Artificial Intelligence In The Classroom: Experimental Research On Innovative Approaches To Mathematics Instruction
Abstract
This paper explores the integration of Artificial Intelligence (AI) in mathematics instruction, examining their impact on student engagement, understanding, and performance. The study provides an overview of AI technologies, their historical development, and theoretical frameworks supporting their use in education, including constructivism, cognitivism, behaviorism, and project-based learning. By leveraging AI's ability to superimpose digital content onto the real world and AI's capacity for personalized learning, educators can create interactive, adaptive, and immersive learning environments. Experimental research and case studies demonstrate the effectiveness of these technologies in enhancing mathematical learning outcomes. For instance, AI provides personalized feedback and adaptive learning paths, fostering critical thinking and problem-solving skills. Despite their potential, the implementation of AI faces significant challenges, including technical issues, cost, accessibility, and the need for comprehensive teacher training. Addressing these challenges is crucial for equitable and effective integration in educational settings. Future research should focus on the long-term impacts, scalability, and integration of these technologies with other educational tools. This study underscores the transformative potential of AI in mathematics education and calls for continued innovation and research to optimize their use.
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