Carnegie Mellon project revives failed inBloom dream to store and analyze student data
Privacy controversy to be dodged by not storing student names, addresses or social security numbers
LearnSphere, a new $5 million federally-funded project at Carnegie Mellon University, aims to become “the biggest open repository of education data” in the world, according to the project leader, Ken Koedinger.
If you think that sounds ambitious and a lot like inBloom, the Gates Foundation-funded non-profit that shut its doors in 2014 after student privacy fears escalated, you’re right.
“There certainly are some similarities,” said Koedinger, a professor of human computer interaction and psychology at Carnegie Mellon University.
An internationally renowned leader in the field of education technology, Koedinger’s known for developing the mathematical models that drive “cognitive tutors,” which tailor instruction to individual students. He’s also a co-founder of Carnegie Learning, an educational software business that was spun off from Carnegie Mellon in 1998, and whose software is currently used by 400,000 students.
Koedinger launched LearnSphere earlier this year with the hope of making it easier and faster for researchers to analyze big datasets — mostly student keyboard clicks — in order to test educational theories and boost learning outcomes from elementary school to college. Just as inBloom had hoped software makers and researchers would use its vast database to improve education technology, Koedinger also wants to create a forum for sharing and analyzing data on how students learn. But, he says, there are important differences between LearnSphere and inBloom.
For one, he says he’s not going to allow any personal information from school records in LearnSphere.
“In some ways, it’s a deep philosophical difference,” Koedinger said. “We are not looking that much at collecting demographic data and certainly not any kind of record information. Those are the things that tend to be particularly sensitive.”
No student names, no addresses, no zip codes, no social security numbers, he says. No race, family income or special education designations. “The student identifier column, even if yours is already anonymized, we re-anonymize it automatically,” he added.
There may be demographic information on a school — for example, the percentage of student who qualify for free or reduced-price lunches. But Koedinger says that even the school name is anonymized in most cases.
Unlike inBloom, which wanted public school districts to use its Carnegie Mellon project revives failed inBloom dream to store and analyze student data - The Hechinger Report:
