Exploring students’ perceptions and experiences of adopting generative artificial intelligence in OER-enabled pedagogy

With the increasing adoption of generative artificial intelligence (GenAI) in higher education, this qualitative research aimed to explore students’ perceptions and experiences of using GenAI in OER-enabled pedagogical practices. We collected qualitative data from multiple sources, including online surveys, individual interviews, reflection essays, and chat transcripts. Eighteen students from two graduate-level courses participated in this study. The research findings showed that students perceived the use of GenAI in OER-enabled pedagogy favourably and encountered both opportunities and challenges. Guided by the Five-Circle Framework, four themes emerged to address students’ perceived opportunities, including 1) GenAI as a personal learning assistant to produce adaptive open knowledge, 2) GenAI as a co-creator of contextually diverse OERs, 3) OER-enabled participatory practices to increase AI acceptance and readiness, and 4) student agency to develop higher-order thinking skills. They also experienced some challenges and concerns, including 1) multifaceted inequality issues and barriers, 2) technical deficiencies and distrust of GenAI, 3) the lack of human elements and interactions, and 4) the limitations of adopted OERs. We concluded by discussing the implications of adopting GenAI to enhance the effectiveness of OER-enabled pedagogy from the macro, meso, and micro perspectives.

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Publication Details

Journal
Open Learning The Journal of Open Distance and e-Learning
Published
2026-06-29
DOI
https://doi.org/10.1080/02680513.2026.2692919
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Exploring students’ perceptions and experiences of adopting generative artificial intelligence in OER-enabled pedagogy

Tian Luo, Xinyue Ren, Rita Detrick
Open Learning The Journal of Open Distance and e-Learning
Artificial Intelligence in Healthcare and Education
article

Exploring students’ perceptions and experiences of adopting generative artificial intelligence in OER-enabled pedagogy

Tian Luo, Xinyue Ren, Rita Detrick
article en

Abstract

With the increasing adoption of generative artificial intelligence (GenAI) in higher education, this qualitative research aimed to explore students’ perceptions and experiences of using GenAI in OER-enabled pedagogical practices. We collected qualitative data from multiple sources, including online surveys, individual interviews, reflection essays, and chat transcripts. Eighteen students from two graduate-level courses participated in this study. The research findings showed that students perceived the use of GenAI in OER-enabled pedagogy favourably and encountered both opportunities and challenges. Guided by the Five-Circle Framework, four themes emerged to address students’ perceived opportunities, including 1) GenAI as a personal learning assistant to produce adaptive open knowledge, 2) GenAI as a co-creator of contextually diverse OERs, 3) OER-enabled participatory practices to increase AI acceptance and readiness, and 4) student agency to develop higher-order thinking skills. They also experienced some challenges and concerns, including 1) multifaceted inequality issues and barriers, 2) technical deficiencies and distrust of GenAI, 3) the lack of human elements and interactions, and 4) the limitations of adopted OERs. We concluded by discussing the implications of adopting GenAI to enhance the effectiveness of OER-enabled pedagogy from the macro, meso, and micro perspectives.

Open Learning The Journal of Open Distance and e-Learning
Dominion University College (GH), Old Dominion University (US)
Quality Education
Openalex Percentile: Top 11%
Artificial Intelligence in Healthcare and Education
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Exploring students’ perceptions and experiences of adopting generative artificial intelligence in OER-enabled pedagogy — Tian Luo, Xinyue Ren, et al. · Open Learning The Journal of Open Distance and e-Learning (2026) | TGRS Research Map | TGRS