Linear regression model to predict the use of artificial intelligence in experimental science students

This study builds on the increasing relevance of technology integration in higher education, specifically in artificial intelligence (AI) usage in educational contexts. Background research highlights the limited exploration of AI training in educational programs, particularly within Latin America. AI has become increasingly pivotal in educational practices, influencing the development of competencies in various disciplines, including experimental sciences. This study aimed to describe the correlation between professional competencies in AI, AI usage, and digital resources among students in the experimental sciences education program at the National University of Chimborazo. Methodologically, a quantitative approach was employed, involving a structured survey distributed among 459 students. Data analysis was conducted using multiple regression models to establish predictive insights into AI usage. A multiple linear regression model was developed to predict AI usage among these students. The analysis revealed significant correlations between AI competencies, AI usage, and digital resources. The regression model highlighted that both AI competencies and digital resources are significant predictors of AI usage. These findings underscore the importance of developing AI competencies and providing access to digital resources to enhance the effective use of AI in educational practices. Limitations and future research directions are discussed.