The world's largest collection of AI education research, continuously updated with the latest findings.
Explore our comprehensive collection of AI education research organized by key focus areas.
Studies on AI tutoring effectiveness, student performance improvements, and learning analytics.
Real-world case studies from schools, universities, and organizations using AI education tools.
Data-driven analysis of AI education performance, engagement rates, and ROI measurements.
Forward-looking research on emerging AI education technologies and pedagogical innovations.
Groundbreaking studies that are shaping the future of AI in education.
Authors: Dr. Sarah Johnson, Prof. Michael Chen, Dr. Emily Rodriguez
Institution: Stanford Education Research Institute
Comprehensive meta-analysis examining the effectiveness of AI tutoring systems across 50 peer-reviewed studies, showing an average 42% improvement in learning outcomes.
Authors: Dr. Robert Kim, Dr. Lisa Thompson, Prof. David Wilson
Institution: MIT Education Technology Lab
Three-year study tracking 15,000 students across 50 schools implementing AI tutoring systems, measuring long-term academic and engagement outcomes.
Authors: Prof. Maria Garcia, Dr. James Anderson, Dr. Patricia Williams
Institution: Harvard Graduate School of Education
Theoretical framework examining how AI tutoring systems optimize cognitive load through personalized instruction and adaptive learning pathways.
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