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Human-subject studies are now a common vehicle for generating empirical evidence in engineering design research, spanning protocol studies, controlled experiments, surveys, interviews, and mixed–methods approaches. Yet a recurring difficulty in current practice is that many studies remain experience–informed point observations, such as single artifacts, simplified tasks, convenience samples, or narrow decision regimes, while making broad claims about engineering design knowledge or practice. This perspective argues that the central issue is not the inclusion of human participants, but rather under–specification of design context and misalignment of validation logic, i.e. importing methods and reporting conventions from adjacent disciplines can improve transparency, but does not, by itself, establish engineering–level applicability or transferability. We synthesise state–of–the–art norms from human factors and ergonomics, human-computer interaction and open science practices, social science qualitative research, and clinical and observational research reporting, and evaluate their strengths and limitations in the context of engineering design. A central organising reflection is an artifact-decision map that frames two orthogonal validity drivers regarding artifact realism and decision realism, and links a study’s position to defensible claim scope. We envision a pragmatic pipeline, including a lightweight Metric–Measure–Method (3M) discipline, and actionable guidance for researchers to strengthen context–aware validation while preserving methodological diversity.
Roger J. Jiao (Tue,) studied this question.