Learning gains — the outcome measure that anchors the wiki's efficacy evidence — appear across ai-tutor-effectiveness-review, genai-meta-analysis-programming-learning, retrieval-augmented-tutoring-algorithm-kite, and efficacy-study: gains are consistently positive but heterogeneous, moderated by scaffolding, context, and learner characteristics (RCT, learning-outcomes).
Related Pages
- adaptive-pretesting-retention -- Adaptive AI pretesting boosts initial learning, but long-term retention over 7 weeks depends on subsequent retrieval practice — learner-directed AI study underperforms structured retrieval.
- learning-behavior-background-advantage-ai-ed — Heterogeneous learning gains (2026-07-14)
📎 10 other pages tagged learning-gains
- A meta-analysis of the effect of generative AI on productivity and learning in programming
- AI in K-12 Evidence Base
- Artificial intelligence and feedback in university education: effectiveness and student perceptions
- Do Gains from Generative AI-Enabled Adaptive Pretesting Persist? Evidence from a Retention Study
- Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build
- Generative AI Availability, Grades, and Student Satisfaction at a Large University
- Generative AI without guardrails can harm learning: Evidence from high school mathematics
- Improving Hybrid Human-AI Tutoring by Differentiating Human Tutor Roles Based on Student Needs
- Is AI making us stupid?
- Learning behavior accounts for background-related advantage in AI-assisted education