Overview
Online and software-based learning tools have been used increasingly in education. This movement has resulted in an explosion of data, which can now be used to improve educational effectiveness and support basic research on learning.
In this course, you will learn how and when to use key methods for educational data mining and learning analytics on this data. You will examine the methods being developed by researchers in the educational data mining, learning analytics, learning-at-scale, student modeling, and artificial intelligence communities. You’ll also gain experience with standard data mining methods frequently applied to educational data. You will learn how to apply these methods and when to apply them, as well as their strengths and weaknesses for different applications.
The course will discuss how to use each method to answer education research questions, and to drive intervention and improvement in educational software and systems. Methods will be covered at a theoretical level, and in terms of learning how to apply them in Python or using software tools like RapidMiner. We will also discuss validity and generalizability; establishing how trustworthy and applicable the analysis results.
Syllabus
Week 1: Prediction Modeling
Regressors Classifiers
Week 2: Model Goodness and Validation
Detector Confidence Diagnostic Metrics * Cross-Validation and Over-Fitting
Week 3: Behavior Detection and Feature Engineering
Ground Truth for Behavior Detection Data Synchronization and Grain Size
Feature Engineering Knowledge Engineering
Week 4: Knowledge Inference
Knowledge Inference Bayesian Knowledge Tracing (BKT)
Performance Factor Analysis Item Response Theory
Week 5: Relationship Mining
Correlation Mining Causal Mining
Association Rule Mining Sequential Pattern Mining * Network Analysis
Week 6: Visualization
Learning Curves Moment by Moment Learning Graphs
Scatter Plots State Space Diagrams * Other Awesome EDM Visualizations
Week 7: Structure Discovery
Clustering Validation and Selection
Factor Analysis Knowledge Inference Structures
Week 8: Discovery with Models
Discovery with Models Text Mining * Hidden Markov Models