E100 Beyond Academic Integrity: GenAI Assessment (Short paper) Discussion A qualitative analysis using the TPACK framework reveals that the primary challenges in assessment redesign lie within the Technological Pedagogical Knowledge (TPK) domain. Beyond the technical issue of detecting AI content, educators face deeper pedagogical struggles: maintaining academic integrity, teaching proper AI use, and designing creative, authentic assignments that promote deep learning. In contrast, technological difficulties (TK) and discipline-specific challenges (TPACK) were less prevalent. Two additional themes emerged: the significant time and effort required for redesign, and conversely, a lack of perceived difficulty among educators who likely do not perceive redesign assessment as difficult. The findings highlight a critical gap: while the technical adoption of GenAI is relatively easy, integrating it pedagogically is complex. The findings point to a growing need for pedagogical and assessment literacy that supports educators in designing meaningful assessments within AI-mediated learning environments. Rather than focusing solely on controlling or detecting AI use, educators must re-center assessment design around clear pedagogical intentions and principled decisions about how GenAI is positioned within learning and evaluation processes. References Chaudhry, I. S., Sarwary, S. A. M., El Refae, G. A., & Chabchoub, H. (2023). Time to revisit existing student’s performance evaluation approach in higher education sector in a new era of ChatGPT — A case study. Cogent Education, 10(1), 2210461. https://doi.org/10.1080/2331186X.2023.2210461 Hopfenbeck, T. N., Zhang, Z., Sun, S. Z., Robertson, P., & McGrane, J. A. (2023). Challenges and opportunities for classroom-based formative assessment and AI: A perspective article. Frontiers in Education, 8, 1270700. https://doi.org/10.3389/feduc.2023.1270700 Lee, D., Arnold, M., Srivastava, A., Plastow, K., Strelan, P., Ploeckl, F., Lekkas, D., & Palmer, E. (2024). The impact of generative AI on higher education learning and teaching: A study of educators’ perspectives. Computers and Education: Artificial Intelligence, 6, 100221. https://doi.org/10.1016/j.caeai.2024.100221 Lye, C. Y., & Lim, L. (2024). Generative artificial intelligence in tertiary eeducation: Assessment redesign principles and considerations. Education Sciences, 14(6), 569. https://doi.org/10.3390/educsci14060569 Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record: The Voice of Scholarship in Education, 108(6), 1017–1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x Winerö, E., & Modén, M. U. (2024). Engaging teachers in co-designing examinations for secondary schools in the era of large language models. In Proceedings of the International Workshop on Participatory Design & End-User Development (PDEUD 2024). CEUR Workshop Proceedings. https://ceur-ws.org/ Zhao, J., Chapman, E., Sabet, P. G. P. (2024). Generative AI and educational assessments: A systematic review. Education Research and Perspectives, 51, 124–155. https://doi.org/10.70953/ERPv51.2412006
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