June 14, 2015
June 14, 2015
June 17, 2015
Educational Research and Methods
26.1564.1 - 26.1564.13
The Power and Politics of STEM Research Design: Saving the Small NLike all research, the analysis of minority experiences in STEM education, including research onpatterns of inclusion and on the nature of classroom teaching and learning, requiresmethodological decisions. Researchers customarily choose between such investigative optionsas quantitative and qualitative evidence, or aggregated and disaggregated data sets. Units ofanalysis, taxonomies, and nomenclatures are all matters of choice, as well. Rigorous scholarscustomarily attempt to match carefully research question to research design, and at the same timeto incorporate realistic data collection aims and resource use. What is less often considered inserious scholarship is the field of existing research options, as such; that is, the question of whatmay determine researchers’ preferences for quantitative or qualitative methods, for aggregated ordisaggregated data and the consequences of such choices. For example, only one inquiry (Riley2013) has problematized the veneration of evidence-based STEM research as narrowingconceptions of valuable teaching and learning in STEM. We see all methodological choices bySTEM researchers as powerful indicators of social understandings of equity and inclusion, in thiscase regarding matters of equity in engineering education. We ask here: What larger socialconditions may be prompting STEM researchers’ ideas of practical and intellectually appropriateresearch design?In this paper, we consider one such idea: The prevailing stigma of research conducted on smallpopulations in research on equity. Scholars’ distaste for the “small n” sometimes simplyconstrues intersectionality as oddity, and depicts “small n” research as focusing our attention onthe rarity, the “Lesbian, Hispanic who uses a wheelchair.” (McRuer, 2006). Other researchers,focusing on seemingly practical aspects of research, describe wanting to keep data on race andgender disaggregated in quantitative analyses of underrepresentation, but believe they possessparticipants in numbers too small to justify doing so. In other words, because of the smallnumbers of people of color in engineering, quantitative analyses find it methodologicallynecessary to aggregate all women together even when their experiences may differ by race, or toaggregate all African-American people together even when their experiences differ by gender.Parallel methodological moves include researchers’ aggregation of people of color even whentheir experiences differ by race or ethnicity, or the failure to demarcate experiences along thelines of other forms of identity such as sexuality, dis/ability, nationality, or age. We see suchschematic choices as erasing (if not intentionally) forms and sources of inequity in STEMeducation.Whatever its source or however explicit (or not) its ideological origins, disregard of the “small n”population as non-meaningful reproduces a marginalization of students. It also casts particularhuman experiences as aberrant by virtue of statistical rarity. But most profoundly, researchers’definition of small or large “n’s” reiterates the value or necessity for established categories (say,racial delineations, or binaries of ability and disability), while we instead believe that criticalreflection on categories is necessary for any address of power and privilege. Our counterexample to prevailing “small n” stigma is [removed for review], which uses narrative methodsfor analyzing the stories of participants’ lives to explore how race and gender (and othercategories such as class) as macrostructures interact to race and gender engineering educationinstitutions. Students’ stories are entrées into understanding better how the structure ofengineering education functions inequitably to maintain engineering as a white, male conclave.
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