Institute-wide
Students work through one of iSAT's curriculum units.
Our Institute-wide team is responsible for overseeing all of iSAT's core research, using the data collected to help identify and implement useful components of the AI partners. The four areas of focus are: AI Partner Design, Implementation, and Testing, Classroom Data Collection and Coordinated Analysis, Technical Architecture, and Collaborative Problem Solving Framework.
This theme focuses on the main activities supporting the design, implementation, and testing of the AI Partners. This requires managing a cross-Institute roadmap ranging from conceptualization to implementation and validation for different versions of AI Partners.
Classroom data collection collects high-quality audio and video student-to-student interactions and student/teacher interactions and annotates and formats the data in ways that it can be widely used for data analysis, partner development and testing, and evaluation.
This theme focuses on developing the core infrastructure and components for the AI Partners, supporting integration of AI models and services into the AI Partners and supporting secure data storage access to data collections from the classroom and lab.
This theme focuses on the need to successfully identify the basis of collaborative problem-solving skills including social, affective, and cognitive processes, identify features of successful collaboration, and identify how to promote equitable and trusted interactions in team problem solving.