AI, METACOGNITION, AND DIGITAL LITERACY IN PHYSICS EDUCATION: SYSTEMATIC LITERATURE REVIEW AND BIBLIOMETRIC ANALYSIS

La Ida, Abdul Haris Odja

Abstract


Purpose – This study critically examines the rapid expansion of artificial intelligence (AI) in digital learning, with a specific focus on how these technologies intersect with metacognitive skills and digital literacy in science/STEM education. This study explicitly investigates their conceptual integration and identifies a substantiated research gap in physics learning contexts.

Methodology – A systematic literature review (SLR) combined with bibliometric analysis was conducted in accordance with the PRISMA 2020 protocol. Articles were retrieved from Scopus using structured TITLE-ABS-KEY queries and limited to peer-reviewed journal articles (2020–2025) within the Social Sciences domain. From 2,670 initial records, 47 articles met predefined inclusion criteria (n = 47). Bibliometric mapping was performed using VOSviewer, followed by thematic synthesis employing open, axial, and selective coding to analyze AI intervention types, pedagogical mechanisms, and measurement approaches for metacognition and digital/AI literacy.

Findings – Bibliometric evidence indicates a sharp rise in publications from 2023 onward, with education and educational technology channels dominating the dissemination landscape. Metadata screening further revealed an explicit research void regarding the integrated study of AI, metacognition, and digital literacy in physics learning. Thematic synthesis suggests AI can enable more personalized learning trajectories, richer formative feedback, and improved self-regulation supports that align with metacognitive development and digital literacy practices.

Contribution – This study provides a bibliometrically grounded knowledge map of AI–metacognition–digital literacy research and conceptual adaptation framework proposing physics-oriented AI learning design principles and task-based assessment directions to guide future empirical research.

Keywords


Artificial intelligence; Deep learning; Metacognitive skills; Digital literacy; Science learning

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References


Al-smadi, O. A., Ab, R., & Al-ramahi, R. A. (2025). Jordanian English language learners ’ engagement with AI-supported self-regulated learning. Research in Learning Technology, 33(3377), 1–18. http://dx.doi.org/10.25304/rlt.v33.3377

Alkhawaja, L., Idris, M., Al-sayyed, S., Malek, A., & Jaber, A. (2025). Exploring the impact of Artificial Intelligence on students ’ skills for sustainable development in education. Frontiers in Education, 1(1), 1–12. https://doi.org/10.3389/feduc.2025.1691148

Anthonysamy, L. (2023). Being learners with mental resilience as outcomes of metacognitive strategies in an academic context. Cogent Education, 10(1), 1–20. https://doi.org/10.1080/2331186X.2023.2219497

Craig, K., Hale, D., Grainger, C., & Stewart, M. E. (2020). Evaluating metacognitive self-reports : systematic reviews of the value of self-report in metacognitive research. Metacognition and Learning, 15(1), 155–213. https://doi.org/10.1007/s11409-020-09222-y

Edwards, N., & Maree, L. (2025). A comparison between preservice science teachers ’ representational competence and fluency in chemistry and physics. Journal of Turkish Science Education, 22(2), 300–317. https://doi.org/10.36681/tused.2025.015

Falloon, G. (2024). Computers & Education Advancing young students ’ computational thinking : An investigation of structured curriculum in early years primary schooling. Computers & Education, 216(1), 1–21. https://doi.org/10.1016/j.compedu.2024.105045

González, J. R., Sánchez, N. S., Pujol, I. S., & José, L. (2025). Challenges and perspectives in the evolution of distance and online education towards higher technological environments. Cogent Education, 12(1), 1–14. https://doi.org/10.1080/2331186X.2024.2447168

Haroud, S., & Saqri, N. (2025). Generative AI in Higher Education: Teachers’ and Students’ Perspectives on Support, Replacement, and Digital Literacy. MDPI: Education Sciences, 15(4), 1–15. https://doi.org/10.3390/educsci15040396

Huang, Y., & Khabusi, S. P. (2025). Artificial Intelligence of Things (AIoT) Advances in Aquaculture: A Review. MDPI: Processes, 13(73), 1–47. https://doi.org/10.3390/pr13010073

Ibeh, L., Cheruiyot, N., Mercy, O., & Manh, N. (2025). Exploring perspectives on ChatGPT integration in education: A student-centered study of benefits, concerns, and global implications for responsible AI integration. Research in Learning Technology, 33(1), 1–16. http://dx.doi.org/10.25304/rlt.v33.3384

Jwair, A. A. Bin. (2025). Generative artificial intelligence in higher education : Students ' journey through opportunities, challenges, and the horizons of academic transformation. Cogent Education, 12(1), 1–15. https://doi.org/10.1080/2331186X.2025.2589495

Kilgour, J., Moore, J., Molenaar, I., & Bannert, M. (2022). Towards investigating the validity of the measurement of self-regulated learning based on trace data. Metacognition and Learning, 17(1), 949–987. https://doi.org/10.1007/s11409-022-09291-1

Kokkonen, T., & Schalk, L. (2021). One Instructional Sequence Fits all ? A Conceptual Analysis of the Applicability of Concreteness Fading in Mathematics, Physics, Chemistry, and Biology Education. Educational Psychology Review, 33(1), 797–821. https://doi.org/10.1007/s10648-020-09581-7

Laer, S. Van, & Elen, J. (2017). In search of attributes that support self-regulation in blended learning environments. Educ Inf Technol, 22(1), 1395–1454. https://doi.org/10.1007/s10639-016-9505-x

Levy-nadav, L., Shamir-inbal, T., & Blau, I. (2025). Digital Competencies for Effective GenAI Use in Secondary Schools : A Longitudinal Exploration of Teachers ’ Perspectives and Classroom Practices. Journal of Computer Assisted Learning, 41(1), 1–18. https://doi.org/10.1111/jcal.70123

Long, D., & Magerko, B. S. (2020). What is AI Literacy ? Competencies and Design Considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, April 1–16. https://doi.org/10.1145/3313831.3376727

Lozano, A., & Fontao, C. B. (2023). Is the Education System Prepared for the Irruption of Artificial Intelligence? A Study on the Perceptions of Students of Primary Education Degree from a Dual Perspective: Current Pupils and Future Teachers. MDPI: Education Sciences, 13(733), 1–12. https://doi.org/10.3390/educsci13070733

Maries, A., & Singh, C. (2023). Education Sciences: Helping Students Become Proficient Problem Solvers Part I : MDPI: Education Sciences, 13(156), 1–21. https://doi.org/10.3390/educsci13020156

Munfaridah, N., Avraamidou, L., & Goedhart, M. (2021). The Use of Multiple Representations in Undergraduate Physics Education : What Do we Know and Where Do we Go from Here ? EURASIA Journal of Mathematics, Science and Technology Education, 17(1), 1–19. https://doi.org/10.29333/ejmste/9577

Muñoz, J. A. S., Flores-Eraña, G., Silva-Campos, J. M., Chavira-Quintero, R., & Olais-Govea, J. M. (2025). GenAI as a cognitive mediator : a critical-constructivist inquiry into computational thinking in pre-university education. Front. Educ, 1(1), 1–19. https://doi.org/10.3389/feduc.2025.1597249

Mwakalinga, S. E., & Mabilika, F. A. (2025). Perceptions, pitfalls, and proposals for the ethical use of artificial intelligence in the classroom : a case study of students and educators ( teachers ' and lecturers '). Cogent Education, 12(1). https://doi.org/10.1080/2331186X.2025.2557611

Namatovu, A., & Kyambade, M. (2025). Leveraging AI in academia: university students' adoption of ChatGPT for writing coursework (take-home) assignments through the lens of UTAUT2. Cogent Education, 12(1), 1–21. https://doi.org/10.1080/2331186X.2025.2485522

Nazari, A., Rajesh, M., Antoun, I., Sheeraz, M., Azhar, M., & Hayat, M. (2024). The Student Grand Round : A Peer Teaching Initiative. Cureus, 16(5), 1–6. https://doi.org/10.7759/cureus.60976

Ng, D. T. K., Wu, W., Leung, J. K. L., Chiu, T. K. F., & Chu, S. K. W. (2024). Design and validation of the AI literacy questionnaire : The affective, behavioral, cognitive, and ethical approach. British Journal of Education Technology, 1(1), 1082–1104. https://doi.org/10.1111/bjet.13411

Picardal, M. T. (2025). Utilization of AI-Driven Smart Prompts in Academic Research in Higher Education Institutions. International Journal of Learning, Teaching and Educational Research, 24(9), 384–404. https://doi.org/10.26803/ijlter.24.9.19

Reyes, K. C., Perez-Hernandez, E., & Cerrillo, P. R. (2025). Critical Digital Literacy in nonformal educational spaces. Digital Education Review, 47(1), 29–43. https://doi.org/10.1344/der.2025.47.29-43

Riwayani, S., Harahap, RD. (2022). Does Blended Learning Improve Student’s Learning dependence during the Covid-19 Pandemic? Evidence from a Labuhanbatu University, North Sumatera. : Jurnal Kependidikan. 8 (1), DOI: https://doi.org/10.33394/jk.v8i1.4509

Saputra, A., Harahap, RD. (2022). An Analysis of Student Learning Challenges in Elementary School Science Subject. Jurnal Kependidikan. 8 (1), DOI: https://doi.org/10.33394/jk.v8i1.4508

Shoval, D. H. (2025). Artificial Intelligence in Higher Education : Bridging or Widening the Gap for Diverse Student Populations ? MDPI: Education Sciences, 15(5), 1–24. https://doi.org/10.3390/educsci15050637

Stasio, M. Di, & Miotti, B. (2024). Education Sciences: Intelligent Agents at School — Child – Robot Interactions as an Educational Path. MDPI: Education Sciences, 14(774), 1–15. https://doi.org/10.3390/educsci14070774

Tadesse, T., Asmamaw, A., Getachew, K., Ferede, B., Melese, W., Siebeck, M., & Fischer, M. R. (2022). Education Sciences Self-Regulated Learning Strategies as Predictors of Perceived Learning Gains among Undergraduate Students in Ethiopian Universities. MDPI: Education Sciences, 12(468), 1–17. https://doi.org/10.3390/educsci12070468

Tafazoli, D. (2024). Critical Appraisal of Artificial Intelligence-Mediated Communication in Language Education. Innovations and Applications of Technology in Language Education, 1(1), 1–34. https://doi.org/10.48550/arXiv.2305.11897

Tiernan, P., Costello, E., Donlon, E., Parysz, M., & Scriney, M. (2023). Information and Media Literacy in the Age of AI: Options for the Future. MDPI: Education Sciences, 13(906), 1–11. https://doi.org/10.3390/educsci13090906

Wang, P., Liu, T., Yang, Y., & Xiang, X. (2025). Optimizing self- ­ regulated learning : A methods study on GAI ’ s impact on undergraduate task strategies and metacognition. British Journal of Education Technology, 1(1), 1–20. https://doi.org/10.1111/bjet.70018

Xie, H., Zhang, G., & Yan, R. (2025). Students' s acceptance of artificial intelligence eBooks using LCA and SEM : a case study of a medical book in China. Frontiers in Ecology and Evolution, 2(2), 1–12. https://doi.org/10.3389/feduc.2025.1683176

Yang, W. (2022). Computers and Education : Artificial Intelligence Artificial Intelligence education for young children : Why, what, and how in curriculum design and implementation. Computers and Education: Artificial Intelligence, 3(1), 1–7. https://doi.org/10.1016/j.caeai.2022.100061

Yim, I. H. Y., & Su, J. (2025). Artificial intelligence literacy education in primary schools : a review. International Journal of Technology and Design Education, 35(5), 2175–2204. https://doi.org/10.1007/s10798-025-09979-w

Zammit, M., Voulgari, I., Liapis, A., & Yannakakis, G. N. (2022). Learn to Machine Learn via Games in the Classroom. Frontiers in Education, 7(1), 1–13. https://doi.org/10.3389/feduc.2022.913530

Zeivots, S., Casey, A., Winchester, T., & Webster, J. (2025). Reshaping Higher Education Designs and Futures : Postdigital Co ‑ design with Generative Artificial Intelligence. Postdigital Science and Education, 7(4), 1334–1374. https://doi.org/10.1007/s42438-025-00595-4




DOI: https://doi.org/10.36987/jes.v13i2.8549

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