The Power and Politics of STEM Research Design: Saving the "Small N"

Slaton, Amy E.; Pawley, Alice L.

doi:10.18260/p.24901

Cited by 19 publications

(21 citation statements)

References 26 publications

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“…A significant problem in quantitative measures of diversity is the "binning" of students' identities into categories defined by others rather than by their own personal identification 14 . Typical demographic variables include gender, race, ethnicity, age, residence (including zip code which can be used as a proxy for socio-economic information), parental education level, parental income level, and high school/high school district (which indicates the academic resources available to the student).…”

Section: Part 1: Why To Ask and How To Framementioning

confidence: 99%

More Comprehensive and Inclusive Approaches to Demographic Data Collection

Fernandez

Godwin

Doyle

et al.

2016 ASEE Annual Conference &Amp; Exposition Proceedings

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Lisa Benson is an Associate Professor of Engineering and Science Education at Clemson University, with a joint appointment in Bioengineering. Her research focuses on the interactions between student motivation and their learning experiences. Her projects involve the study of student perceptions, beliefs and attitudes towards becoming engineers and scientists, and their problem solving processes. Other projects in the Benson group include effects of student-centered active learning, self-regulated learning, and incorporating engineering into secondary science and mathematics classrooms. Her education includes a B.S.

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Section: Part 1: Why To Ask and How To Framementioning

confidence: 99%

More Comprehensive and Inclusive Approaches to Demographic Data Collection

Fernandez

Godwin

Doyle

et al.

2016 ASEE Annual Conference &Amp; Exposition Proceedings

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“…While we often seek statistical significance, we generally undermine the importance of the experiences and stories of those for whom the numbers are small. 76 We discount the intersectionality of individual identities and miss those important experiences. As a field, how do we also learn to use small numbers of "data points" to make decisions that influence classrooms?…”

Section: Broaden Our Definition Of Sufficient Evidencementioning

confidence: 99%

Interactive Panel: Improving the Experiences of Marginalized Students on Engineering Design Teams

Meadows

Sekaquaptewa

Paretti

et al.

2015 ASEE Annual Conference and Exposition Proceedings

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Marie C. Paretti is an Associate Professor of Engineering Education at Virginia Tech, where she codirects the Virginia Tech Engineering Communications Center (VTECC). Her research focuses on communication in engineering design, interdisciplinary communication and collaboration, design education, and gender in engineering. She was awarded a CAREER grant from the National Science Foundation to study expert teaching in capstone design courses, and is co-PI on numerous NSF grants exploring communication, design, and identity in engineering. Drawing on theories of situated learning and identity development, her work includes studies on the teaching and learning of communication, effective teaching practices in design education, the effects of differing design pedagogies on retention and motivation, the dynamics of cross-disciplinary collaboration in both academic and industry design environments, and gender and identity in engineering.

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“…Her theoretical framework is based on Dorothy Smith's work on ruling relations [25][26][27] , which are the 'operating procedures' by which we collectively coordinate social relations in some setting. Alice and her team have written elsewhere about different aspects of this project 2,3,28,29 .…”

Section: Context: Example Projectsmentioning

confidence: 99%

Exploring Ethical Validation as a Key Consideration in Interpretive Research Quality

Walther¹,

Pawley

Sochacka³

2015 ASEE Annual Conference and Exposition Proceedings

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The engineering education community is adopting an increasingly diverse range of qualitative methods. This rapid expansion in required methodological expertise has sparked a vibrant discourse around ways to foster and articulate research quality in qualitative and mixed-methods studies. This paper describes three engineering education scholars' engagement with a processoriented framework for interpretive research quality. Set in the context of a collaborative inquirybased approach to reflecting on and improving research practice, this paper presents five instances when we turned to the framework to address quality challenges that emerged in our own research projects. Analysis of these experiences demonstrates the exploratory and explanatory power of the existing framework. At the same time, however, our collaborative process revealed the need to consider another dimension of research quality, specifically concerned with the human experience of the researcher and the researched throughout the inquiry. In this context, we propose Ethical Validation as a validation construct that, we argue, lies at the heart of conducting and evaluating interpretive research.

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The Power and Politics of STEM Research Design: Saving the "Small N"

Cited by 19 publications

References 26 publications

More Comprehensive and Inclusive Approaches to Demographic Data Collection

More Comprehensive and Inclusive Approaches to Demographic Data Collection

Interactive Panel: Improving the Experiences of Marginalized Students on Engineering Design Teams

Exploring Ethical Validation as a Key Consideration in Interpretive Research Quality

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