8 docs tagged with "ai-in-edtech"

Learn how adaptive learning systems model student knowledge state and sequence educational content using IRT, CAT, spaced repetition, and multi-armed bandits to maximize learning outcomes.

Learn how AI systems automatically score essays, grade short answers, generate feedback, detect plagiarism, and audit for bias in educational assessment pipelines.

Learn how LLMs generate educational content - questions, explanations, worked examples, and quizzes - with quality control, Bloom's taxonomy alignment, and hallucination mitigation.

Learn FERPA compliance, algorithmic bias in educational AI, surveillance concerns, data minimization, transparency requirements, and responsible deployment of AI in learning environments.

Learn Bayesian Knowledge Tracing (BKT), Deep Knowledge Tracing (DKT), SAKT, and AKT - models that estimate student knowledge state over time from interaction sequences.

Learn readability scoring, educational NER, automatic summarization, curriculum alignment, concept map generation, and question difficulty estimation for educational NLP pipelines.

Learn how to build AI tutoring systems using Socratic dialogue, LLM-based hint generation, worked example fading, affective state detection, and multi-session context management.

Learn how to build early warning systems for at-risk students, predict dropout and grades, audit for fairness, and design interventions using ML on LMS engagement data.