Academic Experiences and Best Practices in Utilizing AI-Powered Learning Tools: Inputs to Policy Framework Development
Abstract
This study investigated the academic experiences and best practices of students and teachers in utilizing AI-powered tools in the Schools Division of Santiago City and aimed to generate evidence-based inputs for policy development. The study was guided by the Human–AI Interaction Theory, Technology Integration and Implementation Framework, and Learner Technology Appropriation Theory, which explain AI adoption, technology integration, and users’ engagement with AI-supported learning environments. An explanatory sequential mixed-methods design was employed, beginning with quantitative data collection through a structured Likert-type survey questionnaire, followed by qualitative interviews to further explain participants’ experiences, perceived benefits, and challenges. The respondents consisted of Grade 12 senior high school students and teachers from selected schools in the division who had experience using AI-powered tools for academic and instructional purposes. Results showed that students perceived AI-powered tools as beneficial in supporting academic tasks, improving time management, reducing cognitive load, and enhancing learning engagement. Teachers likewise reported that AI tools improved instructional preparation, teaching effectiveness, and professional efficiency. However, challenges were identified, including concerns on ethical use, dependence on AI, accuracy of AI-generated outputs, limited policy clarity, infrastructure constraints, and the need for continuous AI-related training and guidance. The study concluded that AI-powered tools can positively contribute to teaching and learning when implemented responsibly and supported by appropriate institutional policies. This study aligns with Sustainable Development Goal 4 (Quality Education) by supporting innovative, inclusive, and improved educational practices. It also contributes to sustainable educational governance by providing evidence-based policy inputs for ethical and responsible AI integration in schools.