Adapting Python Programming Teaching for AI integration: Flipped classroom and assessment innovations in business analytics

This paper explores the transformative impact of artificial intelligence (AI) on teaching Python programming in a business school context, focusing on the BUSN7980 Data Intelligence in Practice module at the University of Kent. With AI tools like Google Colab becoming widely accessible, traditional teaching methods centered on basic syntax instruction are no longer sufficient or necessary. Instead, this study advocates for embracing AI as a pedagogical tool, shifting the focus toward real-world applications, critical thinking, and practical problem-solving.

A flipped classroom model was implemented, where foundational Python concepts were delivered through pre-recorded videos, allowing in-class time to be dedicated to AI-assisted data analysis and case studies. This approach is supported by cognitive load theory and social constructivist learning principles, which emphasize efficient cognitive resource allocation and scaffolded learning.

Evaluation through quantitative module feedback revealed a high student satisfaction score of 3.9 out of 4, complemented by qualitative comments highlighting increased engagement, autonomy, and confidence. Thematic analysis of student reflections further confirmed the benefits of integrating AI into teaching.

The findings suggest that educators should no longer seek to ban AI use but instead guide students in leveraging these tools effectively. This pedagogical shift prepares students for the evolving demands of the business analytics profession and offers a practical model for AI-augmented education.