Designing Guidelines for Responsible GenAI Usage in Computer Science Education

Abstract

Introduction: Generative AI (GenAI) is widely used in industry and education, offering benefits like improved writing and personalized learning, but also challenges such as unverified information, over-reliance, and academic dishonesty. This study addresses these challenges by designing guidelines for responsible use of GenAI, considering the perspective of the student. Methodology: We applied the Design Science Research Methodology. The requirements for the guidelines were collected through desk research and semi-structured interviews. This input was used in the first design iteration of the guidelines and was evaluated in a student workshop. A second and third iteration followed, based on feedback from two workshops with teachers. Results: 17 interviews, 15 workshop participants, and desk research led to 825 minutes of audio, 219 codes in 640 quotes, 10 survey responses and 28 potential guidelines. The final guidelines include do’s and don’ts, a justification and referencing approach, and ethical considerations. They aim to support responsible GenAI usage while maintaining academic integrity. Discussion: This study offers insights into communication and alternative assessment methods. Literature highlights concerns about computer science students using GenAI, such as reduced critical thinking and unverified use of information. By integrating a reflection component into the justification model, students are encouraged to stay critical. Finally, the study contributes to existing research with practical guidelines, including do’s and don’ts, and a model for GenAI justification. Conclusion: This study developed guidelines that offer a clear framework for the use of GenAI that ensures academic integrity.

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