Big Data and Education
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.
What you'll learn
- Key methods for educational data mining
- How to apply methods using Python's built-in machine learning library, scikit-learn
- How to apply methods using standard tools such as RapidMiner
- How to use methods to answer practical educational questions
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| Rating | 3.0★ based on 1 ratings |
|---|---|
| Length | 8 weeks |
| Effort | 8 weeks, 6–12 hours per week |
| Starts | On Demand (Start anytime) |
| Cost | $169 |
| From | University of Pennsylvania, PennX via edX |
| Instructor | Ryan Baker |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Data Science Education |
| Tags | Data Analysis & Statistics Education & Teacher Training |
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What people are saying
prof. baker speaks fast
Prof. Baker speaks fast and in "bullet points", constantly adding that he will talk "about it later".
good indicator of actual
Gaming the system may have negative effect on learning, and students' carelessness is not a good indicator of actual skills.
may have negative effect
recommend to take machine
If you're not famiar with data mining, I would recommend to take Machine Learning with A.Ng first.
intelligent tutoring system
Forum posts are very helpful though, and I've learned interesting facts from the "Predicting College Enrollment from Student Interaction with an Intelligent Tutoring System in Middle School" case study example.
predicting college enrollment
case study example
effect on learning
a.ng first
forum posts
middle school
student interaction
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| Rating | 3.0★ based on 1 ratings |
|---|---|
| Length | 8 weeks |
| Effort | 8 weeks, 6–12 hours per week |
| Starts | On Demand (Start anytime) |
| Cost | $169 |
| From | University of Pennsylvania, PennX via edX |
| Instructor | Ryan Baker |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Data Science Education |
| Tags | Data Analysis & Statistics Education & Teacher Training |
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