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Abstract
This rapid study explores teacher educators’ perceptions of generative artificial intelligence (GenAI) in teacher education, conducted through a descriptive survey involving 55 teacher educators from two colleges of education in Ghana. A convenience sampling technique was adopted for data collection, and a data analysis using exploratory factor analysis was used to identify primary factors shaping perceptions and preparedness of GenAI integration. Key findings reveal a generally positive perception among the teacher educators, who recognize GenAI’s potential to support academic achievement, increase student engagement, and improve communication within teacher education settings. The findings further indicate that the teacher educators’ background factors, such as age, years of teaching experience, department, and college, do not significantly predict their perceptions of GenAI. Since none of these measured background factors were significant predictors, this suggests that training and resources for using GenAI should be broadly prioritized, accessible, and not heavily tailored to specific demographic groups. However, the study identified significant concerns within the barriers and challenges factors, including ethical issues, fairness in student assessment, and possible adverse effects on the teacher educator-student relationship. The communication and independence factors highlight a need for professional development, with teacher educators emphasizing the importance of training in GenAI usage to optimize its educational potential. The study concludes that while teacher educators generally support GenAI’s potential benefits, there are essential ethical and practical challenges to address. Recommendations include establishing clear policies and guidelines to guide GenAI implementation and ensure ethical usage. We further recommend the expansion of this research with a larger sample to gather comprehensive insights from the teacher educators and their acceptance levels of GenAI.
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Article Type: Research Article
Journal of Digital Educational Technology, Volume 5, Issue 1, January 2025, Article No: ep2508
https://doi.org/10.30935/jdet/15887
Publication date: 28 Jan 2025
Article Views: 15702
Article Downloads: 7148
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