Abstract

<strong>Background:</strong> Identity research in engineering education has been expanding to include multiple forms of measurement. While a variety of approaches have successfully contributed to our understanding of identity, mixed method approaches have been utilized minimally in identity research. Therefore, additional insight on the implications and affordances of mixed method approaches for identity research is needed. <strong>Purpose:</strong> Our work explored undergraduate engineering students’ researcher identity using a fully integrated mixed method approach by interweaving deductive (quantitative) and inductive (qualitative) strands of survey and interview data. We aimed to answer the research question: <em>How can quantitative and qualitative data approaches be used in combination to explore how students conceptualize their researcher identity?</em> <strong>Method:</strong> The data included responses from 20 undergraduate mechanical and biomedical engineering students representing six different institutions. Students completed surveys, and their survey responses served as a foundation for subsequent interviews. Both the survey and interview contained an identical item (a single anchored scale measure of researcher identity), which directly connected the two data sets. While the survey data was used during the interviews, analysis of the strands was initially separate but concurrent. <strong>Results:</strong> After initial analysis, mixing the data provided two key opportunities to attain a deep understanding of participants’ researcher identity. The anchored scale provided a platform to discuss researcher identity with participants and allowed us to look within and across participants’ experiences in unexpected ways. Our discoveries of how individual students’ conceptualizations of the identity being measured varied and how those conceptualizations changed over time were only possible through the analysis of both quantitative and qualitative data. <strong>Conclusions:</strong> Our fully integrated mixed method approach resulted in a more complete understanding of students’ researcher identities, allowing us to extend our theoretical understanding beyond what would have been possible with either method alone. Researchers exploring complex topics that can be fluid and affected by time and experience, such as identity, may benefit from integrating a similar approach into their research protocols.

Highlights

  • Identity has become a significant area of study in the engineering education community with researchers using quantitative, qualitative, and, to a more limited extent, mixed method approaches to measure identity (Patrick & Borrego, 2016; Rodriguez et al, 2018)

  • Godwin (2016) established a scale that measured identity using a model of performance/competence, interest, and recognition, while Borrego and her colleagues have developed a quantitative instrument using the model of Kajfez, et al: A Mixed Method Approach to Understanding Researcher Identity identifying with an organization (Borrego et al, 2018)

  • We present an approach for integrating a single anchored scale identity item with in-depth interviews using a study of student researcher identity as an exemplar case

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Summary

Introduction

Identity has become a significant area of study in the engineering education community with researchers using quantitative, qualitative, and, to a more limited extent, mixed method approaches to measure identity (Patrick & Borrego, 2016; Rodriguez et al, 2018). This is a deductive approach to identity wherein the researcher is limiting what is and is not part of the engineering identity as represented in the scale items. Purpose: Our work explored undergraduate engineering students’ researcher identity using a fully integrated mixed method approach by interweaving deductive (quantitative) and inductive (qualitative) strands of survey and interview data. Their survey responses served as a foundation for subsequent interviews Both the survey and interview contained an identical item (a single anchored scale measure of researcher identity), which directly connected the two data sets. Researchers exploring complex topics that can be fluid and affected by time and experience, such as identity, may benefit from integrating a similar approach into their research protocols

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