An exploration of pedagogical approaches in teaching artificial intelligence courses: Experience from undergraduates students of Bangladesh

• Published in: Social sciences & humanities open 2024, Vol.10, p.101075, Article 101075
• Main Authors: Rufai, Ashiru Ahmad, Hossain Khan, Md Shahadat, Hasan, Mahbub
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Engineering education; Grounded theory; Instructional method; Teaching methods in AI
• ISSN: 2590-2911; 2590-2911
• DOI: 10.1016/j.ssaho.2024.101075

The increasing demand for skilled professionals in Artificial Intelligence (AI) within the Fourth Industrial Revolution (4IR) has led to the establishment of AI courses in universities worldwide. This study investigated effective pedagogical approaches in an AI course through in-depth interviews with eighteen undergraduate students in Bangladesh. Grounded theory methodology was employed, resulting in the development of five thematic categories: the significance of feedback, combination of theory and practice, promotion of self-paced learning, connection to real-life problems, and integration with future education and emerging technologies. The findings highlight the importance of these pedagogical approaches in enhancing students' learning outcomes. The study's implications include informing the design of professional development programs for AI teachers to improve instructional methods and learning outcomes. The proposed “Holistic Framework for Teaching and Learning in Emerging AI Courses” combines these five categories to provide practical guidance for instructors in the global context of AI education.