Predicting the Acceptance of Artificial Intelligence in Learning Environments Using SPSS and Random Forest Classification

Abstract

This study was conducted from the perspective of the students and faculty members of the Islamic University of Babylon branch, aiming at determining the factors affecting the acceptance of artificial intelligence (AI) technologies in higher education. The researcher used a descriptive survey method and administered a questionnaire involving five major constructs to a randomly selected sample of 100 respondents. With respect to male respondents, the overall mean was 3.01 (SD = 0.54), and for female respondents, it was 2.78 (SD = 0.57). This shows that there is a statistically significant difference in the levels of acceptance. The instrument’s reliability was verified through Cronbach’s Alpha at 0.906, which confirms the instrument’s high reliability. Furthermore, in addition to the usual SPSS analysis, the researcher used a couple of machine-learning analyses (rule-based classifier and Random Forest), which provided F1-scores and distribution analysis to augment the SPSS results. The study suggests that to maximize the use of AI in education, there is a need for more  technical support, training, and workshops.