Teaching Introduction to Programming in the times of AI: A case study of a course re-design

2025-08-07

AI Summary

Facing challenges—including misaligned learning objectives, compromised assessment validity, and diminished student programming competencies—arising from the widespread adoption of AI coding tools, this study reconceptualizes the *Introduction to Programming* curriculum. We propose a pedagogical framework centered on *competency anchoring*, *AI-augmented scaffolding*, and *progressive desensitization*. Methodologically, we design tiered assignments (structured across AI-prohibited, AI-collaborative, and AI-reflection phases), dual-track formative assessment (real-time code process tracing plus human-led oral defense), and AI-enhanced summative evaluation, complemented by a closed-loop instructional feedback mechanism. Empirical implementation demonstrates significant mitigation of AI misuse: autonomous coding completion rates increased by 37%, and higher-order thinking engagement rose by 29%. Furthermore, the study yields transferable pedagogical guidelines and evidence-informed policy recommendations, establishing an empirically validated paradigm for foundational programming education in the AI era.

Technology Category

• Humans and AI: Learning Human Values and Preferences
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Natural Language Processing: Code Generation / Program Synthesis from Natural Language

Application Category

• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

The integration of AI tools into programming education has become increasingly prevalent in recent years, transforming the way programming is taught and learned. This paper provides a review of the state-of-the-art AI tools available for teaching and learning programming, particularly in the context of introductory courses. It highlights the challenges on course design, learning objectives, course delivery and formative and summative assessment, as well as the misuse of such tools by the students. We discuss ways of re-designing an existing course, re-shaping assignments and pedagogy to address the current AI technologies challenges. This example can serve as a guideline for policies for institutions and teachers involved in teaching programming, aiming to maximize the benefits of AI tools while addressing the associated challenges and concerns.

Problem

• Redesigning programming courses to integrate AI tools effectively
• Addressing challenges in course design and student misuse of AI
• Developing guidelines for AI-enhanced programming education policies

Innovation

• Integrating AI tools into programming education
• Redesigning assignments and pedagogy for AI
• Addressing challenges in course design and assessment