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.
That sort of predictive analytics has long been embraced by corporations, but not so much by the academy.
The ongoing data-mining effort, which was kicked off last year with a $1 million grant from the Bill and Melinda Gates Foundation, is being led by WCET, the WICHE Cooperative for Educational Technologies.
A broad range of institutions (see factbox) are participating. Six major for-profits, research universities and community colleges — the sort of group that doesn’t always play nice — are sharing the vault of information and tips on how to put the data to work.
“Having the University of Phoenix and American Public University, it’s huge,” said Dan Huston, coordinator of strategic systems at Rio Salado College, a participant.
According to early findings from the research, at-risk students do better if they ease into online education with a small number of courses, which flies in the face of widely-held belief in the benefits of full student immersion.
Click through for full article text.