Đổi mới hoạt động đánh giá học tập trong giáo dục đại học dưới tác động của AI tạo sinh
Tóm tắt
Generative AI challenges the authenticity and integrity of assessment in higher education. This study employs a structured theoretical review to analyze research on the impact of generative AI on academic assessment in higher education, comprising an analysis of 13 recent studies and 8 foundational documents. The synthesis identifies five themes and consolidates them into three shifts: from final products to product-process-justification evidence; from knowledge reproduction to application, critique, and verification; and from AI control to transparency, accountability, and student agency. The proposed conceptual framework combines process evidence, authentic tasks, critical evaluation of AI outputs, and transparent use. As it has not been empirically validated, applications should be adapted to learning outcomes, task types, disciplines, class size, technology access, and privacy requirements.
Tài liệu tham khảo
Alkouk, W. A., & Khlaif, Z. N. (2024). AI-resistant assessments in higher education: Practical insights from faculty training workshops. Frontiers in Education, 9, Article 1499495. https://doi.org/10.3389/feduc.2024.1499495
Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1), 7-74. https://doi.org/10.1080/0969595980050102
Black, P., & Wiliam, D. (2009). Developing the theory of formative assessment. Educational Assessment, Evaluation and Accountability, 21(1), 5-31. https://doi.org/10.1007/s11092-008-9068-5
Boud, D., & Falchikov, N. (Eds.). (2007). Rethinking assessment in higher education: Learning for the longer term. Routledge. https://doi.org/10.4324/9780203964309
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa
Chiu, T. K. F. (2024). The impact of generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and Midjourney. Interactive Learning Environments, 32(10), 6187-6203. https://doi.org/10.1080/10494820.2023.2253861
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228-239. https://doi.org/10.1080/14703297.2023.2190148
Farazouli, A., Cerratto-Pargman, T., Bolander Laksov, K., & McGrath, C. (2024). Hello GPT! Goodbye home examination? An exploratory study of AI chatbots’ impact on university teachers’ assessment practices. Assessment & Evaluation in Higher Education, 49(3), 363-375. https://doi.org/10.1080/02602938.2023.2241676
Foung, D., Lin, H. F., & Chen, S. W. J. (2024). Reinventing assessments with ChatGPT and other online tools: Opportunities for GenAI-empowered assessment practices. Computers and Education: Artificial Intelligence, 6, Article 100250. https://doi.org/10.1016/j.caeai.2024.100250
Furze, L., Perkins, M., Roe, J., & MacVaugh, J. (2024). The AI Assessment Scale (AIAS) in action: A pilot implementation of GenAI-supported assessment. Australasian Journal of Educational Technology, 40(4), 38-55. https://doi.org/10.14742/ajet.9434
Kizilcec, R. F., Huber, E., Papanastasiou, E. C., Cram, A., Makridis, C. A., Smolansky, A., Zeivots, S., & Raduescu, C. (2024). Perceived impact of generative AI on assessments: Comparing educator and student perspectives in Australia, Cyprus, and the United States. Computers and Education: Artificial Intelligence, 7, Article 100269. https://doi.org/10.1016/j.caeai.2024.100269
Lo, C. K. (2023). What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13(4), Article 410. https://doi.org/10.3390/educsci13040410
Moorhouse, B. L., Yeo, M. A., & Wan, Y. (2023). Generative AI tools and assessment: Guidelines of the world’s top-ranking universities. Computers and Education Open, 5, Article 100151. https://doi.org/10.1016/j.caeo.2023.100151
Nguyen, H. M., & Goto, D. (2024). Unmasking academic cheating behavior in the artificial intelligence era: Evidence from Vietnamese undergraduates. Education and Information Technologies, 29, 15999-16025. https://doi.org/10.1007/s10639-024-12495-4
Sadler, D. R. (1989). Formative assessment and the design of instructional systems. Instructional Science, 18(2), 119-144. https://doi.org/10.1007/BF00117714
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333-339. https://doi.org/10.1016/j.jbusres.2019.07.039
Sokhanvar, Z., Salehi, K., & Sokhanvar, F. (2021). Advantages of authentic assessment for improving the learning experience and employability skills of higher education students: A systematic literature review. Studies in Educational Evaluation, 70, Article 101030. https://doi.org/10.1016/j.stueduc.2021.101030
Torraco, R. J. (2005). Writing integrative literature reviews: Guidelines and examples. Human Resource Development Review, 4(3), 356-367. https://doi.org/10.1177/1534484305278283
Vlachopoulos, D., & Makri, A. (2024). A systematic literature review on authentic assessment in higher education: Best practices for the development of 21st century skills, and policy considerations. Studies in Educational Evaluation, 83, Article 101425. https://doi.org/10.1016/j.stueduc.2024.101425
Wiggins, G. (1990). The case for authentic assessment. Practical Assessment, Research, and Evaluation, 2(1), Article 2. https://doi.org/10.7275/ffb1-mm19
Xia, Q., Weng, X., Ouyang, F., Lin, T. J., & Chiu, T. K. F. (2024). A scoping review on how generative artificial intelligence transforms assessment in higher education. International Journal of Educational Technology in Higher Education, 21, Article 40. https://doi.org/10.1186/s41239-024-00468-z
Tải xuống
Đã Xuất bản
Cách trích dẫn
Số
Chuyên mục
Giấy phép
Bản quyền (c) 2026 Tạp chí Giáo dục
Tác phẩm này được cấp phép theo Ghi nhận tác giả của Creative Commons Giấy phép quốc tế 4.0 .
