How Do Educational Experiences Predict Computing Identity?

作者：Stephanie Lunn, Monique Ross, Zahra Hazari, Mark Allen Weiss, Michael Georgiopoulos, Kenneth J. Christensen · 发表于：ACM Transactions on Computing Education · 年份：2021 · DOI：10.1145/3470653 · 被引用次数：28 · 研究领域：Gender and Technology in Education、Career Development and Diversity、Information Systems Education and Curriculum Development

Despite increasing demands for skilled workers within the technological domain, there is still a deficit in the number of graduates in computing fields (computer science, information technology, and computer engineering). Understanding the factors that contribute to students’ motivation and persistence is critical to helping educators, administrators, and industry professionals better focus efforts to improve academic outcomes and job placement. This article examines how experiences contribute to a student’s computing identity, which we define by their interest, recognition, sense of belonging, and competence/performance beliefs. In particular, we consider groups underrepresented in these disciplines, women and minoritized racial/ethnic groups (Black/African American and Hispanic/Latinx). To delve into these relationships, a survey of more than 1,600 students in computing fields was conducted at three metropolitan public universities in Florida. Regression was used to elucidate which experiences predict computing identity and how social identification (i.e., as female, Black/African American, and/or Hispanic/Latinx) may interact with these experiences. Our results suggest that several types of experiences positively predict a student’s computing identity, such as mentoring others, having a job, or having friends in computing. Moreover, certain experiences have a different effect on computing identity for female and Hispanic/Latinx students. More specifically, receiving academ...