Enhancing Digital-Age Metacognition: A Framework for Cognitive Innovation in Thai Secondary Education

Background/purpose. The increasing prevalence of digital tools in education necessitates models that enhance students' metacognitive skills. Despite this need, limited research exists on structured pedagogical approaches to foster metacognition within digital learning contexts. This study aimed to develop and evaluate the Cognitive Innovation Model to Enhance Metacognitive Skills in the Digital Age (CIMEMSDA) for Thai secondary students, addressing this gap in contemporary education.

Materials/methods. A quasi-experimental design was employed to assess the efficacy of CIMEMSDA, which follows a four-stage structured approach: (I) introduction and recalling, (ii) reviewing and planning, (iii) investigating and applying knowledge, and (iv) summary and evaluation. Rooted in constructivist and metacognitive principles, the model was validated by nine experts for utility, feasibility, suitability, and accuracy. The study involved 80 Grade 8 students in 2024, divided equally into experimental and traditional groups. The experimental group used CIMEMSDA with modules on computational thinking and Python programming, while the traditional group received standard instruction.

Results. The experimental group demonstrated significantly higher metacognitive skills and academic performance than the traditional group. The MAPS Model significantly improved students' digital technology competencies, with post-learning DTS scores exceeding the benchmark by 8.07%. This demonstrates the model's ability to surpass foundational expectations and foster advanced technological skills. Students maintained their academic achievement and digital technology skills for 14 days post-learning without significant decline, illustrating the model's effectiveness in ensuring durable and long-lasting learning outcomes.

Conclusion. CIMEMSDA shows strong potential as an educational tool for enhancing metacognitive skills in the digital age. Its structured, stage-based approach aligns well with contemporary educational practices, addressing critical gaps and offering a feasible framework for integrating metacognitive skill development into secondary education.

Keywords: academic performance, cognitive innovation, metacognition, secondary school students, Thailand

References

Abdelrahman, R. M. (2020). Metacognitive awareness and academic motivation and their impact on academic achievement of Ajman University students. Heliyon, 6(9), e04192. https://doi.org/10.1016/j.heliyon.2020.e04192

Akcaoğlu, M. Ö., Mor, E., & Külekçi, E. (2023). The mediating role of metacognitive awareness in the relationship between critical thinking and self-regulation. Thinking Skills and Creativity, 47, 101187. https://doi.org/10.1016/j.tsc.2022.101187

Alam, M. A. (2023). From teacher-centered to student-centered learning: The role of constructivism and connectivism in pedagogical transformation. Journal of Education, 11(2), 154-167. https://tinyurl.com/5n6fdv54

Altinay, L., Kromidha, E., Nurmagambetova, A., Alrawadieh, Z., & Madanoglu, G. K. (2022). A social cognition perspective on entrepreneurial personality traits and intentions to start a business: does creativity matter? Management Decision, 60(6), 1606-1625. https://doi.org/10.1108/MD-12-2020-1592

Ayoo, S., Leeming, M., & Huff, S. R. (2024). Meta-evaluation: Validating program evaluation standards through the United Nations Evaluation Quality Assessment (EQAs). Evaluation Journal of Australasia, 24(1), 14-39. https://doi.org/10.1177/1035719X231220979

Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs.

Basman, M., & Bayram, D. (2024). Cultural intelligence and attitudes towards multicultural education: Mediating role of intercultural sensitivity. Educational Process: International Journal, 13(3), 177-189. https://doi.org/10.22521/edupij.2024.133.10

Boser, J., Scherer, S., Kuchta, K., Wenzel, S. F. C., & Horz, H. (2017). Empirically founded teaching in psychology–An example for the combination of evidence-based teaching and the Scholarship of Teaching and Learning. Psychology Learning & Teaching, 16(2), 261-275. https://doi.org/10.1177/1475725716686452

Fernández-Cézar, R., Prada-Núñez, R., & Solano-Pinto, N. (2024). Collaborative Online International Learning: Experiences in Higher Education. Educational Process: International Journal, 13(4), 7-24. https://doi.org/10.22521/edupij.2024.134.1

Gero, J. S., & Milovanovic, J. (2020). A framework for studying design thinking through measuring designers' minds, bodies, and brains. Design Science, 6, e19. https://doi.org/10.1017/dsj.2020.15

Goldberg, H. (2022). Growing brains, nurturing minds—neuroscience as an educational tool to support students’ development as life-long learners. Brain Sciences, 12(12), 1622. https://doi.org/10.3390/brainsci12121622

Hackman, D. A., & Kraemer, D. J. (2020). Socioeconomic disparities in achievement: Insights on neurocognitive development and educational interventions. In Educational Neuroscience (pp. 88-119). Routledge. https://doi.org/10.4324/9781003016830

Hokor, E. K., & Sedofia, J. (2021). Developing probabilistic reasoning in preservice teachers: Comparing the learner-centered and teacher-centered approaches of teaching. International Journal of Studies in Education and Science, 2(2), 120-145. https://tinyurl.com/3ykp6tjr

Honra, J. R., & Monterola, S. L. C. (2024). Fostering cognitive flexibility of students through design thinking in biology education. Cogent Education, 11(1). 2415301. https://doi.org/10.1080/2331186X.2024.2415301

Kavousi, S., Miller, P. A., & Alexander, P. A. (2020). Modeling metacognition in design thinking and design making. International Journal of Technology and Design Education, 30, 709-735. https://doi.org/10.1007/s10798-019-09521-9

Kocabaşoğlu, B., & Şahin, E. (2021). Investigation of gifted students' cognitive structures on the concept of innovation. Journal of Turkish Science Education, 18(4), 649-673. https://www.tused.org/index.php/tused/article/view/1162

Kwangmuang, P., Jarutkamolpong, S., Sangboonraung, W., & Daungtod, S. (2021). The development of learning innovation to enhance higher-order thinking skills for students in Thailand junior high schools. Heliyon, 7(6), e07309. https://doi.org/10.1016/j.heliyon.2021.e07309

Li, W., Liu, C. Y., & Tseng, J. C. (2023). Effects of the interaction between metacognition teaching and students’ learning achievement on students’ computational thinking, critical thinking, and metacognition in collaborative programming learning. Education and Information Technologies, 28(10), 12919-12943. https://doi.org/10.1007/s10639-023-11671-2

Li, W., Liu, C. Y., & Tseng, J. C. (2024). Development of a metacognitive regulation‐based collaborative programming system and its effects on students' learning achievements, computational thinking tendency, and group metacognition. British Journal of Educational Technology, 55(1), 318-339. https://doi.org/10.1111/bjet.13358

Maringanti, H. B., & Sahu, M. (2024). Cognitive Learning. In Digital Skill Development for Industry 4.0 (pp. 15-32). Auerbach Publications. https://doi.org/10.1201/9781003504894

McTighe, J., & Willis, J. (2019). Upgrade your teaching: Understanding by design meets. Nneuroscience. https://tinyurl.com/2cejbrnh

Montuori, C., Gambarota, F., Altoé, G., & Arfé, B. (2023). The cognitive effects of computational thinking: A systematic review and meta-analytic study. Computers & Education, 104961. https://doi.org/10.1016/j.compedu.2023.104961

Nückles, M., Roelle, J., Glogger-Frey, I., Waldeyer, J., & Renkl, A. (2020). The self-regulation-view in writing-to-learn: Using journal writing to optimize cognitive load in self-regulated learning. Educational Psychology Review, 32(4), 1089-1126. https://doi.org/10.1007/s10648-020-09541-1

Okoye, K., & Hosseini, S. (2024). Analysis of Variance (ANOVA) in R: One-Way and Two-Way ANOVA. In R Programming: Statistical Data Analysis in Research (pp. 187-209). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-97-3385-9_9

Oyelana, O. O., Olson, J., & Caine, V. (2022). An evolutionary concept analysis of learner-centered teaching. Nurse Education Today, 108, 105187. https://doi.org/10.1016/j.nedt.2021.105187

Padmanabha, C. H. (2020). Metacognition: Conceptual framework. Journal on Educational Psychology, 14(1), 1-11. https://tinyurl.com/mpsdxae5

Papadakis, S. (2022). Apps to promote computational thinking and coding skills to young age children: A pedagogical challenge for the 21st century learners. Educational Process: International Journal (EDUPIJ), 11(1), 7-13.https://doi.org/10.22521/edupij.2022.111.1

Rivas, S. F., Saiz, C., & Ossa, C. (2022). Metacognitive strategies and development of critical thinking in higher education. Frontiers in Psychology, 13, 913219. https://doi.org/10.3389/fpsyg.2022.913219

Raković, M., Bernacki, M. L., Greene, J. A., Plumley, R. D., Hogan, K. A., Gates, K. M., & Panter, A. T. (2022). Examining the critical role of evaluation and adaptation in self-regulated learning. Contemporary Educational Psychology, 68, 102027. https://doi.org/10.1016/j.cedpsych.2021.102027

Rubenstein, L. D., Ridgley, L. M., Callan, G. L., Karami, S., & Ehlinger, J. (2018). How teachers perceive factors that influence creativity development: Applying a Social Cognitive Theory perspective. Teaching and Teacher Education, 70, 100-110. https://doi.org/10.1016/j.tate.2017.11.012

Sato, M. (2022). Metacognition. In The Routledge Handbook of Second Language Acquisition and Individual Differences (pp. 95-110). Routledge. https://doi.org/10.4324/9781003270546

Stufflebeam, D. L. (2015). CIPP evaluation model checklist: A tool for applying the CIPP model to assess projects and programs. Western Michigan University Evaluation Center. http://tinyurl.com/mucdxtm7

Verganti, R., Dell’Era, C., & Swan, K. S. (2021). Design thinking: Critical analysis and future evolution. Journal of Product Innovation Management, 38(6), 603-622. https://doi.org/10.1111/jpim.12610

Wang, C. Y., Gao, B. L., & Chen, S. J. (2024). The effects of metacognitive scaffolding of project-based learning environments on students’ metacognitive ability and computational thinking. Education and Information Technologies, 29(5), 5485-5508. https://doi.org/10.1007/s10639-023-12022-x

Widodo, S. A., Darhim, & Ikhwanudin, T. (2018, January). Improving mathematical problem-solving skills through visual media. In Journal of Physics: Conference Series (Vol. 948, p. 012004). IOP Publishing.

Williams, L. N. (2024). Bilingualism and cognitive flexibility in pre-school aged children with and without autism (Doctoral Dissertation) Drexel University, Pennsylvania. https://tinyurl.com/56zm3phn

Wongrugsa, A., Kanjanawasee, S., & Ratchusanti, S. (2022). The efficiency of an evaluation model for undergraduate vocational education programs: An application of multiple evaluation approaches. Kasetsart Journal of Social Sciences, 43(3), 769–776. https://so04.tci-thaijo.org/index.php/kjss/article/view/260345

Yarbrough, D. B., Shulha, L. M., Hopson, R. K., & Caruthers, F. A. (2010). The program evaluation standards: A guide for evaluators and evaluation users. (3rd. Ed.), Sage Publications. http://tinyurl.com/39txh4v6

Zhang, J., Zhou, Y., Jing, B., Pi, Z., & Ma, H. (2024). Metacognition and mathematical modeling skills: The mediating roles of computational thinking in high school students. Journal of Intelligence, 12(6), 55. https://doi.org/10.3390/jintelligence12060055

Zhu, G., & Burrow, A. L. (2023). Profiles of personal and ecological assets: Adolescents’ motivation and engagement in self-driven learning. Current Psychology, 42(16), 14025- 14037. https://doi.org/10.1007/s12144-021-02412-0

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