LEVERAGING GENERATIVE AI FOR PERSONALIZING FORMATIVE ASSESSMENT IN HIGHER EDUCATION
Abstract
This article explores the role of generative artificial intelligence (GenAI) in personalizing formative assessment in higher education. It examines how AI can provide individualized tasks, immediate feedback, and learning recommendations based on students’ needs. The study also highlights challenges such as academic integrity, data privacy, AI accuracy, and the importance of teacher supervision. The findings indicate that responsible use of GenAI can improve the effectiveness and flexibility of formative assessment.
References
1. Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., et al. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274.
2. Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – Where are the educators? International Journal of Educational Technology in Higher Education, 16, 39.
3. UNESCO. (2023). Guidance for Generative AI in Education and Research. Paris: UNESCO.
4. Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence Unleashed: An Argument for AI in Education. London: Pearson.
5. Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112.
6. Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1), 7–74.
7. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Boston: Center for Curriculum Redesign.
