Understanding ChatGPT adoption for data analytics learning: A UTAUT perspective among social science students in Oman - Suliman Zakaria Suliman Abdalla (Social Sciences and Humanities Open)
Generative artificial intelligence tools, particularly ChatGPT, have shown the potential to reshape education by providing personalized, efficient, and accessible learning experiences across various academic disciplines. Despite concerns about academic integrity and AI-driven misconduct, its potential to revolutionize how students engage with and master complex subjects is undeniable. This study explores the key factors that influence social science students' adoption of ChatGPT as a transformative tool to enhance their learning of data analytics. Using a descriptive quantitative research design, data were collected from a sample of 413 Omani students. The study utilizes the Unified Theory of Acceptance and Use of Technology (UTAUT) as a guiding theoretical framework. Through ordinal logistic regression analysis, the study identifies performance expectancy, facilitating conditions, social influence, self-efficacy, and effort expectancy as significant predictors of students' decisions to adopt ChatGPT for their learning needs. Descriptive findings reveal that students highly value ChatGPT's capability to simplify complex data analytics concepts and assist in selecting appropriate analytical methods. This demonstrates its effectiveness in enhancing conceptual understanding. However, the tool received lower ratings for tasks such as data pre-processing and cleaning, suggesting some limitations in its effectiveness in these aspects of data analytics learning. The study's findings highlight ChatGPT's substantial potential to enhance academic performance in data analytics and provide practical recommendations for students, instructors and institutions. The focus is on strategically integrating AI technologies to optimize instructional effectiveness and foster deeper student engagement with data analytics curricula.