Generative AI, such as ChatGPT, is a disruptive technology with significant impacts on education. While it has the potential to transform the delivery and accessibility of education, it can also undermine educational effectiveness by facilitating academic honesty and creating technostress for educators. This study aims to (i) evaluate the extent to which Generative AI, such as ChatGPT, brings technostress to teachers and (ii) how Generative AI changes teachers' professional identities and the technostress that results from such changes. We hypothesize that techno-eustress and techno-distress are determined by three types of self-discrepancies concerning professional identity construction: actual-ought, actual-ideal, and ought-ideal discrepancies. This research uses a mixed-method approach with surveys and qualitative interviews. Our findings will contribute to the study of technostress in the educational context, as well as provide practical implications for policy-making, formulating regulations, and designing teacher professional development programs to alleviate educators' technostress created by advancement in Generative AI.


Paper Number 1519; Track e-Learning; Short Paper



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