Reimagining Learning Tools for Qualitative Research

"This is really hard!" cried an undergraduate student, two weeks into her first qualitative research experience. The student was in the midst of reviewing data analyses during a course centered on active inquiry into music and culture. The mode of inquiry, qualitative research, is a messy process that demands disciplined, expert judgment. As a teacher, this course was my chance to leap away from the whiteboard and approach the excitement of research with students using a new pedagogical framework and tool.

The fallback model of hybrid and online learning has used learning management systems as administrative tools, where the faculty member is the "learning manager."¹ As online learning continues to develop, faculty members seek technologies that facilitate social learning spaces.² This article suggests further developments in learning systems that structure collaborative interactions with discipline-specific complexity.

Approaching Complexity

Using insights from aviation, medicine, and engineering, Gawande wrote about supporting professionals through the use of process-prompting technologies, or more simply, checklists.³ In cases ranging from plane takeoffs to surgical infections, checklists are used to make routine tasks more accurate. Lin et al. stated that "guided prompts, both in random and fixed presentation schedules, are necessary parts of making any process intentional and overt."⁴

While checklists steer experts through routine processes, they also guide collaboration around fluid and complex problems.⁵ Gawande related the complexity of skyscraper construction and the way that checklists built "pause points" to create space for collaborative thinking. In the context of these kinds of complex problems, expertise becomes distributed and socially constructed through processes of collaboration and comparison.⁶ This model inspired me to develop qualQuery, a process-prompting/process-modeling tool that supported the fluid and complex nature of qualitative research in an undergraduate environment.

Development of qualQuery

qualQuery is designed to allow teams of beginning and experienced researchers to navigate qualitative research processes. Operating from a central "dashboard" interface, the program guides teams through research in a series of numbered steps (see figure 1). Students compare analyses side-by-side as they identify a research focus and code, sort, query, summarize, and analyze data, as shown in the qualQuery demo. These higher-order thinking skills are the capacities that demand critical support for effective and accurate research.

Figure 1. Project dashboard from qualQuery

Research Context

The use of the software was examined in the context of a world musics course I taught, in which a class of two students engaged in a study of music experience in an evangelical Hispanic church. These students, who had never had formal qualitative research training, were tasked with completing a research study in the three and half weeks of a condensed May term. In that time, the students became participant-observers in worship services, conducted six interviews, transcribed interviews, coded data, sorted data, wrote summaries, and drafted a final research paper.

Students simultaneously participated in a study of how they engaged in qualitative research. The research pulled from traditions of action research, case study, and grounded theory. Collected data included pre- and postinterviews, research journals, a self-reported survey, and data entered in the qualQuery system.⁷ Exit interviews were conducted with a faculty member who had no previous interaction with the students. Data were analyzed using grounded theory methods of coding, memo writing, sorting, and summarizing.⁸ Data trustworthiness was ensured by conducting follow-up interviews with participants.

Complexity Navigation

Across interviews and journals, the two participants spoke and wrote extensively about how the project challenged them to use critical thinking skills. One student said, "I think it's the whole synthesis aspect of this research project that you can't just take information and put it together, you have to . . . draw conclusions and synthesize." Step-by-step process prompting and ongoing collaboration were cited as key supports in this complex process. Referring to the structure of the qualQuery tool, a student reflected, "For this project, it was very step-by-step, it was very clear what was expected of us and what we were expected to do." Though the students recognized the intellectual challenge of the project, they felt the tool supported and guided their work.

Pedagogy of Constant Comparison and Collaboration

The collaborative process of constant comparison has been identified as a fundamental process of qualitative research.⁹ In the case of this research study, this qualitative process also emerged as a valuable pedagogical technique. One participant mentioned, "I think that doing it collaboratively gave [the project] a lot more depth and gave me a better understanding of how to interact with research and other researchers." Another student described the collaboration as a place for "constructive feedback and [as] a think-tank to assist my development."

As the students began to listen to interviews and make analyses, comparisons emerged that informed the learning process. Students first noticed how much they were learning through comparisons of interview styles. One participant stated that while her partner's interviews "tended to be more conversational . . . I was happier to sit back and allow the other person to talk, using more nonverbal encouragers such as nods or smiles." Placing elements of student work side-by-side built rich in-classroom discussions and opened new perspectives: "Oh, she looked at the sentence in this way, I hadn't thought about [it] before, so the [technology] was really useful in this process." The pedagogy of constant comparison continued as the two students merged individual writing styles into a cohesive whole.

Themes

Two sets of themes were generated; one set focused on overall experiences, and the other on the use of technology (see table 1). Process-prompting technology effectively moved step-by-step instruction out of the classroom and into embedded, just-in-time information. This shift allowed me to be the teacher I had always wanted to be: a facilitative guide on the side.

Table 1. Major Themes

Conclusion

This is the paradigm shift that Dewey anticipated as he wrote about the role of education in an era of scientific discovery and radically increasing complexity.¹⁰ Instead of factual accumulation, Dewey advocated a complexity-breaking skill, the scientific method. This article returns to that pragmatist epistemology but in a postpositivist manner that uses multiple approaches of inquiry. An inquiry-driven class with embedded supports brought great satisfaction and a strong sense of ownership to participants. One student reflected:

"From the beginning I knew it was going to be a challenge for me. From interviewing, to transcribing, to coding, to writing the paper, I was constantly trying and then fixing things . . . . I had to evaluate whether my own opinions were going to influence my interviews, I had to evaluate whether my transcriptions were really representing the respondents, and I had to evaluate whether my coding really represented the most important ideas of the research study."

Students spoke of their high sense of satisfaction and of this project being one they owned: "It was my project, my paper, which I wanted to be the best that it could be."

There is a place for learning management systems that serve as administrative tools and collections of content. There is also a place for learning management system tools that break down problems into step-wise parts, embedding learning in process-prompted encounters with complexity. In this case, approaching the complexity of inquiry opened spaces for student ownership, transformational learning, and critical thinking. Embarking on shared journeys through sophistication with the support of process-oriented, collaborative technology adds another set of spaces for transformative learning.

1. Louis Pugliese, "A Post-LMS World," EDUCAUSE Review 47, no. 1 (January/February 2012).
2. Cyprien P. Lomas and Chris Johnson, "Design of the Learning Space: Learning and Design Principles," EDUCAUSE Review 40, no. 4 (July/August 2005): 16–28.
3. Atul Gawande, The Checklist Manifesto: How to Get Things Right (New York: Metropolitan Books, 2009).
4. Xiaodong Lin et al., "Designing Technology to Support Reflection," Educational Technology Research and Development 47, no. 3 (1999): 46.
5. Gawande, The Checklist Manifesto.
6. Gawande, The Checklist Manifesto, and Lin et al., "Designing Technology to Support Reflection."
7. The interviews and survey were informed by the work of Sandra Laursen et al., Undergraduate Research in the Sciences: Engaging Students in Real Science (San Francisco: Jossey-Bass, 2010).
8. Kathy Charmaz, Conducting Grounded Theory: A Practical Guide through Qualitative Analysis (London: Sage Publications, 2006).
9. Barney G. Glaser and Anselm L. Strauss, Discovery of Grounded Theory: Strategies for Qualitative Research (Chicago: Aldine, 1967).
10. John Dewey, How We Think: A Restatement of the Relation of Reflective Thinking to the Educative Process (New York: D.C. Heath and Company, 1933).