Enhancing the Educational Process through AI and Gamified Learning

AI provides a wide range of tools for creating personalised learning paths and unlocking each student’s potential. The study aims to investigate the effectiveness of integrating AI tools into the educational process to form personalised learning paths. In the study context, the methods of self-assessment, analysis of learning outcomes, and statistical calculation of pedagogical experiment data processing were used. Criteria for the effectiveness of integrating AI into the educational process to develop personalised learning paths have been formed. Based on the outlined criteria and levels of their implementation, the most effective ones are identified through self-assessment. The tools for implementing these AI-based learning tools are outlined. The higher education students for whom the AI-based learning tools were used were divided into clusters according to their professional training: humanities, social sciences, and engineering. The pedagogical experiment compared the learning outcomes of the control group that used randomly selected AI tools and the experimental group that used AI-based learning tools, distributed according to the clusters of professional training. Based on the statistical comparison of learning outcomes, it was determined that the experimental group shows better results. Therefore, the preliminary analysis of AI-based learning tools and their further application by the clusters of professional training is practical.

Authors

Institutions

Publication Details

Journal
Metaverse Basic and Applied Research
Published
2025-06-02
DOI
https://doi.org/10.56294/mr2025164
Citations
1
Primary Topic
Educational Games and Gamification
Type
article
Field-Weighted Citation Impact
3.44
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article

Enhancing the Educational Process through AI and Gamified Learning

Микита Сапогов, Oleg Khairulin, N.A. Buniak, Маріанна Жумбей et al.
1 citations
Metaverse Basic and Applied Research
Educational Games and Gamification
3.44
article

Enhancing the Educational Process through AI and Gamified Learning

Микита Сапогов, Oleg Khairulin, N.A. Buniak, Маріанна Жумбей, Світлана Парфілова
article en
1 citations

Abstract

AI provides a wide range of tools for creating personalised learning paths and unlocking each student’s potential. The study aims to investigate the effectiveness of integrating AI tools into the educational process to form personalised learning paths. In the study context, the methods of self-assessment, analysis of learning outcomes, and statistical calculation of pedagogical experiment data processing were used. Criteria for the effectiveness of integrating AI into the educational process to develop personalised learning paths have been formed. Based on the outlined criteria and levels of their implementation, the most effective ones are identified through self-assessment. The tools for implementing these AI-based learning tools are outlined. The higher education students for whom the AI-based learning tools were used were divided into clusters according to their professional training: humanities, social sciences, and engineering. The pedagogical experiment compared the learning outcomes of the control group that used randomly selected AI tools and the experimental group that used AI-based learning tools, distributed according to the clusters of professional training. Based on the statistical comparison of learning outcomes, it was determined that the experimental group shows better results. Therefore, the preliminary analysis of AI-based learning tools and their further application by the clusters of professional training is practical.

Metaverse Basic and Applied ResearchVol. 4
West Ukrainian National University (UA), Sumy State Pedagogical University named after A. S. Makarenko (UA), Vinnytsia Mykhailo Kotsiubynskyi State Pedagogical University (UA), Vasyl Stefanyk Carpathian National University (UA), National University of Civil Protection of Ukraine (UA), National Defence University (PK)
Openalex Percentile: Top 9%
Educational Games and Gamification
3.44
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