Empowering Self-Management: Unveiling the Impact of Artificial Intelligence in Learning on Student Self-Efficacy and Self-Monitoring

Abstract

Purpose: This article is going to provide insights to a complex connection between artificial intelligence in learning, student’s self-management skills, and self-efficacy in educational sectors. This research objective surrounds the AI’s impact on the learning experiences, of students by focusing on the existing gaps in previous research, primarily focused on the region of the Kingdom of Saudi Arabia. With the AI intervention, the understanding of the cognitive and motivational dimensions is influenced, as this research further explores the mediating role of self-efficacy in the relationship between AI and self-management. Method: This article pursues the research by using the methodology of structural equation modeling (SEM) with STATA-SEM, where data was collected from 239 students in the Kingdom of Saudi Arabia. The survey-based methodology was used to understand the student’s views and thoughts related to AI, self-management, and self-efficacy. Findings: the main results from the research show that AI in education is connected to better management skills of students, and self-efficacy. However, this connection is influenced by the mediating role of self-efficacy in the learning process. The research also helps to discover the individual differences among the self-monitoring. This becomes the empirical evidence of the growing field of AI in the educational sector, offering insights into the AI affects the students’ cognition and motivation in Saudi Arabia. Originality/Implications: this study plays a unique part as it builds an understanding of AI’s influences on students learning in a particular type of culture and educational setting. The results are important for the teachers and policymakers, they can provide ideas on the implications that would improve both how students think and stay motivated in Saudi Arabia’s learning settings.