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The Institute for Student‐AI Teaming (iSAT) addresses the foundational question:how to promote deep conceptual learning via rich socio‐collaborative learning experiences for all students?—a question that is ripe for AI‐based facilitation and has the potential to transform classrooms. We advance research in speech, computer vision, human‐agent teaming, computer‐supported collaborative learning, expansive co‐design, and the science of broadening participation to design and study next generation AI technologies (called AI Partners) embedded in student collaborative learning teams in coordination with teachers. Our institute ascribes to theoretical perspectives that aim to create a normative environment of widespread engagement through responsible design of technology, curriculum, and pedagogy in partnership with K–12 educators, racially diverse students, parents, and other community members.

 

During COVID-19 pandemic, people’s lifestyles have been changed dramatically and an increase of depression among young adults has been observed. Most universities or colleges offered online courses instead to prevent COVID transmission. Typically, home environment is not designed for work or learning. Despite that the relationships between indoor environment quality (IEQ) and people’s physical health and work performance have been investigated in regular time, very few efforts have been taken to understand the relationship between IEQ and students’ mental health and learning performance during COVID-19 when mental health and learning have become more crucial due to the face-to-face classes suspension, stay-at-home policies. The research gap exists on how IEQ at home or similar residential buildings is related to mental health and learning. This work aims to 1) understand how indoor environmental (such as thermal, air quality, lighting, acoustic) satisfaction is related to college students’ mental health and learning performance, and 2) predict depression with IEQ satisfaction.