Artificial Intelligence in Educational Governance: Implications for Adaptive Learning and Student Mindset Formation

This paper discusses how Artificial Intelligence (AI) instructional support affects adaptive learning and student attitude. A structured Likert-type questionnaire was used to collect data on 180 participants (teachers and students) through a quantitative and cross-sectional design. To describe the patterns and to test the associations, descriptive statistics, bivariate correlations, and multiple regression analyses were performed. Results suggest that AI integration correlates positively with more individualized pacing and level of classroom engagement. Teachers have declared that AI applications have facilitated the delivery of lessons, real-time student progress, and real-time feedback. Adaptive tasks that increase and decrease dynamically with perceived probability of success showed students increases in problem-solving and persistence that the students attributed to the adaptive tasks. Alongside these benefits, the issues cited by the respondents as barriers to impacting the people are data-privacy concerns and lack of equity in accessing the data, as well as lack of training. These results align with prior literature showing that, when appropriately implemented, AI can enhance academic outcomes and learner development. Overall, the study concludes that AI holds substantial promise for educational improvement, provided implementation is accompanied by capacity building and robust governance.