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Abstract
Human life presents many unplanned twists and turns. No one escapes this world without facing adversity of some kind. Therefore, the value in teaching and researching resilience cannot be overstated. This research explores how life story interviewing with interactive methods (also referred to as “elicitation techniques”) provides an invaluable approach to investigating and understanding resilience. Specifically, a stepwise framework is offered for researching resilience as a co-constructed, relational phenomenon. Upon applying this framework through teaching an undergraduate senior seminar, I offer thematic observations of my students’ interviewing experiences to show how life storytelling promotes (a) embodied understandings of resilience, (b) an appreciation for others’ unique differences, and (c) strengthened relationships between interviewees and interviewers. These findings show promise for future teachers and researchers interested in exploring the relational benefits made possible through creative storytelling methods. The methods proposed in this study not only provide a means for exploring conceptualizations of resilience; in and of themselves, they enact resilience.
Keywords
life story interviewing, elicitation techniques, qualitative methods, resilience, relational, narrative
Acknowledgements
I offer gratitude to my students for their generous effort towards learning and demonstrating such sincerity throughout the process of our research together.
Publication Date
2-5-2022
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 International License.
DOI
10.46743/2160-3715/2022.5183
Recommended APA Citation
Russell, L. D. (2022). Life Story Interviewing as a Method to Co-Construct Narratives About Resilience. The Qualitative Report, 27(2), 348-365. https://doi.org/10.46743/2160-3715/2022.5183
ORCID ID
https://orcid.org/0000-0003-4530-4502
ResearcherID
5183
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Quantitative, Qualitative, Comparative, and Historical Methodologies Commons, Social Statistics Commons