Students’ Perspectives on the Application of a Generative Pre-Trained Transformer (GPT) in Chemistry Learning: A Case Study in Indonesia

Abstract

The rapid development of artificial intelligence (AI) has transformed chatbots into generative pre-trained transformers (GPTs) capable of performing various tasks. The use of GPTs is expanding to learning, including natural sciences like chemistry. GPTs can assist students in understanding and solving chemistry problems. However, there are potential negative impacts of using GPTs. This study aims to explore Indonesian university students’ perspectives on using GPTs for chemistry learning. The research used a case study method and collected data through questionnaires, interviews, and GPT usage logs, which were then analyzed thematically. The study revealed that students use GPTs in learning due to perceived usefulness, ease of use, emotional aspects, benefits, and social influence. Students appreciate GPT answers for being easy to understand, detailed, reliable, fairly accurate, fast, and helpful. However, students also recognize that GPT answers can be unreliable, difficult to understand, not always accurate, and potentially unethical. Students evaluate GPT responses by stimulating thoughts, confirming answers, integrating with other sources, directly copying responses, and paraphrasing before use. They are also aware of ethical considerations, drawbacks, and limitations associated with using GPTs. Findings pertaining to motives, constraints, and the evaluation of answer quality and its utilization can serve as indicators for the proper application of GPT in educational contexts. In many countries, including Indonesia, where there is a lack of usage regulations, concrete policies are necessary to ensure the proper integration of GPT into education.