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References: Research Design and Evidence Quality

  1. Research design - Wikipedia - Offers an accessible overview of Research design, including definitions, methods, examples, limitations, and related concepts. This foundation helps students reason carefully about designing valid, reliable, transparent, and reproducible customer studies.

  2. Validity (statistics) - Wikipedia - Offers an accessible overview of Validity (statistics), including definitions, methods, examples, limitations, and related concepts. Its examples help students evaluate evidence for designing valid, reliable, transparent, and reproducible customer studies.

  3. Reliability (statistics) - Wikipedia - Offers an accessible overview of Reliability (statistics), including definitions, methods, examples, limitations, and related concepts. It supplies useful context for decisions about designing valid, reliable, transparent, and reproducible customer studies.

  4. The Practice of Social Research (15th ed.) - Earl Babbie - Cengage - Covers research questions, conceptualization, measurement, sampling, validity, reliability, ethics, and interpretation across social research designs. Its sustained treatment supports work on designing valid, reliable, transparent, and reproducible customer studies.

  5. Research Design (6th ed.) - John W. Creswell and J. David Creswell - SAGE - Compares qualitative, quantitative, and mixed-method designs while linking research questions, assumptions, evidence, procedures, and defensible conclusions. Its cases illuminate tradeoffs involved in designing valid, reliable, transparent, and reproducible customer studies.

  6. User Research Methods - Usability.gov - Organizes practical methods for planning studies, learning about users, evaluating designs, analyzing evidence, and communicating research findings. Its methods give teams a starting point for designing valid, reliable, transparent, and reproducible customer studies.

  7. Writing Survey Questions - Pew Research Center - Explains questionnaire development, pretesting, wording, response formats, order effects, and common sources of measurement error. Its comparisons clarify choices involved in designing valid, reliable, transparent, and reproducible customer studies.

  8. When to Use Which User-Experience Research Methods - Nielsen Norman Group - Organizes research methods by behavioral versus attitudinal evidence, qualitative versus quantitative data, and the context in which a product is studied. Its framework strengthens responsible work on designing valid, reliable, transparent, and reproducible customer studies.

  9. User Interviews: How, When, and Why to Conduct Them - Nielsen Norman Group - Covers interview planning, neutral facilitation, follow-up questions, limitations of self-report, and appropriate uses for attitudinal research. Its examples show how evidence informs designing valid, reliable, transparent, and reproducible customer studies.

  10. AI Risk Management Framework - NIST - Provides the Govern, Map, Measure, and Manage functions for addressing validity, reliability, transparency, privacy, fairness, accountability, and other AI risks. Its implementation advice helps teams practice designing valid, reliable, transparent, and reproducible customer studies.