Enhancing Algorithmic Thinking and Emotional Resilience in Programming Education Through AI Powered Virtual Tutoring

Abstract

This full research-to-practice paper addresses key challenges in programming education within engineering, particularly the uncritical use of generative AI (GenAI) and its potential to hinder independent learning. It introduces JULIUS, an AI-powered chatbot designed to serve as a virtual tutor in a Fundamentals of Programming course, aiming to enhance technical skills, emotional resilience, and student confidence. Grounded in connectivism and Challenge-Based Learning (CBL), JULIUS promotes autonomy, reduces anxiety, and supports real-world problem-solving through structured group dynamics and tools like Excel and PSeInt. A mixed-methods approach combined quantitative pre- and post-tests with qualitative thematic analysis. Results show significant improvements in conceptual understanding, logical reasoning, motivation, and collaboration. JULIUS also enhanced emotional well-being, metacognition, and teamwork, addressing cognitive and affective learning needs. The findings underscore JULIUS's effectiveness in bridging theory and practice while supporting adaptive and collaborative learning. This research highlights the potential of AI-driven tools to transform engineering education by promoting deeper learning, reducing anxiety, and improving group dynamics, aligning with broader trends in digital transformation and educational innovation.

Ähnliche Arbeiten