From perception to practice: Faculty-led assessment redesign in response to generative AI in higher education

Abstract

The rapid diffusion of Generative Artificial Intelligence (GenAI) tools such as ChatGPT into higher education has unsettled long standing assumptions about the validity, reliability, and authenticity of conventional assessment methods. Existing research has predominantly examined perceptions, ethical concerns, and technology acceptance, leaving the actual pedagogical redesign work of faculty, and its relationship to established principles of assessment quality, comparatively underexplored. Drawing on constructive alignment theory, this study examines how faculty are reshaping assessment design under conditions of AI disruption and whether their adaptation strategies address or fail to address core dimensions of assessment validity. A sequential explanatory mixed methods design was used across two phases: a survey of 180 faculty members across STEM and non STEM disciplines at a private institution in India, followed by semi structured interviews and assessment artefact analysis with a purposively selected subset of participants. The results show a marked shift away from unsupervised, product based assessment toward process oriented, reflective, and authentic formats, including oral examinations, project based tasks, in class problem solving, and reflective journals, an implicit faculty led re alignment of assessment with intended learning outcomes. Faculty frame GenAI simultaneously as a threat to assessment integrity and as a catalyst for pedagogical innovation, but institutional structures have not kept pace with this bottom up change, and increased workload, inconsistent guidance, and limited professional development persist as barriers to sustaining and scaling redesign. By empirically documenting faculty led transformation and connecting it explicitly to theories of assessment quality and institutional change, the study moves beyond descriptive accounts of GenAI's impact and offers practical guidance for educators, instructional designers, and institutional leaders seeking to formalise sustainable, valid, and equitable assessment redesign in the GenAI era.