A qualitative inquiry on redefining students' assessments in the age of artificial intelligence: academicians' viewpoint

Abstract

Artificial Intelligence (AI) presents new opportunities and challenges, and its adoption has transformed learning and development for students. Current studies have mostly explored the use of AI among students, with very little emphasis on its impact on teaching and learning tasks, academicians' professional identities, and student-teacher interaction. This research examines the pedagogical, professional, and institutional implications of students' use of AI from the perspective of academic staff at private universities in Malaysia. A structured interview protocol with ten open-ended questions was adopted to implement the qualitative exploratory research design. The final sample consisted of 18 academicians with at least 5 years of teaching experience in higher education and who have been involved in assessing undergraduate, master's, and postgraduate students' assignments. Data were analyzed through open coding, axial coding, and thematic analysis. The results identified six interrelated themes: (1) workload intensification and assessment burden; (2) changes in educators' roles; (3) transformation of the educator's professional identity; (4) pedagogical adaptations and assessment redesign; (5) challenges of academic integrity and AI detection; and (6) finally, coping strategies, institutional support, and future readiness. AI use by pupils is transforming academic tasks by adding workload for teachers, necessitating new roles for teachers as “gatekeepers of academic quality”, and creating tensions around identity issues for teachers. Behaviours such as adaptive teaching, redesigning assessments, seeking greater institutional support and clearer governance, and requiring AI education programs are prominent for academicians. The study contributes to the existing literature on generative AI in higher education by demonstrating that the implications of AI-supported learning extend beyond academic integrity to encompass changes in academic processes, teaching roles, and institutional practices. The study provides novel insights from the firsthand experiences of academicians witnessing this paradigm shift in the higher-education context. The results offer practical guidance for institutions aiming to establish responsible AI governance and sustainable assessment practices in the growing AI-driven learning landscape.