Teachers and administrators have access to more data on how their students are learning than ever before. Through learning management systems and educational technology, they can potentially see what teaching methods resonate and which fall short. But many educators can't or don't use the data they have to make changes in their classrooms. A grant from the Institute of Education Sciences will help Carnegie Mellon University train teachers to make better use of this data through a new program called Data Science for Education (DS4EDU).

John Stamper, an associate professor at the Human-Computer Interaction Institute, is the principal investigator on the project, working with 11 co-principal investigators from CMU — many of whom are affiliated with the School of Computer Science. The CMU team will collaborate with three recruiting partners and receive additional support from CMU learning engineers. 

Stamper said that data science expertise is desperately needed in education, from the classroom to the district level.

"We've reached this point where data is finally being collected at a scale that we can make use of it quickly and efficiently. And to do that, we need folks who have the skills to be able to analyze, look at that data and make judgments," he said. "Teachers are already getting data in a lot of ways by using learning management systems and other tools. This will help them actually use that data and make a difference in their classrooms."

The yearlong program for teachers and administrators includes funding for three cohorts of 25 educational practitioners. Students will attend a weeklong intensive training at CMU's LearnLab Summer School, a long-standing program focused on technology-enhanced learning. The remaining coursework will continue online using CMU's Open Learning Initiative courseware.

Stamper said a hallmark of the program will be mentorship from its many co-principal investigators, who include representation from CMU's Simon Initiative, Master of Educational Technology and Applied Learning Sciences (METALS) program, Department of Statistics & Data Science, and Master of Computational Data Science program.

"Data Science for Education truly highlights the strength of our data science and learning engineering programs," Stamper said. "Bringing together all of these experts will be a boon for the students."

For more information, read the full story on the CMU News website.