Human-AI Co-Creation of Worked Examples for Programming Classes
This addresses the workload of programming instructors in creating educational content, but it is incremental as it builds on existing tools for presenting examples.
The paper tackles the problem of instructors lacking time to create detailed line-by-line explanations for many programming worked examples by introducing a human-AI collaboration system that generates starting explanations for Java code, which instructors can edit, and assesses its quality.
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