Transforming group work: the impact of generative AI integration in an introductory research methods course

Irem Bezcioğlu-Göktolga et al.

The Journal of Research in Innovative Teaching & Learning2025https://doi.org/10.1108/jrit-08-2025-0198article
AJG 1
Weight
0.50

What the paper says

Purpose This study has a twofold purpose. First, it aims to present the redesign of an existing research skills course and integrate artificial intelligence literacy and collaborative skills into formative group assignments. Second, it seeks to explore how students approach the use of generative AI (GenAI) in research design within group assignments. Design/methodology/approach This study employs a mixed-methods approach. It integrates course redesign including learning goals, didactic approach and assessment, with qualitative insights from focus groups and quantitative feedback from mini-surveys. Findings The course redesign resulted in revised learning objectives that emphasized the importance of responsible research, GenAI tools and collaborative skills in the domains of knowledge, skills and character. It further led to the implementation of activities such as a lecture on responsible research, e-module on GenAI and alignment of assessments with the learning objectives, which included a series of group and individual assignments. Data showed that students gained knowledge and skills regarding the use of GenAI in research design and were critical when it came to taking initiative in the use of these tools in group work. Originality/value This study goes beyond merely recommending possible uses of GenAI in group work. Instead, it integrates GenAI into course redesign, describes the process of adjusting learning objectives, teaching activities and assessment and the empirical data presents how students experienced its implementation. It provides new insights into the use of GenAI in group work.

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https://doi.org/https://doi.org/10.1108/jrit-08-2025-0198

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@article{irem2025,
  title        = {{Transforming group work: the impact of generative AI integration in an introductory research methods course}},
  author       = {Irem Bezcioğlu-Göktolga et al.},
  journal      = {The Journal of Research in Innovative Teaching & Learning},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1108/jrit-08-2025-0198},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.