Writing to grieve: Solidarity in times of loss in educational community spaces.
Published In: Journal of Adolescent & Adult Literacy, 2023, v. 67, n. 3. P. 136 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Peachey, Katie B.; Lee, Crystal Chen 3 of 3
Abstract
This qualitative case study is a part of a larger university–community partnership that explores adolescents' utilization of critical literacy to write, engage, and lead in their communities. For this specific study, we explore the question: How does an educational community use literacy practices and modalities to grieve through collective loss and develop solidarity with one another? Through the utilization of a critical literacy framework and a sense‐based pedagogy lens, we explore how various forms of literacy and multimodalities allowed this community to grieve and foster solidarity in a time of loss. We conducted several rounds of inductive and emotion codings to identify key themes from our data sources which included student work/publications, social media posts, organization communication, videos, focus groups, and staff interviews. Our preliminary findings show that (a) reciprocal vulnerability developed over time can produce solidarity; (b) writing can be a restorative act in collective loss; and (c) writing through grief positions students as leaders of their communities. Through this study, we provide educators and community members with potential tools for developing spaces for restorative education and supporting collective resilience through literacy practices. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Adolescent & Adult Literacy. 2023/11, Vol. 67, Issue 3, p136
- Document Type:Article
- Subject Area:Education
- Publication Date:2023
- ISSN:1081-3004
- DOI:10.1002/jaal.1313
- Accession Number:173230822
- Copyright Statement:Copyright of Journal of Adolescent & Adult Literacy is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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