Despite being an emotionally charged profession, there is a paucity of research on the roles of emotions and emotional labor in Teaching English to Speakers of Other Languages (Khong & Saito, 2014; Kocabas¸-Gedik & Hart, 2021; Schutz & Lee, 2014; Zembylas & Schutz, 2009). Furthermore, these concepts and their link to identity formation in nonnative English-speaking teachers (NNEST) have rarely been investigated in local contexts (Song, 2018; Zhang & Zhu, 2008). In order to help fill this gap in literature, this exploratory qualitative study was conducted in Korea with three NNESTs of English employed in private after-school academies. Semi-structured interviews elicited narratives from the participants. The findings suggested that institutional, systematic, and cultural power structures influenced the emotions, emotional labor, and identities of the participants. The emotions felt by participants were heavily instrumented by their institutions when they felt the need to conform to their institution's image of a teacher, when they were forced to engage in duties they believed were distanced from education, and when their professionality was questioned. Emotional labor was found to be a necessary skill for participants as they had to suppress and conjure certain emotions both inside and outside the classroom. Their use of emotional labor was found to be critical to their job satisfaction as it assisted the participants in aligning themselves as professionals. Moreover, EFL teachers may merge or divide their professional and personal identities in reference to these power structures to protect, strengthen, or develop their identities. Further research is needed in local contexts, particularly those in private for-profit institutions in ultra-capitalist societies to examine the power structures involved and their influence on teacher emotions, emotional labor, and identity.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-2428 |
Date | 01 January 2022 |
Creators | Puckett, Emily |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations, 2020- |
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