EAGER: A Training Tool to Help Teachers Recognize and Reduce Bias in Their Classroom Behaviors and Increase Interpersonal Competence

Cornell University, Ithaca NY

Investigators

Abstract

What teachers say is important, but how they say it is also important. Nonverbal behavior can unintentionally convey information about teachers’ emotional states and personal biases. Poor nonverbal communication can affect teachers’ abilities to deliver lessons, assess students and manage classrooms. Effective nonverbal communication increases student engagement, improves classroom management, and make students feel that the teacher cares about them. Students with teachers who communicate effectively nonverbally are more motivated to learn and demonstrate more academic progress. Nonverbal communication is a skill that can be improved with guidance and reflection. This project will work with students and teachers to prototype training modules in virtual reality that track teacher movement. This will compare teachers’ nonverbal behaviors with transformed nonverbal behaviors that would effectively engage students. It will also give students from underrepresented backgrounds the opportunity to observe and participate in our research at both Cornell University and University of North Texas through lab visits. This Early Grant for Exploratory Research (EAGER) will contribute to the fields of education and learning technologies by exploring how nonverbal behaviors are expressed and can best be transformed in virtual reality classrooms, and how skills learned in virtual reality environments can be transferred to teaching in physical classrooms. This exploration will advance our theoretical understanding of how teachers use nonverbal behavior effectively in the classroom and develop novel techniques for helping teachers to recognize and selectively adapt nonverbal behavior to their individual students’ interpersonal communication styles in the context of small to medium classes (5-30 students). The exploration will also contribute to the field of human-computer interaction through the development of novel interfaces to display contextualized nonverbal behavior and promote reflection on this behavior, as well as to the fields of social psychology, communication, Computer-Mediated Communication (CMC), teacher education, and computer-supported collaborative work by developing new corpora and theoretical models of how nonverbal behaviors are evidenced in classroom settings. This EAGER will contribute to designing guidelines on how to aid self-reflection on nonverbal behavior, and how behavior is interpreted in the classroom by both teachers and students. 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.