Enhancing Design Research Quality with an SSQS Checklist
In the realm of Human-Computer Interaction (HCI) research, planning, conducting, and reporting semi-structured qualitative studies (SSQS) is a crucial task. While there is no explicit checklist from Ann Blandford detailing her approach to SSQS in HCI research, the best practices outlined below reflect the core elements that would likely be included in such a checklist.
Study Planning
- Clearly define research objectives and questions.
- Determine the target user group and sample size based on purposive or theoretical sampling.
- Develop an interview guide balancing open-ended and focused questions to allow exploration and comparability.
- Obtain ethical approval and informed consent procedures.
Conducting Interviews
- Use semi-structured interviews to blend consistency and flexibility, allowing participants to express their lived experiences relevant to HCI systems.
- Create a comfortable environment respecting participants' preferences (e.g., time, place).
- Audio-record and/or take detailed notes to preserve data integrity.
Analysis
- Transcribe interviews verbatim.
- Use thematic or content analysis methods rooted in established qualitative traditions.
- Employ coding strategies to identify patterns, themes, and categories.
- Check for reliability or validation via techniques like triangulation, member checking, or peer debriefing.
Reporting
- Present rich, contextualized descriptions supporting themes with participant quotes.
- Reflect on researchers’ positionality and potential biases.
- Discuss implications for HCI design and theory.
- Transparently describe methodology, including recruitment, data collection, and analysis procedures.
These steps align with Ann Blandford's approach to rigorous HCI qualitative research, as evidenced by her contributions to the field. For a precise, authoritative checklist, consulting Blandford’s publications directly or checking specialized HCI methodology literature is recommended.
Additional Considerations
- During a SSQS study, its purpose may change, and if it does, the reasons and implications should be documented.
- Advocacy may be necessary in the study setting, and identifying and working effectively with advocates is important.
- The location and intervention of a SSQS study should be carefully chosen to ensure a natural environment and appropriate forms of intervention.
- The research team's attributes, roles, and training are crucial for the success of a SSQS study.
- Techniques for data gathering, such as observations, interviews, and instructions, should be structured and protocols established.
SSQS research methodologies are unique to each project, and it can be beneficial to have a checklist when conducting SSQS research to maximize the value delivered to projects. Examples of SSQS research include ethnography, interviews, observations, etc.
Data generated from SSQS studies often needs to be systematized and coded for effective analysis. Data analysis methods, such as coding and validation, should be determined beforehand and may involve the research team or participants. Ethical considerations, such as participant benefits, data protection, and informed consent, are essential in conducting a SSQS study.
In both Positivist and Constructivist/Interpretivist approaches, there is no hypothesis to test; the researcher is looking to see what is happening. A theory is often used to guide data gathering, analysis, and reporting in a SSQS study.
[1], [3], [5] provide supporting evidence for many of these steps, emphasizing iterative, participant-centered interviewing and thorough qualitative analysis with contextual reporting.
If you're interested in learning more about SSQS in HCI research, Ann Blandford, Professor of Human Computer Interaction at University College London, proposed a framework for SSQS studies in her chapter "Semi-Structured Qualitative Studies" for the Interaction Design Foundation.
In the realm of UI design and interaction design within Human-Computer Interaction (HCI) research, incorporating aspects of science, health-and-wellness, and fitness-and-exercise can enhance understanding of user experiences with HCI systems. For instance, using SSQS methods to study people's experiences with a health-and-wellness app could shed light on potential UX improvements, thereby merging design and scientific knowledge.
To utilize SSQS effectively for these purposes, it is essential to maintain rigor in the study planning, conducting, analysis, and reporting phases, following best practices such as those outlined previously for HCI research. Moreover, as research objectives and questions often change during the course of a study, documenting the reasons and implications of such changes is crucial for maintaining high-quality results.
