From Paul Fain in Inside Higher Ed
As the participants point out, this is cracking open a door that soon should be kicked down. Congratulations to those who have invested in this project. Thinking of friends Todd Gibby (@intelliworks) and David Yaskin (@starfish360) because this is where they've been trying to drag all of us academics for several years now!
Using Big Data to Predict Online Student Success | Inside Higher Ed
As the participants point out, this is cracking open a door that soon should be kicked down. Congratulations to those who have invested in this project. Thinking of friends Todd Gibby (@intelliworks) and David Yaskin (@starfish360) because this is where they've been trying to drag all of us academics for several years now!
Using Big Data to Predict Online Student Success | Inside Higher Ed
New students are more likely to drop out of online colleges if they take full courseloads than if they enroll part time, according to findings from a research project that is challenging conventional wisdom about student success.
But perhaps more important than that potentially game-changing nugget, researchers said, is how the project has chipped away at skepticism in higher education about the power of “big data.”
Researchers have created a database that measures 33 variables for the online coursework of 640,000 students – a whopping 3 million course-level records. While the work is far from complete, the variables help track student performance and retention across a broad range of demographic factors. The data can show what works at a specific type of institution, and what doesn’t.
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