How to present qualitative findings

Qualitative findings are easiest to read when they’re anchored by a clear thematic structure—often a table of themes—then supported with quotes and, when appropriate, diagrams that match the study’s purpose. A practical starting point is a “table of themes” that lists each theme alongside how many times it appeared and in how many sources (such as interviews). Those counts help readers judge how strong or central a theme is: a theme mentioned by one participant carries less weight than one raised by, for example, 19 out of 20 participants. While some researchers object to quantifying qualitative data, the numbers are framed here as a transparency tool rather than a conversion of meaning into statistics.

The table can be expanded or broken down to keep chapters readable. One recommended approach is to present the full thematic framework early, then later extract smaller sub-tables for specific sections—such as separating “benefits of online education” from “challenges of online education.” Two cautions come with table design. First, including example extracts directly inside the table often makes it too long and forces heavy selectivity; it can also risk leaving readers with a distorted sense of what a theme actually means if the extracts appear without enough context. Instead, the preference is to omit extracts from the table and then explain each theme in the chapter using quotes and contextualized excerpts.

Beyond tables, other visuals can help—word clouds, charts, models, and diagrams—but they should serve the research question rather than decorate the page. For studies that investigate processes or relationships (for instance, how one theme influences another), a diagram or model of dynamic relationships can be appropriate. By contrast, if the study focuses on participants’ opinions about challenges and benefits and avoids speculation about relationships, a model may be unnecessary; a static thematic table may be the better fit.

Once the findings are visually organized, the next decision is how to discuss them and in what order. Using the example of online education, with two participant groups (teachers and students) and two main themes (benefits and challenges), multiple organizing logics are presented. One option is to structure chapters by themes first—benefits, then challenges—and within each theme, present student data and teacher data, optionally followed by a combined comparison section. Another option flips the structure: chapters by participant group first (student findings, then teacher findings), with benefits and challenges inside each group.

Complexity increases when multiple data collection methods enter the picture, such as interviews plus a questionnaire. The findings can then be organized by method (interviews vs. questionnaire), by group (students vs. teachers), by theme (benefits vs. challenges), or by hybrid combinations—such as a student chapter that discusses interview findings supplemented by questionnaire results. The “right” structure isn’t treated as universal; it depends on what the study needs to foreground. If highlighting differences between groups is central, group-based chapters may make the contrast clearer. If thematic consistency is the priority, theme-based chapters can keep the narrative focused.

Practical planning matters: the proposed structure should match the amount of data available for each method. If questionnaire data is thin compared with interview data, separate questionnaire chapters can become lopsided; using questionnaire results as supplementation can preserve the core narrative while still leveraging the broader response patterns (e.g., “90% selected convenience” as a benefit) without letting weaker sections dominate. The overarching guidance is to plan the chapter by reviewing the dataset first and choosing the structure that best communicates the study’s main emphasis—differences, consistency, or thematic centrality.