DEVELOPMENT OF METACOGNITIVE ABILITY FOR ADEQUATE SELF-ASSESSMENT OF STUDENTS' LEARNING ACTIVITIES IN THE CONDITIONS OF ONLINE LEARNING AND THE USE OF AI
DOI:
https://doi.org/10.34142/23129387.2026.75.29Keywords:
metacognitive ability, adequate self-assessment, online learning, artificial intelligence (AI), self-management of learning, reflection, critical thinking, environment (digital educational environment)Abstract
Relevance of the study. The article investigates the problem of developing metacognitive abilities for adequate self-assessment of students' educational activities in the context of online learning and active use of artificial intelligence (AI) technologies. The relevance of the study is due to the increasing role of students' independent work, the need to manage the individual learning process, which requires constant reflection, planning and self-control, as well as the spread of the practice of using AI when performing educational tasks.
The purpose of the study is to theoretically and practically substantiate the methods of organizing students' educational and cognitive activities aimed at developing metacognitive abilities for adequate self-assessment and self-management of learning in a digital educational environment.
Results. The study uses theoretical and methodological analysis of scientific sources, systematization, generalization and analysis of approaches to the use of AI in the educational process. The main advantages and risks of using AI when performing independent and creative open-ended tasks are identified. It is shown that uncritical or excessive use of AI can cause a discrepancy between the real level of formation of the student's competencies and his perception of his own capabilities, reduce the diagnostic value of the results of independent work, weaken the connection between his own efforts, results and self-assessment, and also postpone the development of critical thinking and reflective skills. At the same time, it is substantiated that with pedagogically appropriate use, AI can serve as a tool to support self-assessment, reflection and self-management of educational activities.
The directions of using AI as a means of comparing and self-analysis of one's own answers, identifying errors and gaps in knowledge, organizing reflective dialogue, forming self-assessment criteria, determining the individual zone of further development and critical analysis of one's own argumentation are proposed (Sergeyeva, et al. 2022, Sergeyeva, et al, 2023).
It is proved that AI can act as a means of developing reflection and adequate self-assessment. This approach allows integrating AI into the educational process without replacing the student's independent cognitive activity and creates conditions for the development of adequate self-assessment, critical thinking, reflection and self-management of learning.
Downloads
References
Alhazbi, S. (2024). Using learning analytics to measure self-regulated learning: A systematic review of empirical studies in higher education. Journal of Computer Assisted Learning. https://doi.org/10.1111/jcal.12982
Guan, R., Raković, M., Chen, G., & Gašević, D. (2025). How educational chatbots support self-regulated learning? A systematic review of the literature. Education and Information Technologies, 30, 4493–4518. https://doi.org/10.1007/s10639-024-12881-y
Essien, A., Bukoye, O. T., O’Dea, X., & Kremantzis, M. (2024). The influence of AI text generators on critical thinking skills in UK business schools. Studies in Higher Education, 49(5), 865–882. https://doi.org/10.1080/03075079.2024.2316881
Lin, T. J., et al. (2024). A scoping review on how generative artificial intelligence transforms assessment in higher education. International Journal of Educational Technology in Higher Education. https://doi.org/10.1186/s41239-024-00468
Urban, M., Děchtěrenko, F., Lukavský, J., Hrabalová, V., Svacha, F., Brom, C., & Urban, K. (2024). ChatGPT improves creative problem-solving performance in university students: An experimental study. Computers & Education, 215, 105031. https://doi.org/10.1016/j.compedu.2024.105031
Sergeyeva, T., Bronin, S., & Turlakova, N. (2022). Multidisciplinary dimension of e-learning in the innovative eco-system of a modern university. 2022 International Conference on Smart Information Systems and Technologies (SIST), 251–259. https://doi.org/10.1109/SIST54437.2022.9945768
Sergeyeva, T. (2017). Tekhnika indyvidualizatsii E-kursiv navchannia [Individualising technique of e-training courses]. In Kharkivskyi osinnii marafon psykhotekhnolohii: Materialy naukovo-praktychnoi konferentsii [Kharkiv Autumn Marathon of Psychotechnologies: Proceedings of the Scientific and Practical Conference] (Kharkiv, October 28, 2017) (p. 108). Kharkiv: Vydavnytstvo «Disa plius».
Sergeyeva, T., Bronin, S., Turlakova, N., & Iamnytskyi, S. (2023). Integrating educational components into the metaverse. In Innovative Approaches to Technology-Enhanced Learning for the Workplace and Higher Education (pp. 412–425). Springer. https://doi.org/10.1007/978-3-031-21569-8_39
Turlakova, N. (2015). Metodyka rozrobky navchalnykh materialiv dlia e-learning [Methodology for developing educational materials for e-learning]. In Suchasnyi pidkhid do upravlinnia yakistiu pidhotovky fakhivtsiv v umovakh tekhnichnoho universytetu: Materialy 70-i naukovo-metodychnoi konferentsii [Modern approach to quality management of specialist training in a technical university: Proceedings of the 70th Scientific and Methodological Conference] (pp. 91–94). Kharkiv: Kharkiv National University of Civil Engineering and Architecture.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
