The chair of Marymount University’s Department of Information Technology is on a team that won a $10,000 award from the Arlington Public Schools in a competition to use “big data” to predict – and improve – student success.
Dr. Diane Murphy was part of Deep Learning Analytics and Afliates, which beat out 22 other competitors. It used extensive student data, such as test scores, grades,
attendance and demographics, to predict factors such as early warning signs of students at risk of dropping out.
“It was a good beginning,” Murphy said. “Now we’re going to do extra analysis pro bono for the school system.”
In addition to lowering drop-out rates, the school system wants to increase the number of students who earn advanced diplomas and identify those who could be successful career and technology students.
Other members of the six-person team included John Kaufhold, managing partner at Deep Learning Analytics; Aaron Schumacher, a data scientist with Booz Allen Hamilton; Tommy Shen, a consultant to the World Bank; Ajay Deonarine, an analyst with AIG; and Alec Hubel, a student at the University of California, Berkeley.
“Big Data ofers us a new frontier to look closely at our practices and reevaluate our work in relationship to our goal of preparing and supporting all students to be successful and productive students,” said Dr. Pat Murphy, Arlington superintendent of schools.
The competition was sponsored by CK-12, a Silicon Valley-based non-profit that works to improve education access around the globe.
