Brittany Paloma Fiedler is a Teaching and Learning Librarian at the University of Nevada Las Vegas. She previously worked as a middle school librarian and high school English teacher. She was a 2015-2016 ALA Spectrum Scholar and is a 2018 ALA Emerging Leader.
Chelsea Heinbach is a Teaching and Learning Librarian at the University of Nevada, Las Vegas. Prior to UNLV, she taught at the University of California, Santa Barbara and Auraria Library in Denver, CO. She is a co-founder and editor of The Librarian Parlor and she tweets here.
This post is the third in a series called “How Do You Even…” where we reflect on the research process as new-to-research librarians. Check out our first post on getting started and our second post on doing research, collecting data, and presenting at conferences. In this post, we will talk about choosing where to publish, analyzing the data, and navigating collaborative writing and open peer review.
Choosing where to publish
In the Library with the Lead Pipe (ITLWLP) is one of our favorite journals to read because it’s open access and their style guide includes a commitment to inclusive language. It was our first choice because it so clearly aligned with our values. As a bonus for new researchers like us, we could propose the article by submitting an abstract before actually having to write the whole thing. We’ve been advised many times to write articles with a specific journal in mind, and if our proposal wasn’t accepted, we would have focused on a different part of our research for a different publication (check out Nina Exner’s helpful post on Picking a Journal).
Once we decided where we wanted to publish, we thoroughly read the ITLWLP style guide, submission guidelines, and publication process. We prepared a proposal which included an abstract, a link to writing samples, current CVs (pro tip: always have a current CV!). Our proposal was accepted and we sent happy GChat messages featuring many exclamation marks.
Data Analysis
We de-identified the 21 interview recordings and uploaded them to a shared Google drive folder. One of our co-authors, Emily Pattni, transcribed the interviews. This took her 3ish hours each for a total of 64ish hours. She was an LIS student working as an Outreach and Instruction Specialist in our department, and we were super lucky to have her insight throughout the process.
We had 21 transcribed interviews, but we needed to make sense of all that data. We read a lot about qualitative research and content analysis (we highly recommend “Three Approaches to Qualitative Content Analysis”) and ultimately decided to use a pretty conventional method with slight modifications. We started, as always, by reviewing our research questions. Then we brainstormed codes using these guidelines:
- Codes should cover ONE aspect only, with no more than 15 total
- Subcodes should be mutually exclusive
- There should be no more than three hierarchical levels – nothing beyond sub-subcode
Finally, we tried actually coding an interview. This process was iterative: review research questions, code an interview, edit codes, repeat. An example of this evolution can be seen here:
| Brainstormed Coding Frame | Final Coding Frame |
| 1. UNLV Experiences a. Library Experiences i. Transactional ii. Learning iii. Social space iv. Independent use of space b. Impressions of Library i. Hopes for future ii. General c. Using campus (non-Library) services |
1. Campus resource use (non-library) 2. UNLV Library Experiences a. Services b. Impressions c. Resources d. Spaces used e. Wishes |
We independently hand coded three interviews that purposefully represented different student experiences and then met to review our work and norm the codes. This process worked as a kind of calibration to ensure we coded consistently. As mentioned before, we are fortunate to work at UNLV which has many resources for conducting research. We had access to the software ATLAS.ti (similar to NVivo or Dedoose). If we didn’t have access to software, we could have done it by hand which takes more time. We hope to see open source alternatives pop up in the future.
We each coded eight interviews, one of which overlapped with another PI to check for consistency. It took approximately 1-2 hours to code each interview. After we were done, we sent everything to our auditor who randomly checked 10% of the codes against their definitions to ensure consistent usage. Finally, we discussed our impressions of the data and collectively looked for overarching themes about the transfer student experience.
Writing and Editing
“This method required trust between the collaborators because we had to be willing to edit each other’s work.”
We tried two new things with this paper: a collaborative writing process and open peer review. Based on past projects, we felt that writing sections separately could lead to repetition and uneven voices in the final work. Instead, all of the authors worked together to outline each section, then the first author wrote a draft of that section entirely on her own. We continued this process of outlining and writing for each section of the paper. After we had a working draft, we spent about one week editing together, in each other’s offices and in empty classrooms. We also spent a fair amount of time going back and forth on Google doc comments. This method required trust between the collaborators because we had to be willing to edit each other’s work. This was beneficial because we were able to discuss and formalize the most important parts of the paper in a way that strengthened our message. Once we got the paper in decent enough shape, we sent it out to three people who would give different kinds of feedback. We also sent the paper to Emily, our auditor, to ensure her views were represented. Lastly, each of us individually printed out and hand edited the draft.
“The open peer review process was iterative, highly communicative, and gave us the opportunity to connect with colleagues in meaningful ways.”
ITLWLP uses open peer review, which we found extremely valuable. We received excellent constructive feedback from our chosen reviewer, Eamon Tewell, our ITLWLP reviewer, Kellee Warren, and our ITLWLP editor, Denisse Solis. We used Google docs to communicate, and all of them were generous and thoughtful. The open peer review process was iterative, highly communicative, and gave us the opportunity to connect with colleagues in meaningful ways. To learn more about open peer review at ITLWLP, see Sarah Hare’s post.
We are very proud of our collaboration, our research, and our paper: Dismantling Deficit Thinking: A Strengths-based Inquiry Into the Experiences of Transfer Students In and Out of Academic Libraries.
Acknowledgements
We are indebted to so many people for this experience. Thank you to Rosan Mitola, for bringing us on to this project, and to Emily Pattni for your expertise along the way. Thanks to Eamon Tewell, our external reviewer, Kellee Warren our internal reviewer, and Denisse Solis, our publishing editor. This paper wouldn’t be what it is without your thoughtful questions, prompts, and insights and we are deeply appreciative. Thank you to Kevin Seeber for talking through this idea at the very beginning stages and inspiring us to purposefully avoid focusing on the deficit, to Melissa Bowles-Terry, Erin Rinto, and Susie Skarl for reading drafts and sharing your thoughts, to James Cheng for helping us ground our ideas in a methodology, and to the Mason Undergraduate Peer Research Coaches for testing our interview questions and offering your perspective. Finally, thank you to the amazing UNLV transfer students who shared their experiences with us. Talking to students is why we love our work and we appreciate you spending time letting us get to know you.
Featured image [CC0], via Pexels
This work is licensed under a Creative Commons Attribution 4.0 International License.
The expressions of the writers do not reflect anyone’s views but their own.
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