E96 Beyond Academic Integrity: GenAI Assessment (Short paper) Proceedings of the 21st Chais Conference for the Study of Innovation and Learning Technologies: Learning in the Digital Era I. Blau, A. Caspi, Y. Eshet-Alkalai, N. Geri, Y. Kalman, D. Olenik-Shemesh, Y. Sidi, & N. Brandel (Eds.), Ra'anana, Israel: The Open University of Israel Beyond Academic Integrity: Mapping Educators' Assessment Challenges in the GenAI Era through the lens of the TPACK model (Short paper) Keren Taiter Technion – Israel Institute of Technology kerentaiter@gmail.com Rinat B. Rosenberg-Kima Technion – Israel Institute of Technology rinatros@technion.ac.il מעבר ליושרה אקדמית: מיפוי אתגרי ההערכה של אנשי חינוך בעידן הבינה המלאכותית היוצרת דרך עדשת מודל TPACK )מאמר קצר( רינת רוזנברג - קימה הטכניון – מכון טכנולוגי לישראל rinatros@technion.ac.il קרן טייטר הטכניון – מכון טכנולוגי לישראל kerentaiter@gmail.com Abstract The rapid integration of Generative Artificial Intelligence (GenAI) into higher education has reshaped learning and assessment. As students increasingly use GenAI for academic tasks, educators face a critical challenge: many traditional assessment formats no longer reliably capture authentic student understanding. In response, educators have begun to redesign their assessments to address this shift. Designing AI-aligned assignments can be a challenging task for educators. This study, therefore, explored the challenges educators face when designing assessments in the GenAI era. This study uses the TPACK (Technological, Pedagogical, and Content Knowledge) framework to explore the challenges educators face in redesigning assessments. Data included statements from workshop discussions involving 131 participants and questionnaire responses provided by 31 workshop participants and 31 additional respondents. The most significant difficulties emerged in the Technological Pedagogical Knowledge category. 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 concerns (TPACK) were less prominent. The findings suggest that meaningful assessment in the GenAI era depends less on controlling AI use and more on articulating clear pedagogical intentions that guide principled assessment design. Keywords: Assessment redesign, GenAI in higher education, TPACK framework.
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