Artificial Intelligence Supporting Independent Student Learning: An Evaluative Case Study of ChatGPT and Learning to Code

Abstract

Artificial intelligence (AI) tools like ChatGPT demonstrate the potential to support personalized and adaptive learning experiences. This study explores how ChatGPT can facilitate self-regulated learning processes and learning computer programming. An evaluative case study design guided the investigation of ChatGPT’s capabilities to aid independent learning. Prompts mapped to self-regulated learning processes elicited ChatGPT’s support across learning tools: instructional materials, content tools, assessments, and planning. Overall, ChatGPT provided comprehensive, tailored guidance on programming concepts and practices. It consolidated multimodal information sources into integrated explanations with examples. ChatGPT also effectively assisted planning by generating detailed schedules. However, its interactivity and assessment functionality demonstrated shortcomings. ChatGPT’s effectiveness relies on learners’ metacognitive skills to seek help and assess its limitations. The implications include ChatGPT’s potential to provide Bloom’s two-sigma tutoring benefit at scale.

Keywords

• artificial intelligence
• self-regulated learning
• tutoring
• artificial intelligence in education
• personalized learning
• intelligent tutoring systems