Course Modules:
Module 1: Introduction to AI in Education
Evolution of EdTech and the rise of AI
AI use cases in classrooms and digital platforms
Benefits and challenges of AI-driven education
Module 2: Personalized Learning with AI
Learner profiling and preference detection
Adaptive learning paths using recommendation algorithms
AI tools for differentiated instruction
Module 3: Intelligent Tutoring Systems (ITS)
What is an ITS and how it works
Rule-based vs. machine learning-driven tutoring
Building tutoring bots using NLP and decision trees
Module 4: AI in Assessment and Grading
Automating quizzes, essays, and exam evaluations
AI for formative vs. summative assessment
Real-time feedback generation and plagiarism detection
Module 5: Student Performance Prediction & Analytics
Predictive models for dropout risk and engagement
Time series and classification models for progress tracking
Dashboards for educators and school administrators
Module 6: Natural Language Processing in Education
Conversational agents for language learning
Speech-to-text and automatic transcription tools
Sentiment analysis in student feedback
Module 7: EdTech Product Design & Integration
Building AI into LMS platforms and mobile apps
Integration with SCORM, xAPI, and e-learning standards
UX/UI considerations in educational interfaces
Module 8: Ethics, Bias, and Data Privacy in EdTech
Algorithmic fairness and inclusivity in education
GDPR and COPPA for student data protection
Human oversight and accountability in AI decisions
Module 9: Global Trends & Future of AI in Education
AI in multilingual and cross-cultural learning
AI for lifelong learning and workforce upskilling
Emerging technologies (AR/VR + AI, Metaverse in EdTech)
Module 10: Capstone Project
Choose from:
Designing an intelligent quiz generator
Creating a personalized learning recommendation system
Building a dashboard to monitor student performance
Submit final product with demo, report, and UX documentation
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