learning-experiment

What problem does it solve?

This Skill helps you design educational psychology studies and analyze learning data to quantify student ability, learning trajectories, retention, and intervention effects.

Core Features & Use Cases

• IRT modeling for test/assessment quality: Estimate item discrimination and difficulty using 1PL/2PL/3PL concepts, compute item/test information, and infer precision across ability levels.
• Learning and forgetting curve estimation: Fit learning curves (e.g., power law) and forgetting curves (e.g., Ebbinghaus-style retention) from trial or post-learning measurements.
• Experimental design and causal evaluation: Run A/B testing style analyses for educational interventions using randomized assignment, pre/post designs, effect sizes, and ANCOVA adjustment.

Quick Start

Ask the AI to fit a 2PL IRT model and estimate a power-law learning curve plus an Ebbinghaus forgetting curve from your student response and timing data, then summarize intervention impact with an A/B test (effect size and ANCOVA).