Collaborative Learning Supported by Generative Artificial Intelligence and Rotation Station Model

The paper explores the effectiveness of integrating Generative AI and the ‘station rotation’ model of blended learning to support students' collaborative learning activities. The theoretical basis of the study was the theory of social constructivism. The study employed a triangulation of predominantly qualitative methods, incorporating a qualitative experiment based on the lesson study method, direct observation, and an online survey. A total of 189 students majoring in teacher education participated in the study. The data from the student evaluation of teaching, online survey, students' academic performance, and students' reflection on the classes were analysed to derive the study's results. The findings indicate that the integration of GenAI and the ‘station rotation’ model enhances student engagement in learning, fosters the development of skills in utilising digital tools and AI services, and leads to an improvement in academic performance.

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Publication Details

Published
2025-05-14
DOI
https://doi.org/10.1109/icaie64856.2025.11158520
Primary Topic
Educational Technology and Assessment
Type
article
Field-Weighted Citation Impact
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article

Collaborative Learning Supported by Generative Artificial Intelligence and Rotation Station Model

Elena Chernobay, Madina Davlatova
Educational Technology and Assessment
article

Collaborative Learning Supported by Generative Artificial Intelligence and Rotation Station Model

Elena Chernobay, Madina Davlatova
article en

Abstract

The paper explores the effectiveness of integrating Generative AI and the ‘station rotation’ model of blended learning to support students' collaborative learning activities. The theoretical basis of the study was the theory of social constructivism. The study employed a triangulation of predominantly qualitative methods, incorporating a qualitative experiment based on the lesson study method, direct observation, and an online survey. A total of 189 students majoring in teacher education participated in the study. The data from the student evaluation of teaching, online survey, students' academic performance, and students' reflection on the classes were analysed to derive the study's results. The findings indicate that the integration of GenAI and the ‘station rotation’ model enhances student engagement in learning, fosters the development of skills in utilising digital tools and AI services, and leads to an improvement in academic performance.

National Research University Higher School of Economics (RU), Institute of International Business Education (RU)
Openalex Percentile: Top 62%
Educational Technology and Assessment
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