Quality in Interpretive Engineering Education Research: Reflections on an Example Study

TLDR: In this paper, the authors present reflections on challenges to research quality in an example interpretive engineering education study, and offer a quality framework that emerged from this study as a coherent, discipline-specific view on interpretive research quality.

Abstract: Background The emerging discipline of engineering education research is increasingly embracing a diverse range of interpretive research methods, whose adoption is characterized by a lack of coherent ways to conceptualize, communicate, and judge the quality of interpretive inquiries. Yet fields that have traditionally employed these methods do not offer a consensus about research quality. Purpose This article presents reflections on challenges to research quality in an example interpretive engineering education study, and offers a quality framework that emerged from this study as a coherent, discipline-specific view on interpretive research quality. Design/Method Analysis of the prior study of engineering students' competency formation by the author(s) is combined with a synthesis of the literature from the broad intellectual traditions of the interpretive paradigm to inform the development of a theoretical framework of research quality. Results Drawing on the engineering metaphor of quality management, we propose a systematic, process-oriented framework of research quality along two dimensions: a process model locates quality strategies throughout the research process, and a typology systemizes fundamental aspects of validation (theoretical, procedural, communicative, and pragmatic) and the concept of process reliability to explicate quality strategies in their fundamental contribution to substantiating knowledge claims. Conclusion The quality framework provides a way to develop and demonstrate overall research quality in the interpretive inquiry by shifting attention away from assessing the research quality of a final product. Rather, the framework provides guidance to systematically document and explicitly demonstrate quality considerations throughout the entire research process.