Coding Like a UTEP Data Miner: NSF Grant Helps Bring Next-Generation Computing to High School Students

Last Updated on March 03, 2022 at 12:00 AM

Originally published March 03, 2022

By MC Staff

UTEP Communications

Justice Walker, Ph.D., assistant professor of STEM education in the College of Education at The University of Texas at El Paso, is leveraging data mining techniques to bring next-generation computer science education to teachers and students in the Paso del Norte region through a $300,000 grant from the National Science Foundation (NSF).

Justice Walker, Ph.D., center, assistant professor of STEM education in the College of Education at The University of Texas at El Paso, is the principal investigator of a $300,000 grant from the National Science Foundation that will bring next-generation computer science education to high school teachers and students in the Paso del Norte region. Walker stands with, from left, Sayed Mohsin Reza, doctoral student, and Omar Badreddin, Ph.D., assistant professor of computer science in the UTEP College of Engineering and a co-PI. Photo: J.R. Hernandez / UTEP Marketing and Communications

Walker, the grant’s principal investigator, leads an interdisciplinary collaboration with co-PIs Omar Badreddin, Ph.D., assistant professor of computer science in the UTEP College of Engineering, and Amanda Barany, Ph.D., postdoctoral scholar for the Louis Stokes Alliance for Minority Participation (LSAMP) through the Drexel University School of Education. With the help of Alan Barrera, College of Education research assistant, and Sayed Reza, College of Engineering research assistant, the trio’s goal is to better understand what it takes to successfully design and deploy a high school curriculum in burgeoning and critically needed areas of computing. 

The research group will work with teachers and students from throughout the region to develop culturally relevant computer science education interventions that use technical innovation in software design and online learning. The curriculum will help reimagine what it means to learn computer science in ways that are both personally meaningful and computationally rich.

“We know it is one thing to learn about cutting-edge data mining techniques and then apply them to datasets generated by others, but quite another for learners to build their own code to mine and to construct meaning on their own,” Walker said. “We are leveraging the ubiquitous social media platform Twitter as a sandbox for learners to mine data around topics or hashtags that are important to them.

“We’re investigating what happens when students are situated as producers in computer and data science rather than consumers. There’s a growing body of literature in the learning sciences and constructionism that suggest this paradigmatically distinct form of active learning can be a powerful and meaningful way for learners to access complex ideas.”