PERC 2021 Abstract Detail Page
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| Abstract Title: | Characterizing social behavior patterns in teaching assistant interactions with students |
|---|---|
| Abstract: | Theory on teacher-student relationship development in higher education is scarce despite the empirical work linking positive relationships to important student outcomes. To advance research in this area, this study explores using Epistemic Network Analysis, a technique that characterizes patterns in data by visualizing them as connected graphs, to characterize patterns in social behaviors exhibited by Teaching Assistants in a large-enrollment algebra-based physics course for non-majors. We recorded classroom interactions between teaching assistants and students in synchronous remote active-learning problem-solving sessions and coded the interactions for the types of social behaviors exhibited by the Teaching Assistants (e.g., addressing students by name or empathizing with student difficulties) as they engage groups of 2-3 students in breakout rooms. Using a validated survey measuring a construct related to teacher-student relationship quality, we identified the two instructors with the highest-rated and lowest-rated scores and compared the connected graphs describing the patterns in their social practices. We present the graphs and generate hypotheses about which social behaviors may contribute most to building or damaging relationships between Teaching Assistants and students. Our results can guide future research in Teaching Assistant-student relationships in physics classrooms and have implications for training Teaching Assistants to build rapport with students. |
| Abstract Type: | Contributed Poster Presentation |
| Session Time: | Poster Session 2 Room B |
| Poster Number: | 2B-18 |
Author/Organizer Information | |
| Primary Contact: |
Joe Olsen Rutgers University |
| Co-Author(s) and Co-Presenter(s) |
Nicolette Maggiore, Rutgers University Debbie Andres, Rutgers University Charles Ruggieri, Rutgers University |
