Establishing Essential Guidelines for the Educational Use of Generative AI
The potential of Artificial Intelligence (AI) technology to address several challenges currently facing colleges and universities is significant.These include student underachievement in mathematics, basic science, and the widening learning gap.Prior to imposing an unconditional prohibition on the use of generative AI in an educational context, it is imperative to investigate the potential of AI to enhance learning outcomes and inform pedagogical decision-making.This study comprises a preliminary survey of 438 learners in the humanities and social sciences, exploring their experiences with AI-based learning, concerns regarding copyright, and the challenges encountered when utilizing prompts.Based on the findings of the survey, guidelines for the effective use of generative AI were developed and implemented, with particular attention paid to prompt utilization and copyright concerns.In addition, this study also examines the purposes for which humanities and social science students employ AI, and to suggest that clear guidance from instructors is vital when developing courses that utilize generative AI tools such as ChatGPT.Subsequently, the efficacy of AI in the learning process was evaluated through learners' self-assessments of their satisfaction, confidence in using AI, awareness of copyright issues, and prompt handling.The results demonstrate that learners demonstrated heightened levels of satisfaction and confidence when instructors integrated explicit guidelines on AI utilization and authorship into their instructional materials.Overall, AI technology displays considerable potential in addressing the decline in fundamental academic competencies and addressing learning gaps.However, meticulous consideration and structured guidance are essential for optimizing its educational use, particularly in enhancing learning abilities.
Authors
- Jungin Kwon
Publication Details
- Journal
- Asia-pacific Journal of Convergent Research Interchange
- Published
- 2024-09-27
- DOI
- https://doi.org/10.47116/apjcri.2024.09.54
- Citations
- 1
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.53