Exploring STEM Educational Delivery for Youth in Norfolk Juvenile Detention Center
Lead PI:
Sampath Jayarathna

Detained youth are a population that experience disparities in educational opportunities and in particular, have systemically fewer rich opportunities for STEM learning. Access to educational resources and STEM learning for detained youth are critical to position them to have marketable employment skills and potentially contribute to the STEM workforce of the future. Taking lessons from the conditions and challenges posed by the COVID-19 pandemic, this project seeks to develop and deliver a Personal Learning Environment for Youth, an educational ecosystem that is accessible to a wide range of detained youth learners and provides individual tailoring based on youth interactions with the system. To develop the system, the project takes input from a multidisciplinary juvenile justice community collaborative working group that examines the existing educational infrastructure, determines challenges and affordances, and provides input into the design and delivery of the personalized learning system. The outcome of this research will be a framework for facilitating STEM learning for detained youth using smart and connected technologies.

The project takes place in the context of the Norfolk Juvenile Detention Center (NJDC). The work pursues a set of research questions that seek to identify the barriers and factors impacting accessibility to STEM learning and educational services, how the pandemic conditions changed those challenges, and anticipates the predicted challenges to delivering a personalized learning STEM education ecosystem. Stakeholders, including the center's academic staff, management, the public school system, and personnel related to juvenile justice, form a focus group engaged in conversation about the current educational ecosystem and the design features that would support stronger STEM learning for a personalized system. Participant responses will be distilled into design principles using grounded theory that will guide the design and development of the personalized learning system. The primary outcome of the research will be a case study that describes the framework for the personalized learning system and the design principles on which it rests.

Sampath Jayarathna
I received my Ph.D. in Computer Science from Texas A&M University in 2016, advised by Frank Shipman. Before that, I earned M.S. degree in Computer Science from Texas State University in 2010, advised by Oleg Komogortsev. My undergraduate degree is a B.S in Computer Science (First Class) from University of Peradeniya, Sri Lanka in 2006. I joined the faculty at Old Dominion University in 2018. Before that, I was a tenure-track faculty at Cal Poly Pomona (2016-2018). I am a recipient of 2021 NSF CAREER award. My research interests lie in the use and development of data science, information retrieval and machine learning techniques for effective and efficient adaptive information access. I leverage cross-disciplinary approaches to capture user intent dynamically during information-seeking behaviors and contribute to the fundamental understanding of human-information interaction by looking at how people locate and use information. I enjoy connecting the dots between disciplines and explore computational techniques to build user models from large-scale user interaction data. In addition, I apply methods in areas ranging from perception, cognition and psycho-physiological measurements (e.g., EEG, eye tracking, and wearable devices) by probing the thoughts of people conducting searches, simulating presumed cognitive functions with computational algorithms and observing information behavior in everyday tasks.
Performance Period: 10/01/2021 - 09/30/2024
Institution: Old Dominion University Research Foundation
Sponsor: National Science Foundation
Award Number: 2125395