Pedagogical Design for Authentic Assessment of Learning in the Dawn of the Generative AI Era [Abstract]

Aim/Purpose This paper showcases a blended subject of a postgraduate degree in an Australian university, where content delivery and assessment practices were combined to enhance student engagement, peer learning, and to assure authentic student assessment. Background As generative AI emerged around 2022, it forced a transformation of pedagogical practices in higher education, including assessment. In particular, concerns over assuring assessment authenticity required a redesign of delivery modes as well. Methodology The article shares insights based on the subject coordinator’s reflection after delivering the subject five times. Contribution The paper shares interrelated pedagogical practices for encouraging student learning while assuring assessment authenticity. Findings The learning design includes scaffolding through individual and group micro-assessments, and the authenticity of assessment is assured through content requirements, group accountability, and in-class discussions. Recommendations for Practitioners Educators seeking to engage students in learning and assure the authentic of their assessment could adopt elements this interrelated subject design. Recommendations for Researchers Researchers should be critical of reported student performance since 2022 given the proliferation of GenAI, and assessment methods should be taken into account. Impact on Society Using this learning design can address concerns over effective student learning in higher education, producing graduates better equipped for critical thinking and analysis of GenAI outputs. Future Research Future research should examine the effectiveness of this design and compare it with other designs.