Integrating Artificial Intelligence to support Online Assessment in Higher Education: Opportunities and Challenges for Cognitive and Practical Learning

Abstract

Artificial intelligence (AI) has profoundly transformed online assessment systems in higher education by making assessment practices more personalized, adaptive, and contextual. This article highlights the opportunities and challenges presented by AI-based online assessment, focusing on two complementary dimensions: cognitive assessment and authentic assessment. The first dimension focuses on modeling learners' mental processes through the analysis of responses, learning traces, and interaction patterns, enabling adaptive systems to generate personalized feedback, support metacognitive regulation, and ensure timely remediation. The authentic dimension emphasizes the assessment of skills in realistic or simulated professional contexts, where learners' actions and decisions provide rich evidence of procedural and relational skills. While these approaches offer promising prospects for improving validity and learner engagement, they also raise major methodological and ethical challenges related to reliability, fairness, transparency, and data protection. This contribution analyzes these challenges and proposes design principles for robust, ethical, and inclusive AI-based online assessment systems aligned with the skills required at the institutional, academic, and professional levels in the 21st century.