 104345. https://doi.org/10.1016/j.jpubeco.2020.104345
Baek, C., & Doleck, T. (2023). Educational data mining versus learning analytics: A review of publications from 2015 to 2019. Interactive Learning Environments, 31(6), 3828–3850. https://doi.org/10.1080/10494820.2021.1943689
Ballouk, R., Mansour, V., Dalziel, B., McDonald, J., & Hegazi, I. (2022). Medical students’ self-regulation of learning in a blended learning environment: A systematic scoping review. Medical Education Online, 27(1), Article 2029336. https://doi.org/10.1080/10872981.2022.2029336
Bećirović, S., Ahmetović, E., & Skopljak, A. (2022). An examination of students online learning satisfaction, interaction, self-efficacy and self-regulated learning. European Journal of Contemporary Education, 11(1), 16–35. https://doi.org/10.13187/ejced.2022.1.16
Biggs, J. (1999). What the student does: Teaching for enhanced learning. Higher Education Research and Development, 18, 57–75. https://doi.org/10.1080/07294360.2012.642839
Bodily, R., & Verbert, K. (2017). Review of research on student-facing learning analytics dashboards and educational recommender systems. IEEE Transactions on Learning Technologies, 10(4), 405–418. https://doi.org/10.1109/TLT.2017.2740172
Bravo-Agapito, J., Romero, S. J., & Pamplona, S. (2021). Early prediction of undergraduate student’s academic performance in completely online learning: A five-year study. Computers in Human Behavior, 115, Article 106595. https://doi.org/10.1016/j.chb.2020.106595
Briones, M. R., Prudente, M., & Errabo, D. D. (2023). Characteristics of Filipino online learners: A survey of science education students’ engagement, self-regulation, and self-efficacy. Education Sciences, 13(11), Article 1131. https://doi.org/10.3390/educsci13111131
Brusilovsky, P., Somyürek, S., Guerra, J., Hosseini, R., & Zadorozhny, V. (2015). The value of social: Comparing open student modeling and open social student modeling. In F. Ricci, K. Bontcheva, O. Conlan, & S. Lawless (Eds.), User Modeling, Adaptation and Personalization. UMAP 2015 (pp. 44–55). Springer. https://doi.org/10.1007/978-3-319-20267-9_4
Carvalho, A. R., & Santos, C. (2022). Developing peer mentors’ collaborative and metacognitive skills with a technology-enhanced peer learning program. Computers and Education Open, 3, Article 100070. https://doi.org/10.1016/j.caeo.2021.100070
Cervin-Ellqvist, M., Larsson, D., Adawi, T., Stöhr, C., & Negretti, R. (2021). Metacognitive illusion or self-regulated learning? Assessing engineering students’ learning strategies against the backdrop of recent advances in cognitive science. Higher Education, 82(3), 477–498. https://doi.org/10.1007/s10734-020-00635-x
Chauncey, S. A., & McKenna, H. P. (2023). A framework and exemplars for ethical and responsible use of AI Chatbot technology to support teaching and learning. Computers and Education: Artificial Intelligence, 5, Article 100182. https://doi.org/10.1016/j.caeai.2023.100182
Chen, K. Z., & Li, S. C. (2021). Sequential, typological, and academic dynamics of self-regulated learners: Learning analytics of an undergraduate chemistry online course. Computers and Education: Artificial Intelligence, 2, Article 100024. https://doi.org/10.1016/j.caeai.2021.100024
Chen, L. H. (2023). Moving forward: International students’ perspectives of online learning experience during the pandemic. International Journal of Educational Research Open, 5, Article 100276. https://doi.org/10.1016/j.ijedro.2023.100276
Cheng, Z., Zhang, Z., Xu, Q., Maeda, Y., & Gu, P. (2023, October 10). A meta-analysis addressing the relationship between self-regulated learning strategies and academic performance in online higher education. Journal of Computing in Higher Education, 1–30. https://doi.org/10.1007/s12528-023-09390-1
Choong, P. Y. (2020, May 8). COVID-19: Impact on the tertiary education sector in Malaysia. Crisis assessment. Penang Institute. https://penanginstitute.org/wp-content/uploads/2020/05/IMPACT-ON-THE-TERTIARY-EDUCATION-SECTOR-IN-MALAYSIA.pdf
Cook, R., Kay, J., & Kummerfeld, B. (2015). MOOClm: User modelling for MOOCs. In F. Ricci, K. Bontcheva, O. Conlan, & S. Lawless (Eds.), User Modeling, Adaptation and Personalization. UMAP 2015 (pp. 80–91). Springer. https://doi.org/10.1007/978-3-319-20267-9_7
Dai, Y., Liu, A., & Lim, C. P. (2023). Reconceptualizing ChatGPT and generative AI as a student-driven innovation in higher education. Procedia CIRP, 119, 84–90. https://doi.org/10.1016/j.procir.2023.05.002
Darvishi, A., Khosravi, H., Sadiq, S., Gašević, D., & Siemens, G. (2024). Impact of AI assistance on student agency. Computers & Education, 210, Article 104967. https://doi.org/10.1016/j.compedu.2023.104967
Deeva, G., Bogdanova, D., Serral, E., Snoeck, M., & De Weerdt, J. (2021). A review of automated feedback systems for learners: Classification framework, challenges and opportunities. Computers & Education, 162, Article 104094. https://doi.org/10.1016/j.compedu.2020.104094
Domínguez, C., Garcia-Izquierdo, F. J., Jaime, A., Pérez, B., Rubio, A. L., & Zapata, M. A. (2021). Using process mining to analyze time distribution of self-assessment and formative assessment exercises on an online learning tool. IEEE Transactions on Learning Technologies, 14(5), 709–722. https://doi.org/10.1109/TLT.2021.3119224
Doo, M. Y., Zhu, M., & Bonk, C. J. (2023). Influence of self-directed learning on learning outcomes in MOOCs: A meta-analysis. Distance Education, 44(1), 86–105. https://doi.org/10.1080/01587919.2022.2155618
Edisherashvili, N., Saks, K., Pedaste, M., & Leijen, Ä. (2022). Supporting self-regulated learning in distance learning contexts at higher education level: Systematic literature review. Frontiers in Psychology, 12, Article 792422. https://doi.org/10.3389/fpsyg.2021.792422
Elkot, M. A., & Ali, R. (2020). Enhancing self-regulated learning strategy via handheld devices for improving English writing skills and motivation. International Journal of Information and Education Technology, 10(11), 805–812. https://doi.org/10.18178/ijiet.2020.10.11.1462
Faza, A., Santoso, H. B., & Putra, P. O. H. (2024). Navigating online learning challenges and opportunities: Insights from small group of lecturers during pandemic. Procedia Computer Science, 234, 1164–1174. https://doi.org/10.1016/j.procs.2024.03.112
Fleur, D. S., van den Bos, W., & Bredeweg, B. (2023). Social comparison in learning analytics dashboard supporting motivation and academic achievement. Computers and Education Open, 4, Article 100130. https://doi.org/10.1016/j.caeo.2023.100130
Fructuoso, I. N., Robalino, P. E., & Ahmedi, S. (2023). The flexibility of the flipped classroom for the design of mediated and self-regulated learning scenarios. RIED. Revista Iberoamericana de Educación a Distancia, 26(2), 155-173. https://doi.org/10.5944/ried.26.2.36035
Funa, A. A., Gabay, R. A. E., Deblois, E. C. B., Lerios, L. D., & Jetomo, F. G. J. (2023). Exploring Filipino preservice teachers’ online self-regulated learning skills and strategies amid the COVID-19 pandemic. Social Sciences & Humanities Open, 7(1), Article 100470. https://doi.org/10.1016/j.ssaho.2023.100470
Funa, A. A., & Talaue, F. T. (2021). Constructivist learning amid the COVID-19 pandemic: Investigating students’ perceptions of biology self-learning biology modules. International Journal of Learning, Teaching, and Educational Research, 20(3), 250–264. https://doi.org/10.26803/ijlter.20.3.15
Günther, S. A. (2021). The impact of social norms on students’ online learning behavior: Insights from two randomized controlled trials. In M. Scheffel, N. Dowell, S. Joksimovic, & G. Siemens (Chairs), LAK21: 11th International Learning Analytics and Knowledge Conference (pp. 12–21). ACM. https://doi.org/10.1145/3448139.3448141
Guo, J., King, R. B., Ding, Q., & Fan, M. (2022). Measuring and promoting self-regulation for equity and quality of online learning: New evidence from a multi-institutional survey during COVID-19. Education Sciences, 12(7), Article 465. https://doi.org/10.3390/educsci12070465
Gutiérrez-Peláez, M., & Ellis, K. (2020). Aprendizaje intercultural. Collaborative Online International Learning (COIL) Experiences between Universidad del Rosario and the American University in Cairo Egypt. Reflexiones Pedagógicas, 23, 1–7. https://doi.org/10.48713/10336_25855
Habók, A., Oo, T. Z., & Magyar, A. (2024). The effect of reading strategy use on online reading comprehension. Heliyon, 10(2), Article: e24281. https://doi.org/10.1016/j.heliyon.2024.e24281
Han, J., Kim, K. H., Rhee, W., & Cho, Y. H. (2021). Learning analytics dashboards for adaptive support in face-to-face collaborative argumentation. Computers & Education, 163, Article 104041. https://doi.org/10.1016/j.compedu.2020.104041
Heikkinen, S., Saqr, M., Malmberg, J., & Tedre, M. (2023). Supporting self-regulated learning with learning analytics interventions—A systematic literature review. Education and Information Technologies, 28(3), 3059–3088. https://doi.org/10.1007/s10639-022-11281-4
Heirweg, S., De Smul, M., Merchie, E., Devos, G., & Van Keer, H. (2020). Mine the process: Investigating the cyclical nature of upper primary school students’ self-regulated learning. Instructional Science, 48, 337–369. https://doi.org/10.1007/s11251-020-09519-0
Hidayatullah, A., & Csíkos, C. (2023, November 11). Association between psychological need satisfaction and online self-regulated learning. Asia Pacific Education Review, 2023, 1–11. https://doi.org/10.1007/s12564-023-09910-9
HolonIQ. (2022, February 2). Global education economy: 2022 global education outlook. https://www.holoniq.com/notes/2022-global-education-outlook
Howlett, M. A., McWilliams, M. A., Rademacher, K., O’Neill, J. C., Maitland, T. L., Abels, K., Demetriou, C., & Panter, A. T. (2021). Investigating the effects of academic coaching on college students’ metacognition. Innovative Higher Education, 46, 189–204. https://doi.org/10.1007/s10755-020-09533-7
Huang, L., Li, S., Poitras, E. G., & Lajoie, S. P. (2021). Latent profiles of self‐regulated learning and their impacts on teachers’ technology integration. British Journal of Educational Technology, 52(2), 695–713. https://doi.org/10.1111/bjet.13050
Huber, S. G., & Helm, C. (2020). COVID-19 and schooling: Evaluation, assessment and accountability in times of crises—Reacting quickly to explore key issues for policy, practice and research with the school barometer. Educational Assessment, Evaluation and Accountability, 32, 237–270. https://doi.org/10.1007/s11092-020-09322-y
Imhof, M., Worthington, D., Burger, J., & Bellhäuser, H. (2024). Resilience and self-regulated learning as predictors of student competence gain in times of the COVID 19 pandemic–Evidence from a binational sample. Frontiers in Education, 9, Article 1293736. https://doi.org/10.3389/feduc.2024.1293736
Inan-Karagul, B., & Seker, M. (2021, December 16). Improving language learners’ use of self-regulated writing strategies through screencast feedback. Sage Open, 11(4). https://doi.org/10.1177/21582440211064895
Ingkavara, T., Panjaburee, P., Srisawasdi, N., & Sajjapanroj, S. (2022). The use of a personalized learning approach to implementing self-regulated online learning. Computers and Education: Artificial Intelligence, 3, Article 100086. https://doi.org/10.1016/j.caeai.2022.100086
Irvine, S., Williams, B., Smallridge, A., Solomonides, I., Gong, Y. H., & Andrew, S. (2021). The self-regulated learner, entry characteristics and academic performance of undergraduate nursing students transitioning to university. Nurse Education Today, 105, Article 105041. https://doi.org/10.1016/j.nedt.2021.105041
Ismail, I., & Abdul Hamid, F. Z. (2024). The extent of big data analysis by external auditors: A study of practices and prospects in Palestine. Management & Accounting Review (MAR), 23(1), 133–164. https://doi.org/10.24191/MAR.V23i01-05
Ismail, S. M., Nikpoo, I., & Prasad, K. D. V. (2023). Promoting self-regulated learning, autonomy, and self-efficacy of EFL learners through authentic assessment in EFL classrooms. Language Testing in Asia, 13(1), Article 27. https://doi.org/10.1186/s40468-023-00239-z
Jeon, J., & Lee, S. (2023). Large language models in education: A focus on the complementary relationship between human teachers and ChatGPT. Education and Information Technologies, 28, 15873–15892. https://doi.org/10.1007/s10639-023-11834-1
Jivet, I., Scheffel, M., Schmitz, M., Robbers, S., Specht, M., & Drachsler, H. (2020). From students with love: An empirical study on learner goals, self-regulated learning and sense-making of learning analytics in higher education. The Internet and Higher Education, 47, Article 100758. https://doi.org/10.1016/j.iheduc.2020.100758
Karrenbauer, C., Brauner, T., König, C. M., & Breitner, M. H. (2023). Design, development, and evaluation of an individual digital study assistant for higher education students. Educational Technology Research and Development, 71(5), 2047–2071. https://doi.org/10.1007/s11423-023-10255-8
Kay, J., Bartimote, K., Kitto, K., Kummerfeld, B., Liu, D., & Reimann, P. (2022). Enhancing learning by Open Learner Model (OLM) driven data design. Computers and Education: Artificial Intelligence, 3, Article 100069. https://doi.org/10.1016/j.caeai.2022.100069
Kay, J., & Lum, A. (2005). Exploiting readily available web data for scrutable student models. In C.-K. Looi, G. McCalla, B. Bredeweg, & J. Breuker (Eds.), Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting learning through intelligent and socially informed technology (pp. 338–345). ACM. https://dl.acm.org/doi/10.5555/1562524.1562573
Kesuma, A. T., Harun, Zamroni, Putranta, H., & Kistoro, H. C. A. (2020). Evaluation of the self-regulated learning model in high schools: A systematic literature review. Universal Journal of Educational Research, 8(10), 4792–4806. https://doi.org/10.13189/ujer.2020.081051
Khalid, N., Zapparrata, N., & Phillips, B. C. (2024). Theoretical underpinnings of technology-based interactive instruction. Teaching and Learning in Nursing, 19(1), e145–e149. https://doi.org/10.1016/j.teln.2023.10.004
Khan, K. A., & Rafi, S. M. T. (2020). Online education & MOOCs: Teacher self-disclosure in online education and a mediating role of social presence. South Asian Journal of Management Sciences, 14(1), 142–158. https://doi.org/10.21621/sajms.2020141.08
Kim, S., Jeong, S. H., Kim, H. S., & Jeong, Y. J. (2022). Academic success of online learning in undergraduate nursing education programs in the COVID-19 pandemic era. Journal of Professional Nursing, 38, 6–16. https://doi.org/10.1016/j.profnurs.2021.10.005
Kitchenham, B. (2004). Procedures for Performing Systematic Reviews (Keele University Technical Report TR/SE-0401 and NICTA Technical Report 0400011T.1). Keele University & Empirical Software Engineering Australia. http://www.inf.ufsc.br/~aldo.vw/kitchenham.pdf
Kitchenham, B., Brereton, O. P., Budgen, D., Turner, M., Bailey, J., & Linkman, S. (2009). Systematic literature reviews in software engineering—A systematic literature review. Information and Software Technology, 51(1), 7–15. https://doi.org/10.1016/j.infsof.2008.09.009
Kitchenham, B., Budgen, D., & Brereton, P. (2015). Evidence-based software engineering and systematic reviews. Taylor & Francis. https://doi.org/10.1201/b19467
Kong, S. C., & Lin, T. (2023). Developing self-regulated learning as a pedagogy in higher education: An institutional survey and case study in Hong Kong. Heliyon, 9(11), Article e22115. https://doi.org/10.1016/j.heliyon.2023.e22115
Kryshko, O., Fleischer, J., Waldeyer, J., Wirth, J., & Leutner, D. (2020). Do motivational regulation strategies contribute to university students’ academic success? Learning and Individual Differences, 82, Article 101912. https://doi.org/10.1016/j.lindif.2020.101912
Lambert, S. R. (2020). Do MOOCs contribute to student equity and social inclusion? A systematic review 2014–18. Computers & Education, 145, Article 103693. https://doi.org/10.1016/j.compedu.2019.103693
Latipah, E., Kistoro, H. C. A., & Putranta, H. (2021). How are the parents involvement, peers and agreeableness personality of lecturers related to self-regulated learning? European Journal of Educational Research, 10(1), 413–425. https://doi.org/10.12973/eu-jer.10.1.413
Lee, D., Allen, M., Cheng, L., Watson, S., & Watson, W. (2021). Exploring relationships between self-efficacy and self-regulated learning strategies of English language learners in a college setting. Journal of International Students, 11(3), 567–585. https://doi.org/10.32674/jis.v11i3.2145
Lee, D., Watson, S. L., & Watson, W. R. (2019). Systematic literature review on self-regulated learning in massive open online courses. Australasian Journal of Educational Technology, 35(1), 28–41. https://doi.org/10.14742/ajet.3749
Li, Y., Raković, M., Dai, W., Lin, J., Khosravi, H., Galbraith, K., & Chen, G. (2023). Are deeper reflectors better goal-setters? AI-empowered analytics of reflective writing in pharmaceutical education. Computers and Education: Artificial Intelligence, 5, Article 100157. https://doi.org/10.1016/j.caeai.2023.100157
Liang, Y., Ren, L., Wei, C., & Shi, Y. (2023). The influence of internet-specific epistemic beliefs on academic achievement in an online collaborative learning context for college students. Sustainability, 15(11), Article 8938. https://doi.org/10.3390/su15118938
Lim, L., Bannert, M., van der Graaf, J., Singh, S., Fan, Y., Surendrannair, S., & Gašević, D. (2023). Effects of real-time analytics-based personalized scaffolds on students’ self-regulated learning. Computers in Human Behavior, 139, Article 107547. https://doi.org/10.1016/j.chb.2022.107547
Lin, X., & Dai, Y. (2022). An exploratory study of the effect of online learning readiness on self-regulated learning. International Journal of Chinese Education, 11(2). https://doi.org/10.1177/2212585X221111938
Looi, K. H. (2023). Future preferred mode of learning of business undergraduates and its implications. Knowledge Management & E-Learning, 15(2), 253–268. https://doi.org/10.34105/j.kmel.2023.15.014
Lu, J.-L. (2021). Research on the ideological and political teaching mode of dual system curriculum in colleges and universities based on MOOC. In W. Fu, S. Liu, & J. Dai (Eds.), E-Learning, E-Education, and Online Training. eLEOT 2021 (pp. 231–242). Springer. https://doi.org/10.1007/978-3-030-84383-0_20
Lukes, L. A., Jones, J. P., & McConnell, D. A. (2020). Self-regulated learning: Overview and potential future directions in geoscience. Journal of Geoscience Education, 69(1), 14–26. https://doi.org/10.1080/10899995.2020.1820828
Mapuya, M. (2022). Promoting self-regulated learning among first-year accounting-student teachers: A student empowerment pedagogical framework. International Journal of Learning, Teaching and Educational Research, 21(5), 64–83. https://www.doi.org/10.26803/ijlter.21.5.4
Markauskaite, L., Marrone, R., Poquet, O., Knight, S., Martinez-Maldonado, R., Howard, S., & Siemens, G. (2022). Rethinking the entwinement between artificial intelligence and human learning: What capabilities do learners need for a world with AI? Computers and Education: Artificial Intelligence, 3, Article 100056. https://doi.org/10.1016/j.caeai.2022.100056
Martin, H., Craigwell, R., & Ramjarrie, K. (2022). Grit, motivational belief, self-regulated learning (SRL), and academic achievement of civil engineering students. European Journal of Engineering Education, 47(4), 535–557. https://doi.org/10.1080/03043797.2021.2021861
Matcha, W., Uzir, N. A., Gašević, D., & Pardo, A. (2019). A systematic review of empirical studies on learning analytics dashboards: A self-regulated learning perspective. IEEE Transactions on Learning Technologies, 13(2), 226–245. https://doi.org/10.1109/TLT.2019.2916802
Matcha, W., Gašević, D., Uzir, N. A., Jovanović, J., & Pardo, A. (2019). Analytics of learning strategies: Associations with academic performance and feedback. In D. Azcona & R. Chung (Eds.), Proceedings of the 9th International Conference on Learning Analytics & Knowledge (pp. 461–470). ACM. https://doi.org/10.1145/3303772.3303787
Matsuyama, Y., Nakaya, M., Okazaki, H., Lebowitz, A. J., Leppink, J., & van der Vleuten, C. (2019). Does changing from a teacher-centered to a learner-centered context promote self-regulated learning: A qualitative study in a Japanese undergraduate setting. BMC Medical Education, 19, Article 152.
Mehrabi, M., Safarpour, A. R., & Keshtkar, A. A. (2020). Massive open online courses (MOOCs) dropout rate in the world: A systematic review protocol. Research Square. https://doi.org/10.21203/rs.3.rs-99449/v1
Milano, S., McGrane, J. A., & Leonelli, S. (2023). Large language models challenge the future of higher education. Nature Machine Intelligence, 5, 333–334. https://doi.org/10.1038/s42256-023-00644-2
Muwonge, C. M., Ssenyonga, J., Kibedi, H., & Schiefele, U. (2020). Use of self-regulated learning strategies among teacher education students: A latent profile analysis. Social Sciences & Humanities Open, 2(1), Article 100037. https://doi.org/10.1186/s12909-019-1550-x
Nguyen, H.L., & Zarra-Nezhad, M. (2023). Enhancing sustainable lifelong learning in higher education for uncertain transitions: A mixed method investigation into Vietnamese undergraduates’ strategies. International Journal of Lifelong Education, 42(4), 389–405. https://doi.org/10.1080/02601370.2023.2226346
Nikolopoulou, K. (2023). Self-regulated and mobile-mediated learning in blended tertiary education environments: Student insights from a pilot study. Sustainability, 15(16), Article 12284. https://doi.org/10.3390/su151612284
Nufus, H., Muhandaz, R., Nurdin, E., Ariawan, R., Fineldi, R. J., Hayati, I. R., & Situmorang, D. D. B. (2024). Analyzing the students’ mathematical creative thinking ability in terms of self-regulated learning: How do we find what we are looking for? Heliyon, 10(3)., Article: e24871. https://doi.org/10.1016/j.heliyon.2024.e24871
Núñez, M. E., García, P. M., & Abbas, A. (2023). The mediating role of self-regulation between emotional intelligence and student performance in online global classroom-based collaborative international online learning (COIL): Empirical evidence from four partner universities of Latin America. Research in Globalization, 7, Article 100178. https://doi.org/10.1016/j.resglo.2023.100178
Núñez, M. E., Rojas, J.-C., & Rodríguez-Paz, M. X. (2019). Real-time distance courses to improve satisfaction and competence—A case study on the performance of students observing their grades. In A. K. Ashmawy & S. Schreiter (Eds.), 2019 IEEE Global Engineering Education Conference (EDUCON) (pp. 519–525). IEEE. https://doi.org/10.1109/EDUCON.2019.8725235
Oinas, S., Hotulainen, R., Koivuhovi, S., Brunila, K., & Vainikainen, M. P. (2022). Remote learning experiences of girls, boys and non-binary students. Computers & Education, 183, Article 104499. https://doi.org/10.1016/j.compedu.2022.104499
Omar, S., Hussein, N. H., Hanapi, N. H., Abdullah, Y. S., Mohd Noor, A. L., & Saidi, B. (2023). Self-efficacy and self-regulated learning among undergraduate in learning Arabic as a foreign language via online. Issues in Language Studies, 12(2), 227–245. https://doi.org/10.33736/ils.v12i2
Osakwe, I., Chen, G., Fan, Y., Rakovic, M., Li, X., Singh, S., & Gašević, D. (2023). Reinforcement learning for automatic detection of effective strategies for self-regulated learning. Computers and Education: Artificial Intelligence, 5, Article 100181. https://doi.org/10.1016/j.caeai.2023.100181
Panadero, E. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 8, Article 422. https://doi.org/10.3389/fpsyg.2017.00422
Park, H. J., & Kim, S. (2023). Relationship between super-leadership and self-directed learning ability in online nursing education: The mediating effects of self-leadership and self-efficacy perceptions. Heliyon, 9(6), Article e17416 https://doi.org/10.1016/j.heliyon.2023.e17416
Patiño-Toro, O. N., Valencia-Arias, A., Fernández-Toro, A., Jiménez-Guzmán, A., & Gil, C. A. P. (2023). Proposed methodology for designing and developing MOOCs for the deaf community. Heliyon, 9(10), Article e20456. https://doi.org/10.1016/j.heliyon.2023.e20456
Paudyal, P., Banerjee, A., Hu, Y., & Gupta, S. (2019). DAVEE: A deaf accessible virtual environment for education. In S. Dow & M. L. Maher (Chairs), C&C ’19: Proceedings of the 2019 Creativity and Cognition (pp. 522–526). ACM. https://doi.org/10.1145/3325480.3326546
Pintrich, P. R. (1999). The role of motivation in promoting and sustaining self-regulated learning. International Journal of Educational Research, 31(6), 459–470. https://doi.org/10.1016/S0883-0355(99)00015-4
Pintrich, P. R. (2000). Chapter 14: The role of goal orientation in self-regulated learning. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 451–502). Academic Press. https://doi.org/10.1016/B978-012109890-2/50043-3
Raviv, A., Amasha, M., & Bader, N. (2023). Arab and Jewish students in the post-Covid-19 era: Learning patterns as a trigger for dropout intent. Social Sciences & Humanities Open, 8(1), Article 100637. https://doi.org/10.1016/j.ssaho.2023.100637
Reparaz, C., Aznarez-Sanado, M., & Mendoza, G. (2020). Self-regulation of learning and MOOC retention. Computers in Human Behavior, 111, Article 106423. https://doi.org/10.1016/j.chb.2020.106423
Reyes-Millán, M., Villareal-Rodríguez, M., Murrieta-Flores, M. E., Bedolla-Cornejo, L., Vázquez-Villegas, P., & Membrillo-Hernández, J. (2023). Evaluation of online learning readiness in the new distance learning normality. Heliyon, 9(11), Article e22070. https://doi.org/10.1016/j.heliyon.2023.e22070
Riatun & Alvin, S. (2023). Empowering education: Developing an e-learning course for introduction to communication studies at UMN. International Journal of Educational Review, Law & Social Science, 3(3), 1006–1016. https://radjapublika.com/index.php/IJERLAS/article/view/882
Robbins, M. M., Onodipe, G. O., & Marks, A. (2020). Reflective writing and self-regulated learning in multi-disciplinary flipped classrooms. Journal of the Scholarship of Teaching and Learning, 20(3), 20–32. https://doi.org/10.14434/josotl.v20i3.27541
Rodríguez, M. F., Nussbaum, M., Yunis, L., Reyes, T., Alvares, D., Joublan, J., & Navarrete, P. (2022). Using scaffolded feedforward and peer feedback to improve problem-based learning in large classes. Computers & Education, 182, Article 104446. https://doi.org/10.1016/j.compedu.2022.104446
Saiyad, S., Virk, A., Mahajan, R., & Singh, T. (2020). Online teaching in medical training: Establishing good online teaching practices from cumulative experience. International Journal of Applied and Basic Medical Research, 10(3), 149–155. https://doi.org/10.4103/ijabmr.ijabmr_358_20
Schunk, D. H., & Ertmer, P. A. (2000). Self-regulation and academic learning self-efficacy enhancing interventions. In M. Boekaerts, P. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 631–649). Academic Press. https://doi.org/10.1016/B978-012109890-2/50043-3
Sevnarayan, K. (2022). Reimaging eLearning technologies to support students: On reducing transactional distance at an open and distance eLearning institution. E-Learning and Digital Media, 19(4), 421–439. https://doi.org/10.1177/20427530221096535
Su, L., Noordin, N., & Jeyaraj, J. J. (2023). Effectiveness of self-regulated learning intervention on foreign language learning at tertiary level: A systematic review. World Journal of English Language, 13(5), 403–411. https://doi.org/10.5430/wjel.v13n5p403
Tadesse, T., Asmamaw, A., Getachew, K., Ferede, B., Melese, W., Siebeck, M., & Fischer, M. R. (2022). Self-regulated learning strategies as predictors of perceived learning gains among undergraduate students in Ethiopian universities. Education Sciences, 12(7), Article 468. https://doi.org/10.3390/educsci12070468
Tao, X., Hanif, H., & Ebrahim, N. A. (2023). Emerging trends of self-regulated learning: A comprehensive bibliometric analysis. World Journal of English Language, 13(6), 252-269. https://doi.org/10.5430/wjel.v13n6p252
Tekkol, İ. A., & Demirel, M. (2018). An investigation of self-directed learning skills of undergraduate students. Frontiers in Psychology, 9, Article 2324. https://doi.org/10.3389/fpsyg.2018.02324
Teng, L. S., Yuan, R. E., & Sun, P. P. (2020). A mixed-methods approach to investigating motivational regulation strategies and writing proficiency in English as a foreign language contexts. System, 88, Article 102182. https://doi.org/10.1016/j.system.2019.102182
ter Beek, M., Opdenakker, M.-C., Spijkerboer, A. W., Brummer, L., Ozinga, H. W., & Strijbos, J.-W. (2019). Scaffolding expository history text reading: Effects on adolescents’ comprehension, self-regulation, and motivation. Learning and Individual Differences, 74, Article 101749. https://doi.org/10.1016/j.lindif.2019.06.003
Tise, J. C., Hernandez, P. R., & Schultz, P. W. (2023). Mentoring underrepresented students for success: Self-regulated learning strategies as a critical link between mentor support and educational attainment. Contemporary Educational Psychology, 75, Article 102233. https://doi.org/10.1016/j.cedpsych.2023.102233
Tran, T. Q., & Phan Tran, T. N. (2021). Vietnamese EFL high school students’ use of self-regulated language learning strategies for project-based learning. International Journal of Instruction, 14(1), 459–474. https://doi.org/10.29333/iji.2021.14127a
Troussas, C., Krouska, A., & Sgouropoulou, C. (2020). Collaboration and fuzzy-modeled personalization for mobile game-based learning in higher education. Computers & Education, 144, Article 103698. https://doi.org/10.1016/j.compedu.2019.103698
Turan, Z., Kucuk, S., & Karabey, S. C. (2022). The university students’ self-regulated effort, flexibility and satisfaction in distance education. International Journal of Educational Technology in Higher Education, 19, Article 35. https://doi.org/10.1186/s41239-022-00342-w
Tzimas, D. E., & Demetriadis, S. N. (2024). Impact of learning analytics guidance on student self-regulated learning skills, performance, and satisfaction: A mixed methods study. Education Sciences, 14(1), Article 92. https://doi.org/10.3390/educsci14010092
Upton, K., & Kay, J. (2009). Narcissus: Interactive activity mirror for small groups. In G.-J. Houben, G. McCalla, F. Pianesi, & M. Zancanaro (Eds.), UMAP09, User Modeling, Adaptation and Personalisation (pp. 54–65.) Springer. https://doi.org/10.1007/978-3-642-02247-0_8
van Alten, D. C. D., Phielix, C., Janssen, J., & Kester, L. (2020). Self-regulated learning support in flipped learning videos enhances learning outcomes. Computers & Education, 158, 1–16, Article 104000. https://doi.org/10.1016/j.compedu.2020.104000
Wang, C., Cheng, Z., Yue, X.-G., & McAleer, M. (2020). Risk management of COVID-19 by universities in China. Journal of Risk and Financial Management, 13(2), Article 36. https://doi.org/10.3390/jrfm13020036
Wang, H., Yang, J., & Li, P. (2021). How and when goal-oriented self-regulation improves college students’ well-being: A weekly diary study. Current Psychology. 41(11), 7532-7543. https://doi.org/10.1007/s12144-020-01288-w
Wang, J., King, R. B., & Rao, N. (2019). The role of social-academic goals in Chinese students’ self-regulated learning. European Journal of Psychology of Education, 34(3), 579–600. https://doi.org/10.1007/s10212-018-0404-y
White, S., White, S., & Borthwick, K. (2020). MOOCs, learning designers and the unbundling of educator roles in higher education. Australasian Journal of Educational Technology, 36(5), 71–84. https://doi.org/10.14742/ajet.6111
Wild, S., & Neef, C. (2023). Analyzing the associations between motivation and academic performance via the mediator variables of specific mathematic cognitive learning strategies in different subject domains of higher education. International Journal of STEM Education, 10(1), Article 32. https://doi.org/10.1186/s40594-023-00423-w
Winne, P. H., & Hadwin, A. F. (1998). Studying as self-regulated engagement in learning. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Metacognition in educational theory and practice (pp. 277–304). Routledge.
Wong, J., Baars, M., Davis, D., Van Der Zee, T., Houben, G. J., & Paas, F. (2019). Supporting self-regulated learning in online learning environments and MOOCs: A systematic review. International Journal of Human-Computer Interaction, 35(4–5), 356–373. https://doi.org/10.1080/10447318.2018.1543084
Wong, J., Baars, M., He, M., de Koning, B. B., & Paas, F. (2021). Facilitating goal setting and planning to enhance online self-regulation of learning. Computers in Human Behavior, 124, Article 106913. https://doi.org/10.1016/j.chb.2021.106913
Xie, H., Chu, H.-C., Hwang, G.-J., & Wang, C.-C. (2019). Trends and development in technology-enhanced adaptive/personalized learning: A systematic review of journal publications from 2007 to 2017. Computers & Education, 140, Article 103599. https://doi.org/10.1016/j.compedu.2019.103599
Xu, Z., Zdravkovic, A., Moreno, M., & Woodruff, E. (2022). Understanding optimal problem-solving in a digital game: The interplay of learner attributes and learning behavior. Computers and Education Open, 3, Article 100117. https://doi.org/10.1016/j.caeo.2022.100117
Xu, Z., Zhao, Y., Liew, J., Zhou, X., & Kogut, A. (2023). Synthesizing research evidence on self-regulated learning and academic achievement in online and blended learning environments: A scoping review. Educational Research Review, 39, Article 100510. https://doi.org/10.1016/j.edurev.2023.100510
Yan, L., Sha, L., Zhao, L., Li, Y., Martinez-Maldonado, R., Chen, G., & Gašević, D. (2023). Practical and ethical challenges of large language models in education: A systematic scoping review. British Journal of Educational Technology, 55(1), 90–112. https://doi.org/10.1111/bjet.13370
Yavuzalp, N., & Bahcivan, E. (2021). A structural equation modeling analysis of relationships among university students’ readiness for e-learning, self-regulation skills, satisfaction, and academic achievement. Research and Practice in Technology Enhanced Learning, 16, Article 15. https://doi.org/10.1186/s41039-021-00162-y
Yeh, Y.-C., Kwok, O.-M., Chien, H.-Y., Sweany, N. W., Baek, E., & McIntosh, W. A. (2019). How college students’ achievement goal orientations predict their expected online learning outcome: The mediation roles of self-regulated learning strategies and supportive online learning behaviors. Online Learning, 23(4), 23–41. https://doi.org/10.24059/olj.v23i4.2076
Zarestky, J., Bigler, M., Brazile, M., Lopes, T., & Bangerth, W. (2022). Reflective writing supports metacognition and self-regulation in graduate computational science and engineering. Computers and Education Open, 3, Article 100085. https://doi.org/10.1016/j.caeo.2022.100085
Zhang, X., Dai, S., & Ardasheva, Y. (2020). Contributions of (de)motivation, engagement, and anxiety to English listening and speaking. Learning and Individual Differences, 79, Article 101856. https://doi.org/10.1016/j.lindif.2020.101856
Zheng, J., Huang, L. Y., Li, S., Lajoie, S. P., Chen, Y. X., & Hmelo-Silver, C. E. (2021). Self-regulation and emotion matter: A case study of instructor interactions with a learning analytics dashboard. Computers & Education, 161, Article 104061. https://doi.org/10.1016/j.compedu.2020.104061
Zhou, L., Li, F., Wu, S., & Zhou, M. (2020). School’s out, but class’s on: The largest online education in the world today: Taking China’s practical exploration during the COVID-19 epidemic prevention and control as an example. Best Evidence of Chinese Education, 4(2), 501–519. https://doi.org/10.15354/bece.20.ar023
Zhou, X., Chai, C. S., Jong, M. S.-Y., & Xiong, X. B. (2021). Does relatedness matter for online self-regulated learning to promote perceived learning gains and satisfaction? The Asia-Pacific Education Researcher, 30(3), 205–215. https://doi.org/10.1007/s40299-021-00579-5
Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American Educational Research Journal, 45(1), 166–183. https://www.jstor.org/stable/30069464
Zimmerman, B. J., & Moylan, A. R. (2009). Self-regulation: Where metacognition and motivation intersect. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Handbook of metacognition in education (pp. 299–315). Routledge/Taylor & Francis Group. https://doi.org/10.4324/9780203876428
Zimmerman, B. J., & Schunk, D. H. (2011). Self-regulated learning and performance: An introduction and an overview. In D. H. Schunk & B. Zimmerman (Eds.), Handbook of self-regulation of learning and performance (1st ed., pp. 1–12). Routledge. https://doi.org/10.4324/9780203839010
Published
How to Cite
Issue
Section
License

This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License. The copyright for all content published in IRRODL remains with the authors.
This copyright agreement and usage license ensure that the article is distributed as widely as possible and can be included in any scientific or scholarly archive.
You are free to
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
The licensor cannot revoke these freedoms as long as you follow the license terms below:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.