Traditional and AI Tools for Teaching Concurrency

Today, AI tools are generally considered as education disrupters. In this paper, we put them in context with more traditional tools, showing how they complement the pedagogical potential of the former. We motivate a set of specific novel ways in which state-of-the-art tools, individually and together, can influence the teaching of concurrency. The pedagogy tasks we consider are illustrating concepts, creating motivating and debuggable assignments, assessing the runtime behavior and source code of solutions manually and automatically, generating model solutions for code and essay questions, discussing conceptual questions in class, and being aware of in-progress work. We use examples from past courses and training sessions in which we have been involved to illustrate the potential and actual influence of tools on these tasks. Some of the tools we consider are popular tools such as interactive programming environments and chat tools - we show novel uses of them. Some of the others such as testing and visualization tools are in-use novel tools - we discuss how they been used. The final group consists of AI tools such as ChatGPT 3.5 and 4.0 - we discuss their potential and how they can be integrated with traditional tools to realize this potential. We also show that version 4.0 has a better understanding of advanced concepts in synchronization and coordination than version 3.5, and both have a remarkable ability to understand concepts in concurrency, which can be expected to grow with advances in AI.