Introduction

In today’s digital-first educational ecosystem, institutions must harness the power of Educational Data Mining (EDM) and Learning Analytics (LA) to personalize learning, increase retention rates, improve academic performance, and optimize curriculum design. Educational Data Mining and Learning Analytics Training Course is designed to equip educators, data scientists, instructional designers, and policy-makers with the tools and techniques to analyze student data, extract patterns, and implement data-driven decision-making strategies for learning environments. The content integrates predictive modeling, data visualization, and machine learning tailored to the education sector.

With the increasing shift toward online and hybrid learning models, learning institutions must adapt to data-driven education models that prioritize learner engagement, institutional effectiveness, and performance outcomes. Participants will gain hands-on experience with tools like Python, R, RapidMiner, and Tableau, explore ethical considerations in educational data usage, and develop impactful dashboards and reports for real-time interventions. The course provides actionable case studies and simulations from K-12, higher education, and corporate training environments.

Programme Curriculum

Educational Data Mining and Learning Analytics Training Course

Introduction

Course Objectives

Understand the fundamentals of Educational Data Mining (EDM) and Learning Analytics (LA)
Apply machine learning models for predicting student success
Explore data collection methods in virtual and blended learning environments
Conduct behavioral analysis using clickstream and LMS data
Utilize data visualization tools like Tableau and Power BI for reporting
Identify at-risk learners through predictive analytics
Analyze student engagement metrics and performance indicators
Develop personalized learning pathways based on data insights
Ensure ethical use and privacy of educational data
Create data dashboards to inform instructional design
Leverage AI and NLP in learning analytics
Integrate EDM and LA with institutional policy-making
Conduct longitudinal and real-time data analysis for learning optimization

Target Audiences

University Professors and Lecturers
Educational Researchers
Instructional Designers
Data Analysts in Education
School Administrators and Policy Makers
EdTech Product Developers
Learning Management System (LMS) Managers
Graduate Students in Education and Data Science

Course Duration: 5 days

Course Modules

Module 1: Introduction to Educational Data Mining

Definition and Scope of EDM
Historical Development of EDM
Key Techniques in Data Mining
Tools Used in Educational Data Mining
Benefits and Challenges
Case Study: Applying EDM to Improve Student Retention in Higher Education

Module 2: Understanding Learning Analytics

Distinction Between EDM and LA
Key Frameworks and Models
The Role of LA in Student Success
Real-Time vs Longitudinal Analytics
Data Sources: LMS, Social Media, Clickstream
Case Study: Using LA to Improve Engagement in MOOCs

Module 3: Predictive Analytics in Education

Introduction to Predictive Modeling
Logistic Regression and Decision Trees
Predicting Dropout Rates and Performance
Early Warning Systems
Data Requirements and Accuracy
Case Study: Predictive Analytics in Online STEM Courses

Module 4: Tools and Technologies for EDM & LA

Using Python and R for Analysis
Introduction to RapidMiner and Orange
Tableau and Power BI for Visualization
Data Preprocessing and Cleaning
Tool Integration with LMS (Canvas, Moodle, Blackboard)
Case Study: Tableau Dashboards for K-12 Performance Metrics

Module 5: Learning Behavior and Engagement Analysis

Behavioral Data Collection from LMS
Identifying Learning Styles via Analytics
Clickstream and Navigation Patterns
Measuring Participation and Collaboration
Custom Reports and Visualizations
Case Study: Tracking Engagement Patterns in Blended Learning

Module 6: Personalization and Adaptive Learning Systems

Concept of Adaptive Learning
Recommender Systems in Education
Personalized Feedback Loops
Data-Driven Curriculum Design
Adaptive Pathways in E-Learning
Case Study: Adaptive Learning in Math Remedial Programs

Module 7: Ethics, Privacy, and Data Governance

FERPA, GDPR, and Educational Data Laws
Consent and Anonymity
Data Ownership and Access Rights
Ethical Dilemmas in Learning Analytics
Governance Frameworks in Institutions
Case Study: Ethical Data Use in University-Wide Analytics Project

Module 8: Strategic Implementation of EDM and LA

Aligning Analytics with Institutional Goals
Capacity Building for Educators and Staff
Policy Formulation Based on Analytics
Cross-Departmental Collaboration
Scaling Analytics Infrastructure
Case Study: Institutional Transformation through LA Strategy

Training Methodology

Instructor-led live virtual sessions
Hands-on lab exercises and real-time data practice
Group-based problem-solving activities
Use of open-source and commercial analytics tools
Weekly quizzes and capstone project assessment

Register as a group from 3 participants for a Discount

Send us an email: info@fineskilltrainingcenter.org or call +254769199797

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to Fineskill Training Center account, as indicated in the invoice so as to enable us prepare better for you.

Skills & Software Covered

Learning analytics educational data mining insights

Programme Fee

Duration: 5 Days

Method: Online or Physical

Online Price: $1,000

Physical Price: $1,500

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Oct 19 2026

19 Oct — 23 Oct 2026

💻 Online / Virtual session

Online $1,000