Assessment of Students Use of Generative Artificial Intelligence: Prompting Strategies and Prompt Engineering in Chemistry Education

Abstract

The rapid integration of generative artificial intelligence (AI) into educational settings prompts an urgent examination of its efficacy and the strategies that students employ to harness its potential. This study focuses on preservice chemistry teachers use of generative AI for chemistry-specific problem-solving and task completion. We found that there is a prevalent reliance on copy-pasting tactics in initial prompting approaches, and students need guidance to improve their prompting abilities. By implementing the “Five S” prompting framework, we explore the evolution of student prompts and the resultant satisfaction with AI-generated responses. Our findings indicate that, while students initially struggle with the nuances of effective prompting, the adoption of structured frameworks significantly enhances their perceived quality of AI-generated answers. This research sheds light on the current state of AI use among students but also underscores the importance of targeted educational frameworks to refine AI interaction in academic contexts. In particular, we suggest critical engagement and methodological prompt engineering strategies to maximize the educational benefits of generative AI technologies.

Revisiting a Teaching Sequence on the Topic of Electrolysis: A Comparative Study with the Use of Artificial Intelligence

“…In view of this, it is crucial to provide teachers with specialized training in AI-related tools, particularly generative ones, as the outcome highly depends on the quality of prompts. ,, Such complexities involved in lesson planning necessitate a thorough curation that only a specialistthe teachercould effectively undertake. In this scenario, the guarantee of curation quality hinges on the presence of a well-developed knowledge base among these professionals, underscoring the need for comprehensive teacher education programs.…”

“…The resulting answer from this step was named GPT-4-F (where F stands for feedback). An important aspect to consider while formulating AI inputs is prompt engineering . In this regard, we aimed to adhere to three guidelines for the best practices in prompt engineering: (1) iterative testing and refining; (2) balancing user intent and model creativity; and (3) ensuring ethical usage and avoiding biases .…”

Student Perceptions of Artificial Intelligence Utility in the Introductory Chemistry Classroom

“…In this way, no student or potentially copyrighted information is being provided to the corporations that make these systems. Instruction in effective prompt writing is an important topic as discussed by Tassoti, but falls outside the scope of this study. This study was approved by the Indiana University Institutional Review Board.…”