NSF Award
2417557
This project aims to serve the national interest by significantly advancing the understanding of how to provide guidance for neurodiverse teams of learners, in particular cultivating inclusion and engagement of neurodivergent learners in engineering. Engineering education literature on teamwork involving neurodiverse students is relatively sparse, in fact, most of the research on teamwork focuses on neurotypical majorities, with little attention to the strengths of neurodivergent minorities. Surveys of neurodivergent individuals reveal the social-emotional and sensory difficulties that reduce their participation in education and employment. It is known that interactional experiences like teamwork shape these students’ identity formation and provide opportunities to acquire executive functioning (EF) skills for planning, attaining goals, and regulating behaviors. This project will investigate engineering teamwork experience from a neurodivergent perspective and ascertain the effectiveness of an AI-driven intervention on students’ acquisition of EF skills as well as changes in their social-emotional and sensory challenges during teamwork. It is expected that the findings will plant the seeds for important cultural change by creating an education landscape that empowers and is empathetic toward neurodivergent students.<br/><br/>The goal of the project is to develop a prototype of an AI-driven platform for guiding neurodiverse teamwork. The utility of the platform in cultivating inclusion and engagement of neurodivergent learners in engineering will be investigated for the following purposes: (1) providing evidence-based guidance to improve EF skills in neurodiverse students during teamwork and (2) assisting professors mentor neurodiverse students during teamwork and (3) increasing neurodiversity awareness among faculty and students. A Large Language Model will be developed and managed - in the interest of data security - on the institution’s local research server. Three research questions will be investigated related to (i) identification of challenges experienced by neuro-divergent students; (ii) potential of AI to mitigate social-emotional and sensory challenges and (iii) feasibility of AI platform to foster enhanced inclusion and engagement. A mixed method approach is planned involving both qualitative and quantitative data collection as well as the use of validated instruments for measurement of Executive Functions. The robust and well-conceived dissemination plan includes the publication of a free online handbook of evidence-based strategies for mentoring neurodiverse students and a workshop to empower faculty - as ambassadors for neurodiversity in the school of engineering. Lessons learned will inform future AI-powered interventions revealing the benefits and limitations of the use of AI to foster inclusion and engagement of neurodiverse students in engineering. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
