Coding Like a Data Miner: A Culturally Relevant Data Analytics Intervention for High School Students
Supported by The National Science Foundation
Project led by:
Amanda Barany, PhD
Amanda Barany, PhD, a postdoctoral scholar from Drexel’s School of Education, is leveraging data mining techniques and the affordances of online social media spaces to design and implement a culturally relevant data analytics intervention for high school students. The goal of the project is to better understand what it takes to successfully design and deploy a high school curriculum in burgeoning and critically needed areas of computing. This work is supported by a $300,000 grant from the National Science Foundation (NSF).
The grant is an interdisciplinary collaboration that includes Amanda Barany, Ph.D., postdoctoral scholar for the Louis Stokes Alliance for Minority Participation (LSAMP) through the Drexel University School of Education, Justice Walker, Ph.D., assistant professor of STEM Education in the College of Education at the University of Texas at El Paso (UTEP), and Omar Badreddin, Ph.D., assistant professor of computer science in the UTEP College of Engineering. Their collective expertise will inform theoretically grounded and equity-driven best practices for developing culturally relevant computer science education interventions that are at the very edge of technical innovation and pedagogy in these fields. The curriculum will be co-designed by El Paso-region teachers and students who will help reimagine what it means, and takes, 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. 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. With social media’s growing prominence in shaping social discourse and public perception, it makes sense that we’d consider ways to shift how learners interact with the platform—toward a more unconventional, computational, and critical form of engagement. 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.”
This project is a continued stride toward Drexel’s mission to prepare each new generation of students for productive professional and civic lives while also focusing our collective expertise on solving society's greatest problems. The work also represents another example of technical and pedagogical innovation aimed at developing leaders with the expertise to collaborate and solve complex problems through the Drexel University School of Education.