AI in Education Research Database

Filter Research By:

Method: Case Study Quantitative Qualitative Mixed Methods
Subject Area: Mathematics Science Language Arts Social Studies
Education Level: Elementary Middle School High School Higher Education

Featured Research

Impact of AI-Powered Adaptive Learning Systems on Student Achievement

Quantitative Mathematics Middle School

Key Findings:

  • 20% improvement in student test scores
  • Increased engagement in mathematical problem-solving
  • Significant reduction in achievement gaps
  • Higher student satisfaction rates

Johnson, M., et al. (2024). Journal of Educational Technology, 45(2), 112-128.

Natural Language Processing for Writing Feedback: A Multi-School Study

Mixed Methods Language Arts High School

Key Findings:

  • Improved writing quality across multiple metrics
  • Reduced teacher grading time by 40%
  • Enhanced student revision practices
  • Positive teacher and student feedback

Smith, A. & Brown, R. (2024). AI and Education Quarterly, 12(1), 45-62.

AI-Enhanced Personalized Learning Pathways in Science Education

Case Study Science High School

Key Findings:

  • Customized learning paths increased comprehension
  • Higher student engagement in complex topics
  • Improved laboratory preparation and safety
  • Better retention of scientific concepts

Wilson, K., et al. (2024). Science Education Technology Review, 18(3), 89-104.

Predictive Analytics for Early Intervention: A Large-Scale Study

Quantitative Elementary

Key Findings:

  • 85% accuracy in predicting learning challenges
  • Early intervention improved outcomes by 35%
  • Reduced achievement gaps in target populations
  • Cost-effective implementation strategies identified

Chen, L., et al. (2024). Educational Data Mining Journal, 8(4), 156-172.

Teacher Perspectives on AI Integration: A Qualitative Analysis

Qualitative Multiple Levels

Key Findings:

  • Identified key implementation challenges
  • Professional development recommendations
  • Success factors for AI adoption
  • Best practices for teacher support

Martinez, J. & Thompson, P. (2024). Teacher Education Technology Journal, 15(2), 78-93.

Research Implications

Key Trends and Recommendations

  • Personalization is key to successful AI implementation
  • Teacher training significantly impacts effectiveness
  • Hybrid approaches show most promise
  • Data privacy remains a critical consideration
  • Cost-benefit analysis supports strategic implementation

Additional Resources