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Abstract Title: Lens to Learning: Automating assessment of student groups based on visual cues
Abstract: Is it possible to tell -- just by watching student groups in a classroom -- the kinds of discussions they are having? Is information about students' activities reliably expressed in visual observables like gestures, posture, and facial expressions? We describe collaborative research between physics education and computer vision to automate assessment of student group behavior based on visual cues.
Abstract Type: Contributed Poster Presentation

Author/Organizer Information

Primary Contact: Laura Tucker
Harvard University
Co-Author(s)
and Co-Presenter(s)
Rachel Scherr (Seattle Pacific University), Todd Zickler (Harvard University), Ruonan Li (Harvard University), and Eric Mazur (Harvard University)