Use when you need to assess, quiz, test, or diagnose a student's current knowledge state using adaptive questioning. Implements ALEKS-style assessment using BLIM (Basic Local Independence Model) with Bayesian state updating, fringe-based item selection, and CbKST competence state inference. Supports PoLIM for graded…
Use when you need to establish prerequisite relationships between knowledge items. Constructs the surmise relation (prerequisite quasi-order) using the QUERY algorithm with the AI agent as domain expert, producing confidence-scored prerequisite pairs with explicit rationale. Supports IITA data-driven and FCA-based…
Use when you need to derive the full knowledge space from the surmise relation. Computes all feasible knowledge states (downward-closed sets), inner and outer fringes, and representative learning paths using scripts/kstutils.py. Reads/produces knowledge graphs in graphs/.json. Part of the KST pipeline — Phase 2…
Use when you have explicit learning objectives to decompose into testable, atomic knowledge items. Applies five taxonomic frameworks (Bloom's Revised, SOLO, Marzano's, Webb's DOK, Fink's) to classify and decompose each objective, with ECD assessment validation and CbKST competence identification. Reads/produces…
Use when you need to extract atomic knowledge items from course materials such as syllabi, textbooks, standards documents, or curriculum artifacts. Analyzes source materials using hierarchical curriculum decomposition and taxonomic classification (Bloom's, DOK, Hess CRM) to produce the foundational items[] array for a…
Use when you need to generate personalized learning materials, lessons, or tutoring content for a student based on their knowledge state. Targets the student's outer fringe using CbKST competence-first design, ZPD scaffolding, meaningful learning connections, UDL 3.0 principles, and learning/forgetting awareness.…
Use when you need to build a concept map showing relationships between knowledge items and identify latent competences (CbKST). Organizes items hierarchically, identifies item-level relationships (prerequisite-of, is-a, part-of, co-requisite, related-to), discovers latent competences and the skill map, and produces…
Use when you need to plan a class session, lecture, or differentiated instruction using class-wide knowledge state data. Analyzes aggregate student states and competence profiles to determine optimal teaching targets, student groupings, and peer tutoring pairings following UDL 3.0 principles. Uses scripts/kstutils.py…
Use when the curriculum, field, or domain evolves and the knowledge graph needs updating — adding, removing, merging, or splitting items and competences, or revising prerequisites. Preserves mathematical integrity and performs impact analysis on student states, competence states, and learning paths. Uses…
Use when you need to validate a knowledge graph for mathematical consistency, educational plausibility, CbKST integrity, and schema conformance. Runs automated validation via scripts/kstutils.py then performs reasoning-based checks. Produces a structured PASS/WARN/FAIL report. Reads/produces knowledge graphs in…
Instructions for vanderbilt-data-science/knowledge-spaces, covering knowledge space theory — skill suite, skill pipeline, phase 1: domain analysis, phase 2: knowledge structure construction and phase 3: application.