Teaching Artificial Intelligence and Machine Learning to Non-Major Students at University: A Scoping Review (Stage 2, 1:50 PM)

• In Event: e-Lightning Ed-Talk Session 18 - Stage 2

Abstract

Considering the crucial role of AI/ML and the scarcity of instructional guidelines outside of computer science, we evaluated AI/ML instruction at the university level, specifically for non-specialized students. We reviewed 24 journal articles, nine conference papers, and three book chapters published from 2010 onward, gathered from seven databases. Findings indicate several areas for improvement: (a) studies predominantly focused on AI/ML literacy and AI/ML models that are accessible for non-major learners, (b) there are plenty of technological tools and platforms that can be used in AI/ML education, (c) student-centered pedagogical approaches are frequently adopted in the courses and majority of studies rely solely on student surveys rather than assessing core learning outcomes, and (d) studies often lack a rigorous research design.

Authors

• Oguz Koklu, Bogazici University

• Muhammet Şahal, Yildiz Technical University

• Merve Dede, İstanbul Beykent University