01Module 6: AI in EdTechAdaptive learning systems, AI-powered assessment, knowledge tracing, and personalized tutoring - building educational AI that actually improves learning outcomes.02Adaptive Learning SystemsLearn 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.03AI-Powered AssessmentLearn how AI systems automatically score essays, grade short answers, generate feedback, detect plagiarism, and audit for bias in educational assessment pipelines.04Content Generation for EducationLearn how LLMs generate educational content - questions, explanations, worked examples, and quizzes - with quality control, Bloom's taxonomy alignment, and hallucination mitigation.05Knowledge Tracing ModelsLearn Bayesian Knowledge Tracing (BKT), Deep Knowledge Tracing (DKT), SAKT, and AKT - models that estimate student knowledge state over time from interaction sequences.06Student Performance PredictionLearn 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.07Personalized Tutoring AILearn how to build AI tutoring systems using Socratic dialogue, LLM-based hint generation, worked example fading, affective state detection, and multi-session context management.08NLP for Educational ContentLearn readability scoring, educational NER, automatic summarization, curriculum alignment, concept map generation, and question difficulty estimation for educational NLP pipelines.09Ethics and AI in EducationLearn FERPA compliance, algorithmic bias in educational AI, surveillance concerns, data minimization, transparency requirements, and responsible deployment of AI in learning environments.
