Authoring Worked Examples for Java Programming with Human-AI Collaboration
This addresses the problem of time constraints for instructors in programming education, though it appears incremental as it builds on existing explanation methods with AI assistance.
The paper tackles the challenge of instructors lacking time to provide line-by-line explanations for Java programming worked examples by introducing a human-AI collaboration authoring system that generates initial explanations for editing, and it assesses the quality of these explanations in a study.
Worked examples (solutions to typical programming problems presented as a source code in a certain language and are used to explain the topics from a programming class) are among the most popular types of learning content in programming classes. Most approaches and tools for presenting these examples to students are based on line-by-line explanations of the example code. However, instructors rarely have time to provide line-by-line explanations for a large number of examples typically used in a programming class. In this paper, we explore and assess a human-AI collaboration approach to authoring worked examples for Java programming. We introduce an authoring system for creating Java worked examples that generates a starting version of code explanations and presents it to the instructor to edit if necessary. We also present a study that assesses the quality of explanations created with this approach.