Generative AI For Learning and Assessment

SUPERVISOR: Reza farrokhnia

The rapid advancement of generative artificial intelligence (GenAI) is reshaping the landscape of education, learning, and assessment (Farrokhnia et al., 2025). As these technologies become increasingly integrated into teaching and research practices, they offer new opportunities for personalized feedback, adaptive learning environments, and efficient assessment systems. At the same time, they raise complex questions concerning trust, ethics, literacy, and the evolving roles of teachers and students in AI-mediated learning contexts. The following proposed research topics explore diverse facets of this emerging field, focusing on how GenAI can enhance feedback processes, assessment practices, and learners’ critical engagement with AI technologies in higher education.

Reference

• Farrokhnia, M., Soleimani, S., & Noroozi, O. (2025). Generative AI in higher education: Transformative tools for research, teaching, and assessment. In S. Sabbaghan (Ed.), Navigating generative AI in higher education: Ethical, theoretical, and practical perspectives. Edward Elga. https://doi.org/10.4337/9781035337873.00007

Topics

Exploring hybrid intelligent feedback in education: Sequencing human (peer or teacher) and GenAI feedback for optimal learning perceptions

Acceptance of (Gen)AI grading in higher education: A discrete choice study among students and teachers

GenAI sensitivity to text quality in automated feedback

The development of (Gen)AI literacy among higher education students