Typical case sampling helps you describe what is common in a group or setting, especially when time for data collection is limited. Rather than focusing on extremes, you select cases that reflect routine practice. It can be especially useful for applied projects that aim to inform practice or policy.
Learn more: https://qdacity.com/typical-case-sampling
A thesis or literature review can get messy fast when you’re handling many sources. Qualitative data analysis helps you track themes, patterns, and gaps, link claims to excerpts, and document how categories evolve. For students, QDAcity’s coding workflow can make large volumes of material easier to manage and revisit during writing.
https://qdacity.com/qda-software-for-students/
Rigor isn’t only about collecting good data. It’s also about how you justify the quality and coherence of your claims. Two common paradigms can guide that evaluation: the rationalistic paradigm, focused on validity and reliability, and the naturalistic paradigm, focused on trustworthiness. Making your framework explicit helps you report rigor more clearly.
https://qdacity.com/research-rigor
Working in a team?
Consistent coding is part of making your analysis defensible. Intercoder agreement helps you see how similarly researchers apply codes, reveal ambiguity in code definitions, and improve reliability in collaborative projects. Used well, it supports a clearer codebook, aligned interpretations, and transparent analytic decisions.
https://qdacity.com/intercoder-agreement
Member checking helps you test whether your interpretations make sense to the people who shared their experiences. Used thoughtfully, it can strengthen ethics and rigor by inviting feedback on meaning, surfacing misunderstandings, and documenting how interpretations were reviewed. It can be used after interviews, during analysis, or when drafting findings.
https://qdacity.com/member-checking/
Mixed methods helps you study a research problem from more than one angle, combining qualitative depth with quantitative patterns. It supports broader coverage, stronger inferences through triangulation, and flexible designs that fit your question. Used well, it becomes a coherent strategy for building answers from multiple forms of evidence.
https://qdacity.com/mixed-methods-research/
Transferability in qualitative research helps readers judge whether findings fit other comparable settings. You can strengthen it through rich description of context, reflexivity, and data triangulation. When your setting and analytic choices are clearly documented, others can assess fit without overclaiming.
Explore more: https://qdacity.com/trustworthiness/transferability/
New addition to my list of Open Source tools for Qualitative Data Analysis: BORIS ("Behavioral Observation Research Interactive Software"), useful for coding of audio-visual recordings.
The list: https://codeberg.org/stragu/open-source-qda
BORIS website: https://www.boris.unito.it/
QDAcity now supports spreadsheets in your workflow. You can upload Excel files in XLSX format and create or edit spreadsheets directly in QDAcity. This helps you keep research-related data in one place and code it with a consistent codebook. The feature is available now.
We’d love to hear your feedback: https://qdacity.com/
QDAcity
Polly Kraisus
