Evaluating and Optimizing Educational Content with Large Language Model Judgments

arXiv:2403.02795v1 Announce Type: cross
Abstract: Creating effective educational materials generally requires expensive and time-consuming studies of student learning outcomes. To overcome this barrier, one idea is to build computational models of student learning and use them to optimize instructional materials. However, it is difficult to model the cognitive processes of learning dynamics. We propose an alternative approach that uses Language Models (LMs) as educational experts to assess the impact of various instructions on learning outcomes. Specifically, we use GPT-3.5 to …

abstract arxiv build cognitive computational cs.ai cs.cl educational language language model large language large language model materials processes studies them type