Date of Graduation
12-2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Higher Education (PhD)
Degree Level
Graduate
Department
Counseling, Leadership, and Research Methods
Advisor/Mentor
McCray, Suzanne
Committee Member
Mamiseishvili, Ketevan
Second Committee Member
Murry, John W. Jr.
Third Committee Member
Keiffer, Elizabeth A.
Keywords
Business Analytics; ChatGPT; GenAI; Generative AI; Prompt Engineering; Quantitive
Abstract
The rapid evolution of generative artificial intelligence (GenAI) presents a transformative opportunity in higher education, offering new pathways for learning through personalized feedback, interactive environments, and support for complex tasks. This quasi-experimental study investigated the effects of targeted GenAI prompt engineering instruction on knowledge acquisition, prompt writing skills, and confidence levels among undergraduate and graduate students in business analytics courses at a research university. A pre-test and post-test design measured changes across knowledge acquisition, prompt writing proficiency, and GenAI confidence and usage. Findings revealed a mixed impact on knowledge acquisition, with undergraduates showing minor improvements and graduate students experiencing declines without significant reinforcement, highlighting the importance of contextual, sustained GenAI instruction. The experimental groups demonstrated notable improvements in prompt writing skills, underscoring the effectiveness of structured GenAI training in fostering clarity and specificity in GenAI interactions. Additionally, undergraduate students reported increased confidence in using GenAI daily, while graduate students showed greater confidence in academic applications. These results indicate that brief, targeted interventions can quickly build GenAI literacy, equipping students with essential skills for an increasingly AI-driven world. This study contributes valuable empirical data to guide educators in integrating GenAI instruction, supporting skill development, and ethical considerations essential for responsible GenAI use in higher education.
Citation
Gastineau, J. (2024). Exploring the Impact of Generative AI Prompt Engineering in Higher Education: A Study in Undergraduate and Graduate Business Analytics Courses. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/5551
