“Learning from small numbers” of underrepresented students’ stories: Discussing a method to learn about institutional structure through narrative

The underrepresentation of women and men of color and white women in undergraduate engineering programs continues to be cause for concern by national engineering bodies, university administrations, and disciplinary organizations. Extensive research and intervention programming has gone into understanding this underrepresentation, and why it persists despite national and institutional focus and funding. However, this paper argue that most previous studies and interventions have been hampered by three challenges: 1) they tend to depend on statistical methods of generalization to understand the experiences of underrepresented people, despite the fact that the number of such people are usually too low to make analysis of them statistically significant; 2) they often result in interventions not in the structure of institutions but in the behavior of students themselves, and in their adaptation to their institutions; and 3) they usually examine women and people of color at predominantly white educational institutions and thus fail to focus on institutions which have showed relatively better success. This study was designed to respond to each of these challenges by importing research tools designed by sociologists to examine small numbers of people to investigate institutional structure: we use personal narratives about engineering education contributed by white women and students of color in undergraduate programs to understand how the structure of their educational institutions assists or hinders their success. My team and I have confronted methodological challenges when trying to analyze these narratives using commonly used qualitative coding methods. Through describing these challenges in detail, along with our theoretical and methodological frameworks and data collection and cleaning procedures, I hope to discuss with other qualitative researchers ways to use better methods that allow us collectively to “learn from small numbers.”