Conceptualising using prompt engineering with ChatGPT in engaging with higher education students

Abstract

Artificial intelligence (AI) tools like ChatGPT are being rapidly adopted in educational institutions to improve learning and teaching outcomes. However, educators may use ChatGPT to facilitate teaching without examining how prompts influence critical thinking, analytical skills, and students’ engagement. Despite the growing popularity and adoption efforts, many institutions struggle to achieve this aim. This could be attributed to a lack of understanding of applying prompt engineering (PE) using ChatGPT to enhance teaching and improve learning outcomes. This study seeks to understand the influencing factors by employing qualitative methods. Existing materials were gathered, and two, critical posthumanism (CP) and new materialism (NM), theoretical frameworks were applied to guide the analysis of the materials. The analysis revealed four critical influencing factors: rules of engagement, use of language, contextualisation, and intentionality. The four factors were interpreted to better understand how they manifested to influence the use of PE with ChatGPT. From the interpretation, the factors’ attributes were revealed. The impact of the factors and their attributes is highlighted, which has implications for both learners and educators.