Assumptions in Qualitative Research
Based on Qualitative Researcher Dr Kriukow's video on YouTube. If you like this content, support the original creators by watching, liking and subscribing to their content.
Assumptions can be essential for developing research ideas, guiding curiosity, and structuring data collection in qualitative studies.
Briefing
Assumptions aren’t automatically a contaminant in qualitative research; they’re often necessary scaffolding for designing a study, shaping curiosity, and guiding what researchers choose to look for. The key is treating assumptions as visible, workable inputs rather than hidden forces—because they can either help inquiry move forward or quietly take over analysis.
In qualitative work, assumptions frequently get framed as bias: the fear that researchers will impose expectations on participants’ accounts and distort findings. But assumptions also serve a constructive role. They help researchers develop a research idea and proposal, decide how to structure data collection, and set the initial direction for exploration. Without some expectations—however tentative—researchers may struggle to formulate questions, build interview guides, or know what to pay attention to during analysis.
Problems arise when researchers over-rely on assumptions, especially in exploratory designs such as grounded theory, where findings are expected to emerge from the data rather than from a preselected storyline. A common failure mode is building the data collection instrument around a single anticipated theme. For instance, if an interview guide is structured to confirm one expected outcome, participants may respond in ways that don’t match the researcher’s frame—either because the topic isn’t salient to them or because they don’t interpret the questions as intended.
A personal example illustrates how this can play out. While studying “English language identity” among Polish migrants in Scotland, the researcher entered interviews expecting participants to talk directly about their identity in English versus Polish. During a pilot study, participants appeared confused by the identity-focused questions. The researcher felt frustrated, unsure what was wrong. Yet participants were still eager to talk and offered rich, detailed experiences—just not in the identity terms the researcher had assumed.
Reflection shifted the interpretation. The researcher recognized that the “identity” theme might be the researcher’s assumption rather than participants’ organizing concept. By giving participants more freedom and dropping the insistence on identity as the explicit label, the interviews began to yield the intended substance. Later analysis revealed that identity was present in participants’ stories, even though they didn’t call it that way.
The takeaway is not to eliminate assumptions or pretend they don’t exist. Instead, researchers should be explicit about their assumptions, document them through tools like a research diary or journal, and remain alert to when assumptions stop guiding inquiry and start dominating it. That monitoring helps generate new analytical ideas while also flagging the moment when a single expectation begins to narrow what the data can reveal.
Cornell Notes
Assumptions in qualitative research are often necessary for shaping a study’s questions, curiosity, and design, but they become risky when researchers over-rely on them—especially in exploratory approaches like grounded theory. The central lesson is to treat assumptions as explicit, documented inputs rather than hidden biases. A researcher’s study of “English language identity” among Polish migrants in Scotland shows how an identity-focused interview guide can confuse participants, even when they are willing to share rich experiences. By reflecting on the mismatch and allowing participants to speak more freely, the researcher later found that identity themes were still present, just not labeled in the expected way. Ongoing reflection helps researchers notice when assumptions guide analysis versus when they start to dominate it.
Why aren’t assumptions automatically harmful in qualitative research?
What makes assumptions especially problematic in exploratory designs like grounded theory?
How did the “English language identity” example demonstrate over-reliance on assumptions?
What changed after reflection, and what was the outcome?
What practical steps help keep assumptions from dominating analysis?
Review Questions
- What are two ways assumptions can support qualitative research, and what condition turns them into a liability?
- In the grounded theory context, why can designing an interview guide around a single expected theme reduce the chance of discovery?
- How did the researcher’s pilot study findings lead to a change in interview strategy, and what did later analysis reveal?
Key Points
- 1
Assumptions can be essential for developing research ideas, guiding curiosity, and structuring data collection in qualitative studies.
- 2
Assumptions become harmful mainly when researchers over-rely on them and let them narrow what the data can reveal.
- 3
Exploratory methods such as grounded theory are particularly vulnerable to assumption-driven interview design that blocks emergence from the data.
- 4
A pilot study can reveal assumption problems when participants appear confused by researcher-framed topics despite being willing to share rich experiences.
- 5
Reflection through a research diary or journal helps researchers document assumptions and monitor when they shift from guiding analysis to dominating it.
- 6
Eliminating assumptions or pretending they don’t exist is neither possible nor desirable; the goal is explicitness and ongoing critical awareness.