As part of my dissertation, I am writing a paper that describes a qualitative study based on interviews with chemistry ungrading faculty. The qualitative study process, including its communication, has been more difficult than it should be and the problem seems to be me.
Creswell and Poth (2024), in the 5th edition of Qualitative Inquiry and Research Design (often considered a defining text in qualitative research methodology classes), define qualitative research as:
Qualitative research begins with assumptions and the use of intepretive/theoretical frameworks that inform the study of research problems addressing the meaning individuals or groups ascribe to a social or human problem. To study this problem, qualitative researchers use an emerging qualitative approach to inquiry, the collection of data in a natural setting sensitive to the people and places under study, and data analysis that is both inductive and deductive and establishes patterns or themes. The final written report or presentation includes the voices of participants, the reflexivity of the researcher, a complex description and interpretation of the problem, and its contribution to the literature or a call for change. (Creswell, 2013, p. 44 as found in Creswell & Poth, 2024, p. 5)
As we can see from the second sentence of this definition, data analysis that “establishes patterns or themes” through inductive (drawing conclusions from observation) and deductive (drawing conclusions from general principles) requires the application of analytic coding schema to the data collection, which is usually open-ended surveys, interviews, narratives, etc. This definition is super broad in many ways but also specifically requires theoretical frameworks, a statement of the problem, collection of data, data analysis using coding schema, and communication of results that includes the voices of the participants, usually as excerpts from the data collection materials.
In practice (as I have experienced it), qualitative research requires the same things that quantitative research does: IRB approval (in the U.S. at least), data collection (that requires time, access to the population being studied, and possibly money), data cleaning, data analysis (usually several levels), member checking (if possible), and some kind of communication of results.
IMHO, qualitative research is much more difficult than quantitative research on almost every front (take that with a grain of salt as my masters degrees are in Chemistry and Statistics, which I clearly enjoy). Learning to do something like interviewing well takes art (asking questions in a way that they are mutually understood), not just science (figuring what makes a good question). Data cleaning requires transcribing the interviews, usually without something helpful like artificial intelligence (hello otter.ai) due to IRB constraints, and it is just beyond tedious. I honestly think that transcription is a such major barrier to qualitative research for those with a neurodivergence like ADHD that it may be the place where the qualitative research endeavor becomes impossible.
And then there is the data analysis, which, as we stated previously, usually involves analytically coding the data with labels of some sort. There are all kinds of coding schema. Saldaña (2016) alone describes at least 31 different first and second level coding schema, all with their specific data requirements, analysis requirements, and designations as to which labels should be applied to that data collected. Each coding schema requires essentially dividing the data into chunks upon which a code (quick example – in VAB coding, the codes are given and are value, attitude, or belief) can be applied and then using analytical memos and the codes that you have ascribed to the data chunks to find overall patterns or themes in the data.
Most qualitative researchers do not use one level of coding or one type of coding for a data set, but instead apply several layers of coding, reanalyzing the data afresh every time.
So then, what is the major problem with coding when one is an ungrader? Unfortunately, analytical coding feels like a lot like grading. Providing what feels like arbitrary labels to data and then trying to find meaningful patterns that collectively result somehow in an overall answer to a question (what is my course grade, for instance?)? Sound familiar?
There must be other ways to do this. And there are.
The excellent work pioneered by indigenous, critical, and Global Southern researchers has lead the way to more collaborative and more open qualitative methodologies , including ones that name those researched (ie participants) as coauthors or, going even further, ones that involve and include participants as co-research designers. Think participant design for research with constant member checking.
Aras Bozkurt (et al., 2020, 2023; Tlili et al., 2022) regularly adds participants as both coauthors and co-designers. His work centers educational technology, and he seems to purposefully choose diverse coauthors with diverse perspectives. Critical and indigenous qualitative methodologies question what even counts as research and the epistemology (what counts as knowledge?) undergirding data collection, analysis, and communication. Researchers in these areas include those who use qualitative research practices stemming from emancipatory pedagogies (Gay, 2010; Hannafin et al., 2014; Kiyama & Aguilar, 2018; Jhangiani et al., 2017; Ladson-Billings, 1994; Noel, 2016) and from indigenous research perspectives (Tuhiwai Smith, 2019 and 2023). And these are only some of the many, many researchers questioning and building new pathways through qualitative methodologies.
For me, I have spent a lot of time putting the qualitative research aside, saying “I’ll get to it later” and generally not engaging. The process continues to seem overwhelming even with as much progress as I’ve made towards my goal of completing this qualitative work and the paper I’m writing that describes it. I guess my overwhelming anxiety about all of this comes down to asking “who’s story is it that I’m telling?” Because if it’s my participants’ stories, then I should include them as coauthors. But if I’m doing this qualitative research to try to search for deeper meaning – a delineation between instructor experiences using ungrading in chemistry, considering their individual and institutional intersectionalities, including barriers and catalysts – then maybe their collective stories can create something larger that would be confounded by adding them as researchers and/or authors. I just still feel uneasy assigning arbitrary codes to their data and trying to make meaning without their constant input and perspectives along the way.
References
Bozkurt, A., Jung, I., Xiao, J., Vladimirschi, V., Schuwer, R., Egorov, G., Lambert, S. R., Al-Freih, M., Pete, J., Olcott, D., Rodes, V., Aranciaga, I., Alvarez, A. V., Roberts, J., Pazurek, A., Raffaghelli, J. E., de Coëtlogon, P., Shahadu, S., Brown, M., … Mano, M. (2020). A global outlook to the interruption of education due to COVID-19 Pandemic: Navigating in a time of uncertainty and crisis. Asian Journal of Distance Education, 15(1), 1-126. https://www.asianjde.com/ojs/index.php/AsianJDE/article/view/462
Bozkurt, A., Xiao, J., Lambert, S., Pazurek, A., Crompton, H., Koseoglu, S., Farrow, R., Bond, M., Nerantzi, C., Honeychurch, S., Bali, M., Dron, J., Mir, K., Stewart, B., Costello, E., Mason, J., Stracke, C. M., Romero-Hall, E., Koutropoulos, A., … Jandrić, P. (2023). Speculative futures on ChatGPT and generative artificial intelligence (AI): A collective reflection from the educational landscape. Asian Journal of Distance Education, 18(1), 53-130. https://doi.org/10.5281/ZENODO.7636568
Creswell, J. W. (2013). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed). SAGE Publications, Inc.
Creswell, J. W., & Poth, C. N. (2024). Qualitative inquiry & research design: Choosing among five approaches (5th ed). SAGE Publications, Inc.
Gay, G. (2010). Culturally reponsive teaching: Theory, research, and practice (2nd ed.). Teachers College Press.
Hannafin, M. J., Hill, J. R., Land, S. M., & Lee, E. (2014). Student-centered, open learning environments: Research, theory, and practice. In J. M. Spector, M. D. Merrill, J. Elen, & M. J. Bishop (Eds.), Handbook of research on educational communications and technology (pp. 641–651). Springer New York. https://doi.org/10.1007/978-1-4614-3185-5_51
Kiyama, J. M., & Aguilar, C. R. (Eds.). (2018). Funds of knowledge in higher education: Honoring students’ cultural experiences and resources as strengths. Routledge.
Jhangiani, R. S., Biswas-Diener, R., & Noba Project (Eds.). (2017). Open: The Philosophy and Practices that are Revolutionizing Education and Science. Ubiquity Press. https://doi.org/10.5334/bbc
Ladson-Billings, G. (1994). The dreamkeepers: Successful teachers of African American children. Jossey-Bass.
Noel, L. A. (2016, June 25). Promoting an emancipatory research paradigm in Design Education and Practice. Design Research Society Conference 2016. https://doi.org/10.21606/drs.2016.355
Saldaña, J. (2016). The coding manual for qualitative researchers (3rd ed.). SAGE Publications Ltd.
Tlili, A., Huang, R., Shehata, B., Liu, D., Zhao, J., Metwally, A. H. S., Wang, H., Denden, M., Bozkurt, A., Lee, L.-H., Beyoglu, D., Altinay, F., Sharma, R. C., Altinay, Z., Li, Z., Liu, J., Ahmad, F., Hu, Y., Salha, S., … Burgos, D. (2022). Is Metaverse in education a blessing or a curse: A combined content and bibliometric analysis. Smart Learning Environments, 9(24). https://doi.org/10.1186/s40561-022-00205-x
Tuhiwai Smith, L. (2019). Decolonizing research: Indigenous storywork as methodology. Bloomsbury Publishing. https://www.bloomsbury.com/us/decolonizing-research-9781350348172/
Tuhiwai Smith, L. (2023). Decolonizing methodologies: Research and indigenous peoples. Bloomsbury Publishing. https://www.bloomsbury.com/us/decolonizing-methodologies-9781350346086/
