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Arvind Chawla
Independent Researcher
India
Abstract
Metacognition—the awareness and regulation of one’s own cognitive processes—plays a pivotal role in educational success, particularly within open‑book online assessments where learners have continual access to resources. This manuscript explores the theoretical underpinnings of metacognition, examines its manifestation in digital assessment environments, and investigates how targeted instructional interventions can strengthen learners’ metacognitive skills. Employing a convergent parallel mixed‑methods design, the study engaged 250 undergraduate students in an online psychology course, integrating quantitative measures (pre‑ and post‑Metacognitive Awareness Inventory), qualitative think‑aloud protocols, and learning analytics captured via a bespoke LMS dashboard. Guided scaffolding—including planning templates, real‑time monitoring checklists, and structured reflective summaries—was embedded in two of three consecutive assessments. Compared to a baseline assessment without supports, students exposed to scaffolds demonstrated significant gains in metacognitive knowledge (d = 0.96), increased strategic resource consultation, and more sustained time‑on‑task. Think‑aloud data revealed a shift from ad‑hoc searching to deliberate planning and evaluation of answers, while focus‑group feedback highlighted the value of prompts in reducing cognitive overload and enhancing self‑confidence. Furthermore, assessment performance rose from an average score of 72% to 81%, underscoring the practical benefits of metacognitive support. By triangulating survey data, behavioral metrics, and learner voices, this study provides robust evidence that scaffolded metacognitive interventions not only amplify academic performance but also foster deeper engagement and self‑regulated learning habits. Implications for instructional design, LMS feature development, and future longitudinal research are discussed.
Keywords
Metacognition; Open‑Book Online Assessments; Self‑Regulated Learning; Scaffolding; Digital Learning Analytics
References
- https://www.researchgate.net/publication/319130669/figure/fig5/AS:527713926225924@1502828212298/Theoretical-Model-of-Metacognition.png
- https://www.researchgate.net/publication/328194909/figure/fig2/AS:11431281176240205@1690079415501/Scaffold-design-and-fabrication-flowchart.png
- Brown, A. L. (1987). Metacognition, executive control, self‑regulation, and other more mysterious mechanisms. In F. E. Weinert & R. H. Kluwe (Eds.), Metacognition, motivation, and understanding (pp. 65–116). Lawrence Erlbaum Associates.
- Birenbaum, M. (2005). New assessment formats: The challenge of open‑book examinations. Open University Press.
- Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
- Broadbent, J., & Poon, W. L. (2015). Self‑regulated learning strategies and academic achievement in online higher education learning environments: A systematic review. The Internet and Higher Education, 27, 1–13. https://doi.org/10.1016/j.iheduc.2015.04.007
- Creswell, J. W., & Plano Clark, V. L. (2011). Designing and conducting mixed methods research (2nd ed.). Sage.
- de Bruin, A. B. H., Thiede, K. W., & Camp, G. (2013). Supporting self‑regulated learning in text revision: The role of peer and expert feedback. Metacognition and Learning, 8(2), 185–206. https://doi.org/10.1007/s11409-012-9106-8
- Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive‑developmental inquiry. American Psychologist, 34(10), 906–911. https://doi.org/10.1037/0003-066X.34.10.906
- Greene, J. A., & Azevedo, R. (2010). The measurement of learners’ self‑regulation while using hypermedia. Journal of Educational Computing Research, 42(1), 51–73. https://doi.org/10.2190/EC.42.1.d
- Hacker, D. J., Dunlosky, J., & Graesser, A. C. (2009). Metacognition in educational theory and practice. Routledge.
- Macfadyen, L. P., & Dawson, S. (2010). Mining LMS data to develop an “early warning system” for educators: A proof of concept. Computers & Education, 54(2), 588–599. https://doi.org/10.1016/j.compedu.2009.09.008
- Pang, M., & Zaphiris, P. (2014). Self‑regulated learning strategies and effectiveness in constructivist learning environments. Educational Technology Research and Development, 62(2), 165–184. https://doi.org/10.1007/s11423-013-9332-6
- Pintrich, P. R., & Zusho, A. (2002). The development of academic self‑regulation: The role of cognitive and motivational factors. In A. Wigfield & J. S. Eccles (Eds.), Development of achievement motivation (pp. 249–284). Academic Press.
- Schraw, G., & Dennison, R. S. (1994). Assessing metacognitive awareness. Contemporary Educational Psychology, 19(4), 460–475. https://doi.org/10.1006/ceps.1994.1033
- Schraw, G., Crippen, K. J., & Hartley, K. (2006). Promoting self‑regulated learning in science education: Metacognition as part of a broader perspective on learning. Research in Science Education, 36(1–2), 111–139. https://doi.org/10.1007/s11165-005-3917-8
- Van de Pol, J., Volman, M., & Beishuizen, J. (2010). Scaffolding in teacher–student interaction: A decade of research. Educational Psychology Review, 22(3), 271–296. https://doi.org/10.1007/s10648-010-9127-6
- White, B. Y., & Frederiksen, J. R. (2005). A theoretical framework and approach for fostering metacognitive development. Educational Psychologist, 40(4), 211–223. https://doi.org/10.1207/s15326985ep4004_2
- Winne, P. H., & Hadwin, A. F. (1998). Studying as self‑regulated learning. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Metacognition in educational theory and practice (pp. 277–304). Erlbaum.
- Zimmerman, B. J. (2002). Becoming a self‑regulated learner: An overview. Theory into Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2