Directly.me Big Data in EducationIntroduction to course:
With the use of internet increasing at such a fast pace, education is also increasingly occurring online. Besides online educational courses, there are a number of educational softwares as well that the websites are using to promote distant learning. This has led to an outburst of data that can be used to improve educational effectiveness and support basic research on learning. This course has been designed to help students learn how and when to use key methods for educational data mining and learning analytics on this data.
Who should take this course?
People related to online education or those planning to enter this field can take this course to improve their data mining skills. People usually think that only programmers can take these kind of courses, but for this course experience with programming is not required. However, the participants should have basic knowledge of either statistics, data mining, mathematical modelling, or algorithms.
What you will learn in this course?
In this course you will learn data mining methods and models and their strengths and weaknesses for different applications. It will cover data mining methods at a theoretical level as well as in terms of how to apply and execute them using standard software tools. You will also learn to use these methods to answer education research questions and improve answer education research questions. You will also be able to develop models for data mining.
Table of content:
- Prediction Modelling
- Behaviour Detection
- Behaviour Detector Validation
- Relationship Mining
- Discovery with Models
- Visualization of Educational Data
- Knowledge Inference
- Structure Discovery: Knowledge Structures
- Structure Discovery: Clustering and Factor Analysis
- Educational Databases
Author Bio:
This free online course has been prepared by Ryan Shaun Joazeiro de Baker, a Visiting Associate Professor at Teachers College, Columbia University.
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Big Data in Education
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Introduction to course:
With the use of internet increasing at such a fast pace, education is also increasingly occurring online. Besides online educational courses, there are a number of educational softwares as well that the websites are using to promote distant learning. This has led to an outburst of data that can be used to improve educational effectiveness and support basic research on learning. This course has been designed to help students learn how and when to use key methods for educational data mining and learning analytics on this data.
Who should take this course?
People related to online education or those planning to enter this field can take this course to improve their data mining skills. People usually think that only programmers can take these kind of courses, but for this course experience with programming is not required. However, the participants should have basic knowledge of either statistics, data mining, mathematical modelling, or algorithms.
What you will learn in this course?
In this course you will learn data mining methods and models and their strengths and weaknesses for different applications. It will cover data mining methods at a theoretical level as well as in terms of how to apply and execute them using standard software tools. You will also learn to use these methods to answer education research questions and improve answer education research questions. You will also be able to develop models for data mining.
Table of content:
- Prediction Modelling
- Behaviour Detection
- Behaviour Detector Validation
- Relationship Mining
- Discovery with Models
- Visualization of Educational Data
- Knowledge Inference
- Structure Discovery: Knowledge Structures
- Structure Discovery: Clustering and Factor Analysis
- Educational Databases
Author Bio:
This free online course has been prepared by Ryan Shaun Joazeiro de Baker, a Visiting Associate Professor at Teachers College, Columbia University.

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