Sangam: A Confluence of Knowledge Streams

USING APPLIED CONVERSATION ANALYSIS AND MEMBERSHIP CATEGORIZATION ANALYSIS TO STUDY STEM GRADUATE STUDENT TEACHING DEVELOPMENT

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dc.contributor Buck, Gayle A.
dc.contributor Lester, Jessica Nina
dc.creator Williamson, Francesca Arielle
dc.date 2020-06-25T15:49:47Z
dc.date 2020-06-25T15:49:47Z
dc.date 2020-06
dc.date.accessioned 2023-02-24T18:26:16Z
dc.date.available 2023-02-24T18:26:16Z
dc.identifier http://hdl.handle.net/2022/25645
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/260264
dc.description Thesis (Ph.D.) - Indiana University, School of Education/University Graduate School, 2020
dc.description United States (US) stakeholders have advocated for increased preparation for teaching for the next generation of faculty as a key higher education reform strategy in fields of science, technology, engineering, and mathematics (STEM). It has been argued that this strategy can increase the number of skilled STEM professionals, improve scientific literacy of the US populace, and foster diversity, equity, and inclusivity within these fields. The literature about the practice and outcomes of STEM graduate student teaching development, however, has indicated that the implementation of this reform strategy varies in quality and has been understudied. This study took a novel, discursive approach to study STEM graduate student teaching development. Specifically, I combined applied conversation analysis (CA) and membership categorization analysis (MCA) to study how participants used language to co-construct social actions to achieve the practice of teaching development. Few studies have combined applied CA and MCA, thus this study also pursued methodological engagement between these two approaches to contribute to the analytic practices for characterizing the sequential and categorial organizations of social interaction. Data included 18 hours of video- and audio-recordings of face-to-face meetings for three types of teaching development: (1) a multidisciplinary STEM learning community, (2) a discipline-specific seminar, and (3) an identity-based co-curricular learning community. Disagreement was found to be a common social action co-produced by participants and shaped by the distinctive interactional contexts of each group. Notably, three forms of disagreement were found and characterized in terms of their sequential and categorial organizations: uncontested, contested, and affiliative disagreements. These disagreements served many functions, such as providing critiques, introducing moral dilemmas, questioning the feasibility of implementing evidence-based practice, and offering support. Additionally, by combining applied CA and MCA, I identified two categorial practices involved in the co-construction of disagreements: categorial linking and categorial resistance or reorganization. This analysis made visible, at the level of language-use, how normative cultures in STEM disciplines are constructed, negotiated, and subsequently shape discourse about teaching and learning. Overall, this study contributes substantive and methodological knowledge about the production disagreements in teaching development meetings and has important implications for research and efforts to promote change in STEM higher education.
dc.language en
dc.publisher [Bloomington, Ind.] : Indiana University
dc.subject STEM graduate student and future faculty teaching development
dc.subject conversation analysis
dc.subject membership categorization analysis
dc.title USING APPLIED CONVERSATION ANALYSIS AND MEMBERSHIP CATEGORIZATION ANALYSIS TO STUDY STEM GRADUATE STUDENT TEACHING DEVELOPMENT
dc.type Doctoral Dissertation


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