Abstract:

The rapid emergence of Generative Artificial Intelligence (GenAI) has prompted renewed debate around its impact on introductory programming education, particularly regarding students’ ability to generate professional-quality code with minimal conceptual understanding. While concerns persist that such capabilities may undermine foundational programming instruction, this paper argues that GenAI, when intentionally integrated, has the potential to strengthen rather than replace the development of core programming competencies and critical thinking skills.

Using a practitioner-oriented design-based research (DBR) method, this paper proposes a structured pedagogical framework for incorporating GenAI as a cognitive amplifier in introductory programming courses. The methodology draws on established learning theories and recent empirical insights to conceptualise how GenAI can provide immediate error explanations, iterative debugging support, and scalable formative feedback. To illustrate this proposed methodology, the paper presents two detailed, comparative lesson-plan case studies (“pre-GenAI” and “post-GenAI”) addressing foundational programming topics such as variables, branching, functions, and refactoring. These case studies are used not as evaluated interventions but as conceptual demonstrations of how learning and teaching practices may evolve when GenAI is embedded deliberately and transparently into classroom and laboratory settings.

Rather than reporting empirical results, the paper outlines anticipated pedagogical benefits, including improved accessibility of feedback, increased emphasis on reasoning over syntax, and enhanced transparency in assessment, as hypotheses for future research. The paper also identifies key risks such as hallucinations, over-reliance, inequitable access, and academic integrity, offering recommendations for responsible integration and highlighting the need for longitudinal empirical evaluation.

This work contributes a theoretically grounded and practically oriented framework that invites further study into how GenAI can be harnessed to support, rather than supplant, foundational programming education.

Keywords:

Generative AI, programming education, introductory programming, teaching frameworks, assessment practices, debugging support, learning design.