Navigating Large Language Models: Rules, Challenges, and Fair Transformations for STEM Education

Research Project, 2024 – 2026

This research aims to contribute to understanding how applied rules governing the usage of Large Language Models (LLMs) consider the advantages and disadvantages related to students' academic work in STEM education. By delving into the rules governing LLMs utilization and their impact on student's academic engagement, the study explores the challenges these regulations pose to the fundamental principles of fair education. In this context, the project strives to identify strategies that teachers within STEM disciplines can employ to navigate the complexities of students’ LLMs integration. The research addresses the following three overarching research questions, which build upon each other: 1) What rules have teachers in STEM education applied to students' use of LLMs? 2) What consequences do the applied LLMs rules have for students' use of LLMs? 3) How do teachers design rules to manage the complex consequences stemming from students' LLMs usage, with a focus on promoting fairness in teaching and assessment within STEM education? For this research project, Cultural-Historical Activity Theory (CHAT) is chosen as the theoretical framework.