Back to the Future: Navigating the AI Landscape with Interactive Oral Assessments

Authors

• Shahper Richter, University of AucklandFollow
• Marilyn Giroux, Laval University
• Erica Brady, Monash University
• Angela Cruz, Monash University
• Patrick Dodd, University of Auckland
• Peter Wagstaff, Monash University
• Inna Piven, University of Auckland

Author ORCID Identifier

Shahper Richter: https://orcid.org/0009-0006-6445-0977

Marilyn Giroux: https://orcid.org/0000-0001-5764-0533

Erica Brady: https://orcid.org/0009-0003-6298-3495

Angela Cruz: https://orcid.org/0000-0002-8977-6088

Peter Wagstaff: https://orcid.org/0000-0002-6998-7494

Abstract

As higher education undergoes rapid digital transformation, accelerated by Education 4.0 technologies and emergence of generative Artificial Intelligence (AI) tools, particularly large language models (LLMs), traditional assessment paradigms, particularly standardized exams and essays, face increasing challenges. These tools perform tasks previously used to measure student knowledge, reasoning, and higher-order skills, calling into question assessment validity and integrity. This paper addresses the urgent need for authentic, AI-resilient evaluation methods by presenting Interactive Oral Assessments (IOAs) as a pedagogically robust alternative. IOAs enable dynamic, dialogic evaluation that fosters deep learning, critical thinking, communication skills, and real-world readiness, capabilities that AI struggles to replicate. Drawing on empirical evidence from multi-institutional case studies, this research demonstrates how IOAs enhance academic integrity, equity, student engagement, and academic rigor, while addressing scalability and feasibility. The primary contribution is a validated “3Ps” implementation blueprint (Preparing Learners, Preparing Assessors, Preparing Processes), offering step-by-step guidance for designing, piloting, and scaling IOAs. Theoretically, the study illustrates how social constructivist principles can be operationalized to support scalable, authentic assessment. By integrating empirical evidence, practical strategies, and learner-centered design, this paper provides a timely, actionable roadmap for higher education institutions seeking to maintain integrity and foster higher-order skills in AI-augmented learning environments.

Recommended Citation

Richter, S., Giroux, M., Brady, E., Cruz, A., Dodd, P., Wagstaff, P., & Piven, I. (In press). Back to the Future: Navigating the AI Landscape with Interactive Oral Assessments. Communications of the Association for Information Systems, 58, pp-pp. Retrieved from https://aisel.aisnet.org/cais/vol58/iss1/69