Reading and understanding code form the basis of programming education. The emergence of LLMs has increased the importance of these skills, as developers also need to interact effectively with LLM-generated code. This paper presents an approach that marries code comprehension with LLM capabilities by leveraging ‘Explain in plain English’ (EiPE) tasks. These tasks challenge learners to describe code snippets’ purposes succinctly, aiming to automate assessment with LLMs and cultivate LLM prompting abilities. Here are the key takeaways from the study:

• Traditional code comprehension paired with LLM interaction can enhance learning outcomes.
• EiPE assessments benefit from automated evaluation using LLM-generated code responses.
• Positive student feedback illustrates a welcoming perspective on integrating LLMs in coding education.
• This approach assists in developing necessary skills for formulating clear prompts that elicit desired code from LLMs.

In my opinion, effectively integrating LLMs into programming education can significantly streamline the learning process. Students not only learn to understand code but also how to communicate with and make the most of LLMs. This hybrid strategy could pioneer innovative pedagogical models in computer science education, ushering in a new era where human coders and AI collaborate seamlessly.