Content modeling
Define the attributes required by each item and lesson.
LANGUAGE DIAGNOSTIC ASSESSMENT
Technology that helps AI understand the learner. Expert AI tutoring starts here.
An expert tutor uses experience to interpret learning outcomes and student behavior. DiagniaLab gives AI the learner information it needs to make the same kind of informed judgment.
“Cognitive diagnostic assessment is designed to measure specific knowledge structures and processing skills in students.”— Leighton & Gierl, Cognitive Diagnostic Assessment for Education (2007)
DIAGNOSTIC PIPELINE
From learning data to the next teaching decision
Learning evidence
Collect responses, time, questions, dialogue, and relearning records.
Diagnostic inference
Estimate the likely reason for difficulty and ask when evidence is uncertain.
AI tutoring
Choose the next question, hint, explanation, or problem for this learner.
CORE TECHNOLOGY
Four technologies behind learner-aware AI
Q-matrix design
Maps assessment items to the language and cognitive attributes they require.
Cognitive diagnostic models
Infer a learner's mastery pattern instead of reducing ability to a single score.
Learner modeling
Builds an evolving learner profile from behavior, questions, dialogue, and learning outcomes.
Educational recommendation systems
Connect diagnostic information to the next problem, explanation, and learning sequence.
DOMAIN EXPERTISE
Effective scaffolding requires deep subject-matter expertise.
Giving only the help a learner needs—without doing the thinking for them—depends on a precise model of language, assessment, and instruction. DiagniaLab combines this domain knowledge with AI engineering.