AI in Educational Research

Home >Courses >AI in Educational Research

Mentor Based

Program Syllabus

Module 1

About This Course

This self-paced program explores the role of AI in educational research, focusing on data analysis, predictive analytics, AI-driven research methodologies, and ensuring ethical AI practices. Participants will also prepare for AI certifications in educational research.

Module 2

Aim

To provide PhD scholars and academicians with advanced skills in applying AI to educational research and development. This course aims to enhance research methodologies, predictive analytics, and ethical considerations using AI tools and techniques.

Module 3

Program Objectives

Utilize AI for educational data analysis.
Implement predictive analytics in educational research.
Enhance research methodologies with AI tools.
Ensure ethical AI practices in educational research.
Prepare for AI certifications in educational research.

Module 4

Program Structure

Data Analysis in Education
- Using AI for educational data analysis
- Tools and techniques for data analysis
- Hands-on session with AI data analysis tools
Predictive Analytics
- AI models predicting educational outcomes
- Implementing predictive analytics in educational research
- Practical applications and case studies
Research Methodologies
- AI-driven research methodologies
- Enhancing traditional research methods with AI
- Hands-on session with AI research tools
Ethical Considerations
- Ensuring ethical AI research in education
- Ethical standards and guidelines
- Case studies and best practices
Certification Insights
- Key areas for AI certifications in educational research
- 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.