This project titled “Beyond the Deficit Model: Gender Schemas, Computing, Preferences, and IT Careeer Choices” set out to understand the mechanisms that influence how and whether middle school students move toward computing classes, majors and careers. Our goal was to update our conceptual models and scales and instruments on this fast moving field: today’s children grow up with computers all around them, and many of them own powerful pocket computers—smart phones—by the time they enter high school. However, despite decades of effort, computing careers have few women or African-Americans or Hispanics, and few people from poorer backgrounds. We wanted to understand the dynamics and the context that motivates and supports girls, children of color and poorer children towards a path that can result in a career in computing fields, and what discourages or blocks such paths. Most importantly, we wanted to understand both the obstacles and the aspirations of the children themselves.
To accomplish all this, we started with in-depth interviews with more than 100 middle school students and using those interviews to capture their language and mental models. We proceeded to develop scales that measure important dimensions of the mechanisms that influence our research question. After piloting and testing these scales, we developed an 18 page high-quality survey instrument that included almost every dimension that was found to be relevant in the literature. The survey also included our new scales which reflected an updated understanding of this age group and their relationship to computing. We proceeded to gather survey data using this instrument. Our resulting sample of about 5200 surveys far exceeded our initial goal of 2000 and included middle school children from a variety of backgrounds. Our sample has a range of schools ranging from very well-off schools ones to poorer schools across a range of racial and ethnic compositions. The advantage of such a large sample is that it will allow us to do truly intersectional analyses: we can try see how race, gender and class interact as we have sufficient subsamples of many groups who are traditionally hard to analyze because they don’t show up in large numbers in smaller surveys.
Our findings will be published in a wide range of academic journals and will be communicated to the public, practitioners and stakeholders. Through our analyses, we hope to be able to help schools design better curriculum that can be more attractive to demographic groups who are underrepresented in computing classes. Our data can be used to design more inclusive summer camps and after school programs in computing, and understand which paths are more likely to encourage children to pick up computing classes, major and careers. Our publications should also help guide technology companies better understand how children conceptualize careers in computing, and whether they need to change the way they advertise and publicize what such work entails.
Since we began our work, the White House announced a “computing for all” initiative for high school students. We hope that our data can be used to guide how to make these computing classes truly work for “all” students rather than ones who were already on a path to such careers.
Our survey instruments and scales should help other researchers looking at these questions. Many of our existing theories and instruments predate the explosion of computers in everyday life. Thanks to this NSF funding, we were able to catch up in this very fast-moving field.
Our findings should help teachers understand how children think of their classes in computing, and how to try to frame them to appeal to broader groups.
Our findings also include data about the importance of school infrastructure in how children think of computing careers. Many times, the first computer technician they see is the one who works in their schools, and they may think of computing careers within the framework of their school experience.
Our findings should be helpful to parents as we asked students about their views on skill levels of their parents, as well as the role of parental careers. Parents can also use our findings to understand the role computing classes and other activities play in encouraging children to take interest in computing careers.
Our survey has in-depth data in many other dimensions, ranging from the role of games to students’ sense of their skills.
We hope that our findings will further our theoretical understanding of the role of gender, race and class in computing careers. We also hope our findings will help practitioners design better extra-curricular programs; help policy-makers appreciate the role of infrastructure; help parents have a better sense of which computing activities contribute to educational outcomes and how; help teachers understand their classroom choices better; and help people in the technology companies have more options in recruiting and fostering a more diverse workforce.
Last Modified: 01/27/2017
Modified by: Zeynep Tufekci