Integrating LLMs in Software Engineering Education: Motivators, Demotivators, and a Roadmap Towards a Framework for Finnish Higher Education Institutes

Abstract

The increasing adoption of Large Language Models (LLMs) in software engineering education presents both opportunities and challenges. While LLMs offer benefits such as enhanced learning experiences, automated assessments, and personalized tutoring, their integration also raises concerns about academic integrity, student over-reliance, and ethical considerations. In this study, we conducted a preliminary literature review to identify motivators and demotivators for using LLMs in software engineering education. We applied a thematic mapping process to categorize and structure these factors (motivators and demotivators), offering a comprehensive view of their impact. In total, we identified 25 motivators and 30 demotivators, which are further organized into four high-level themes. This mapping provides a structured framework for understanding the factors that influence the integration of LLMs in software engineering education, both positively and negatively. As part of a larger research project, this study serves as a feasibility assessment, laying the groundwork for future systematic literature review and empirical studies. Ultimately, this project aims to develop a framework to assist Finnish higher education institutions in effectively integrating LLMs into software engineering education while addressing potential risks and challenges.

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