Enhancing Student Engagement with AI

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Mentor Based

Program Syllabus

Module 1

About This Course

This self-paced course covers the application of AI in enhancing student engagement. Participants will explore AI-driven educational games, virtual tutoring systems, and engagement analytics tools. The course also includes case studies of successful implementations and prepares participants for AI certifications in education.

Module 2

Aim

To provide PhD scholars and academicians with advanced skills in using AI to enhance student engagement and learning outcomes. This course aims to integrate interactive AI-driven tools, virtual tutors, and engagement analytics to create a dynamic learning environment.

Module 3

Program Objectives

Implement AI-driven interactive learning tools.
Utilize AI-based virtual tutors effectively.
Measure and improve student engagement with AI analytics.
Analyze successful case studies of AI in education.
Prepare for AI certifications in education.

Module 4

Program Structure

Interactive Learning Tools
- AI-driven educational games and simulations
- Benefits and challenges of interactive learning tools
- Hands-on session with AI educational tools
Virtual Tutors
- AI-based virtual tutoring systems
- Implementing and optimizing virtual tutors
- Practical applications and examples
Engagement Analytics
- Tools to measure and improve student engagement
- Key AI technologies in engagement analytics
- Hands-on session with engagement analytics tools
Case Studies
- Examples of increased student engagement with AI
- Analysis of successful implementations
- Lessons learned and best practices
Certification Preparation
- Important topics for AI certifications in education
- Study materials and resources
- Practice exams and review sessions

Lead Instructor

Dr. Sarah Chen

PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.