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Book Review: Handbook of Educational Data Mining

  • Writer: Nirmal Patel
    Nirmal Patel
  • Jul 15, 2021
  • 2 min read

Updated: Dec 5, 2021

In this short article, I am going to review the Handbook of Educational Data Mining. It is one of the most amazing introductions to the Educational Data Mining field. The book is a collection of articles divided into two parts. The first section walks through data mining methods commonly used in Educational Data Mining (or EDM) field, and the second section is a collection of case studies that presents so many different dimensions and applications of EDM methods.



The first part of the book has a certain focus on outlining various algorithms or methods that are commonly used to analyze educational data. For example, data visualizations, clustering, bayesian models, process analysis, etc. The sequence of the chapters is also partly in chronological order in terms of the methods’ introduction into the education research domain. Here are the chapters in the first section of the book:


  1. Visualization in Educational Environments

  2. Basics of Statistical Analysis of Interactions Data from Web-Based Learning Environments

  3. A Data Repository for the EDM Community: The PSLC DataShop

  4. Classifiers for EDM

  5. Clustering Educational Data

  6. Association Rule Mining in Learning Management Systems

  7. Sequential Pattern Analysis of Learning Logs: Methodology and Applications

  8. Process Mining from Educational Data

  9. Modeling Hierarchy and Dependence among Task Responses in EDM

This is a great introduction to the EDM field if you have not analyzed educational data before, but are aware of the statistical and computational methods of data mining. As more educators are using educational data every day, EDM methods are becoming more relevant. The explosion of online learning has also given a boost to the EDM field, as digital learning platforms collect vast amounts of learner data. We can use EDM on big educational data and get actionable insights that can directly impact student learning. Educational data also open rich possibilities for classroom technologies.


If you are interested in learning EDM, you should find a copy of this book. Also, if you are interested in knowing what's current in EDM, consider attending the 2021 Educational Data Mining Conference that is taking place virtually as well as in-person https://educationaldatamining.org/edm2021/


Have a great day.

 
 
 

1 Comment


Robusto
2 days ago

The book's structure, covering both core methods and practical case studies, makes it an excellent resource for anyone looking to apply data mining techniques to education. The chapter on process mining and the PSLC DataShop are particularly valuable for analyzing learning patterns. For those interested in data collection and delivery systems, you might also find it helpful to know the how to contact spark driver page if you're involved in app-based logistics or gig work. Understanding data flows from different fields can offer broader insights into how information is gathered and used.

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