2023: Prototyping learning analytics for human-AI interaction

Master's theses

Advisor(s)

Abstract

Large language models allow to support human learning and work in real time. This joint activity has potential to both positively and negatively impact human cognition and problem solving. The project aims to build a student-facing prototype for analytics that reflect their interaction with LLMs when they learn. The prototype will mirror to the individuals how they use an LLM application, when they rely on it during learning, and whether that supports their intended goals for learning. Potential context for implementing the prototype is within the Artemis system but other contexts are possible and can be discussed with the supervisory team.


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