LLM-Assisted Coding for Non‑Engineering Students

Drawing from my innovation in the MBA course, Data Analytics for Managers (PMBA6093), I will introduce how to apply LLM-assisted coding in a class with highly diverse student backgrounds, aiming to enable “coding with natural language” while still fostering and preserving students’ critical thinking skills. Specifically, I will cover the following:

1. Integrating LLMs into the traditional problem-solving loop to streamline mechanical steps while keeping students engaged in interpretation and decision-making.
2. Creating a competitive, collaborative environment in which students critically evaluate and improve upon the baseline answers generated by LLMs. I will use the example of “Given a dataset covering 70 flight providers, produce the most informative visualization of each provider’s average ticket price using LLM and Rstudio” to illustrate how to initiate a peer review environment and forster continuous improvement in class.
3. Maximizing the potential of human–LLM collaboration by assigning complex, ambiguous tasks that mirror real-world problem-solving across multiple domains.