software development trainers

Abstract: The increasing availability of generative artificial intelligence (GenAI) tools, such as ChatGPT and code-completion assistants, raises questions about how learners integrate these tools into learning activities, particularly in MOOCs that attract diverse participant populations. This study examines the use of GenAI in two programming MOOCs taught in Estonian that differ in duration, workload, topic complexity, and assignment volume: About Programming (4 weeks, 26 expected hours, n = 187) and Introduction to Programming (8 weeks, 78 expected hours, n = 182). Post-course questionnaire data were analyzed using non-parametric statistical methods to examine self-reported adoption, usage frequency, and purposes of GenAI use across courses and learner backgrounds. The results show that GenAI adoption was widespread in both MOOCs, with no statistically significant differences by gender, age, education level, or prior programming experience. However, participants in the longer, more extensive MOOC reported significantly higher usage frequency and were more likely to use GenAI for debugging and idea generation. Reported usage frequency for code explanation and debugging was also higher in the longer course. Exploratory analyses found limited relationships between GenAI use and learning-related outcomes. The findings suggest that course context may play a greater role than learner characteristics in shaping how GenAI tools are used. These results provide implications for instructional design and guidance in programming education.

Abstract: Refactoring is the art of improving the internal structure of the code without altering its external behavior. Because of the topic's significance, several teaching methods and strategies have been proposed in the literature. However, skills in identifying and refac- toring code smells come from training and experience, and a lack of motivation may hinder developers' adoption of refactoring tools. In this paper, we discuss the results of an experiment in the classroom that involved performing various refactoring activities to remove antipatterns using Refactoria, an innovative game-based tool that supports the acquisition of code smell and refactoring concepts. The players play as an expert chef with their sidekick Watson the Whiskbot to refactor Watson's instructions into efficient, readable, and easily maintainable code. We present an experiment with 30 student developers. In particular, we study the perception, effectiveness, and usefulness of gamification for engaging developers in code smell identification and refactoring. Our evaluation indicates a high perceived usefulness among students, and participants reported that Refactoria facilitated their understanding of the refactoring concepts.