Reimagining assessment in higher education: the role of artificial intelligence in student evaluation

Abstract

The technology of artificial intelligence (AI) is rapidly changing the way assessment is practiced in higher learning. Learning analytics, data-driven, intelligent feedback systems, automated marking, and AI-supported evaluation are changing the way the performance of students is assessed. Although these technologies have been quickly adopted, there is not much research investigating the experiences and perceptions of AI-mediated processes of assessments by students in real academic settings. Based on a socio-technical approach, the proposed qualitative study explores the perception of the students in the university concerning AI-supported evaluation and its effects on learning, assessment, and academic responsibility. The analysis builds around thematic examination of over 100 open-ended replies available as a result of a survey conducted among university students. The results show that AI-enhanced evaluation improves the immediacy of feedback, transparency, and consistency of the evaluation process. According to students, AI-generated feedback helps students to reflect, self-regulate, and engage in lifelong learning. Meanwhile, the participants raise the issue of algorithmic bias, a deficit of contextual knowledge, and the possible loss of human cognition in evaluation.