Evaluating Prompting Frameworks for Enhancing ChatGPT-Assisted Literature Reviews and Ethical and Pedagogical Implications

Students use generative artificial intelligence (GenAI) tools for academic writing, but there is still little understanding of how students can prompt ChatGPT to write literature reviews, how structured prompting frameworks affect their outputs and what the implications are of such use of GenAI in teaching practices. Prompts and literature reviews written by seven students were collected before and after the introduction of three prompting frameworks (COSTAR, POSE, and Sandwich) and analysed. Following the intervention, students’ prompting became more focused and efficient, although they did not use all the elements of the frameworks, except for Sandwich. While literature review scores improved, approaching near-full marks, they lacked critical thinking and originality. Therefore, more training and understanding of prompting frameworks and fundamental knowledge about literature reviews are still needed. Plagiarism checks demonstrate a reasonable degree of similarity, although recurrent citation mistakes were found. These findings highlight pedagogical and ethical risks associated with GenAI use, which may be mitigated by alternative approaches to evaluating literature reviews that place greater emphasis on paper selection and topic choice. Although the small sample precludes generalisation, this study provides an initial exploration of how prompting frameworks influence GenAI-assisted literature reviews and what the ethical and pedagogical implications are.