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ADAPT and AI: An Instructor’s Success Story
Wed March 4, 2026 @ 8:00 pm - 9:00 pm GMT

This session demonstrates practical ways to build and deploy homework in LibreTexts ADAPT using WeBWorK algorithmic problems.
WeBWorK uses a complex Perl-based language called PG, and writing questions in PG can be challenging. Most PG examples online focus on math, physics, and engineering. As a life science professor, I want to bridge that gap by bringing algorithmic biology problems, which are often more descriptive than numerical, into LibreTexts ADAPT using WeBWorK.
In this session, I will show new instructors how to use AI to turn a conceptual homework idea into a fully functional WeBWorK problem, without needing to know how to code. The talk will demonstrate how large language model agents such as Claude Code and OpenAI Codex can produce working WeBWorK problems when given solid documentation and required to check output using a local renderer.
A brief course case study will show how a problem concept can become a working WeBWorK assignment through an iterative workflow.



