A Unified Framework for Knowledge Assessment and Progression Analysis and Design

Designing engaging learning content is important but difficult, and typically involves a lot of manual specification. We present a unified framework that utilizes automatic problem decomposition and partial ordering graph construction to facilitate multiple workflows: knowledge assessment and progression analysis and design. We present results from a study with 847 participants in an online Japanese-language assessment tool demonstrating that our framework can efficiently measure student ability and predict student performance on specific problems. We also present results from analysis of curricula showing that the progressions of two different textbooks are surprisingly similar, and that our framework can lead to the discovery of general principles of expert progression design. Finally, we demonstrate automatic progression generation with desired sequencing and pacing, allowing for tailoring of progressions and mapping of parameters extracted from one curriculum onto another.