A suggested Model to employ AI tools in Math teaching for secondary schools
Abstract
This study aimed to design and validate a proposed model for employing Artificial Intelligence (AI) tools in mathematics teaching for secondary schools. The model seeks to enhance teaching and learning practices by integrating intelligent systems that support adaptive instruction, data-driven feedback, and problem-solving skills. It responds to the growing demand for innovative approaches that align mathematics education with twenty-first-century learning environments. The model was developed based on educational technology frameworks and pedagogical theories, integrating constructivist, cognitive, and communicative approaches. It consists of four main domains: Inputs, Processes, Outputs, and Evaluation & Continuous Improvement. The Inputs domain identifies the human, technical, and curricular resources necessary for AI integration. The Processes domain focuses on designing and implementing AI-supported learning activities. The Outputs domain reflects the enhancement of students’ mathematical understanding, engagement, and creativity. Finally, the Evaluation & Continuous Improvement domain ensures sustainability and ethical use of AI through ongoing feedback and performance assessment. Expert validation of the model revealed a high level of agreement (M = 87.03%), indicating its suitability, coherence, and applicability in mathematics education. The study concludes that the proposed model provides a practical and adaptable framework for integrating AI tools to support personalized learning and enhance teaching effectiveness. It further recommends adopting the model to guide curriculum development, teacher training, and policy-making aimed at preparing students for an AI-driven educational future.
Fields of Study & Subjects
Technology-Enhanced Education Studies
Educational Technology and E-Learning
E-Learning and COVID-19
Publication details
- Journal / source
- Technium Romanian Journal of Applied Sciences and Technology
- Volume
- 30
- Pages
- 453–475
- Publication date
- 3 January 2026