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Title: CS Teaching and Racial Identities in Interaction: A Case for Discourse Analytic Methods
Motivation. Teachers can play a role in disrupting social inequities that are reflected in education, such as racial disparities in who succeeds in CS. Professional learning addressing inequities causes teachers to confront difficult topics, including how their own identities impact these problems. Understanding the differing ways teachers’ identities surface can provide insights into designing better supports for their professional learning. Objectives. The goal of this paper is to examine the teaching and racial identities of two secondary CS teachers who participated in professional learning focused on combining CS content and equity pedagogy. The second goal of this paper is to demonstrate how discourse analytic methods can be used to examine interviews and other interactional data. Method. Teachers were interviewed individually about their teaching identity, racial identity, and professional learning. Drawing on Bucholtz and Hall’s identity and interaction framework, interviews were examined for linguistic and discursive features reflecting positionality (i.e., how identity surfaces through the way individuals present themselves to and are perceived by others) and indexicality (i.e., various ways of referring to an identity). Results. Participants used personal deictics, quotative markers, code choice, and affective and epistemic stances when discussing and negotiating their identities with the interviewer. The data reflected ways teachers problematized questions about teaching identity, negotiated tensions in their disciplinary identities, found the topic of race difficult to address, and highlighted other aspects of their identities relevant to understanding and discussing race. Discussion. The study provides a demonstration of how discourse analytic methods can reveal nuances of teacher identity that may be overlooked with other qualitative approaches. Findings also revealed how teachers’ ethnic identities might be used as a lever in helping teachers discuss the difficult topic of race in education. Discourse analytic methods are encouraged for future CS education research focused on interactional analyses.  more » « less
Award ID(s):
2124841
PAR ID:
10425821
Author(s) / Creator(s):
Date Published:
Journal Name:
2023 ACM Conference on International Computing Education Research
Volume:
1
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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