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.