Improvement of Computer Science Student's Online Search by Metacognitive Instructions

Sergey Sakulin; Alexander Alfimtsev; Yuri Kalgin

doi:10.28991/ESJ-2025-SIED1-03

Authors

Sergey Sakulin
sakulin@bmstu.ru
Institute of Informatics and Control Systems, Bauman Moscow State Technical University, Moscow 105005, Russian Federation http://orcid.org/0000-0001-9218-9725
Alexander Alfimtsev Institute of Informatics and Control Systems, Bauman Moscow State Technical University, Moscow 105005, Russian Federation
Yuri Kalgin Institute of Informatics and Control Systems, Bauman Moscow State Technical University, Moscow 105005, Russian Federation

Vol. 9 (2025): Special Issue "Emerging Trends, Challenges, and Innovative Practices in Education"

Special Issue "Emerging Trends, Challenges, and Innovative Practices in Education"

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The purpose of this study is to evaluate the improvement of computer science students' online searches by using metacognitive instructions. These instructions in the form of flowcharts with detailed descriptions help students to plan, monitor, and evaluate their actions when searching for scientific and technical information. The research methods include the analysis of existing applications of metacognitive instructions and conceptual models of search in the learning process. To carry out the experiment, we designed a tutorial that contains the described metacognitive instructions with a detailed search plan. During the experiment, students had the task of writing the review sections of their term or final papers using the tutorial. The results were evaluated based on the quality of the submitted reviews and tutor feedback. The students using metacognitive instructions significantly improved the quality of the review sections. The structure of review sections improved, and the analysis of sources became more rigorous with more precise keyword phrasing. The study confirms that the use of metacognitive instructions enhances information search and academic performance. The novelty of the study lies in the integration of the metacognitive approach with conceptual search models into the learning process of computer science students. The improvements can be adapted to other disciplines to expand the study to other academic areas and develop additional tools to support metacognitive learning.

Doi: 10.28991/ESJ-2025-SIED1-03

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Sakulin, S., Alfimtsev, A., & Kalgin, Y. (2025). Improvement of Computer Science Student’s Online Search by Metacognitive Instructions. Emerging Science Journal, 9, 39–55. https://doi.org/10.28991/ESJ-2025-SIED1-03

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Improvement of Computer Science Student's Online Search by Metacognitive Instructions

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