{"title":"Using Discrimination Response Ideation to Uncover Student Attitudes about Diversity and Inclusion in Computer Science","authors":"Lina Lee, Celine Latulipe, Tonya Frevert","doi":"https://dl.acm.org/doi/10.1145/3550487","DOIUrl":null,"url":null,"abstract":"<p>Helping students learn to identify and respond to situations involving discrimination is important, especially in fields like Computer Science where there is evidence of an unwelcoming climate that disproportionately drives underrepresented students out of the field. While students should not be considered responsible for fixing issues around discrimination in their institutions, they do have a role to play. In this paper, we present the results of a study in which 318 undergraduate computer science majors were presented with scenarios of discrimination and asked to identify the issues, rate the severity of the issues, and ideate 3–5 responses to address the described situations. They were also asked to identify which of their responses would likely be most effective in addressing discrimination and which of their responses they would be most likely to use if they were in the situation described in real life. Our results show that while students generally are able to identify various forms of discrimination (sexism, racism, religious discrimination, ethnic discrimination, etc.), any ambiguity in a scenario led to students describing the scenario as less severe and/or as an example of oversensitivity. We also show that students come up with many passive responses to scenarios of discrimination (such as ignoring the situation or wishing it had not happened in the first place). Students in our study were more likely to say they would deploy passive responses in real life, shying away from responses that involve direct confrontation. We observed some differences between student demographic subgroups. Women and BIPOC students in CS tend to think these issues are more severe than men and White and Asian students in CS. Women are more likely to ideate direct confrontation responses and report willingness to use direct confrontation responses in real situations. Our work contributes a methodology for examining student awareness and understanding of diversity issues as well as a demonstration that undergraduate computer science students need help in learning how to address common situations that involve either intentional or unintentional discrimination in an academic environment.</p>","PeriodicalId":48764,"journal":{"name":"ACM Transactions on Computing Education","volume":"37 2","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Computing Education","FirstCategoryId":"5","ListUrlMain":"https://doi.org/https://dl.acm.org/doi/10.1145/3550487","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
引用次数: 0
Abstract
Helping students learn to identify and respond to situations involving discrimination is important, especially in fields like Computer Science where there is evidence of an unwelcoming climate that disproportionately drives underrepresented students out of the field. While students should not be considered responsible for fixing issues around discrimination in their institutions, they do have a role to play. In this paper, we present the results of a study in which 318 undergraduate computer science majors were presented with scenarios of discrimination and asked to identify the issues, rate the severity of the issues, and ideate 3–5 responses to address the described situations. They were also asked to identify which of their responses would likely be most effective in addressing discrimination and which of their responses they would be most likely to use if they were in the situation described in real life. Our results show that while students generally are able to identify various forms of discrimination (sexism, racism, religious discrimination, ethnic discrimination, etc.), any ambiguity in a scenario led to students describing the scenario as less severe and/or as an example of oversensitivity. We also show that students come up with many passive responses to scenarios of discrimination (such as ignoring the situation or wishing it had not happened in the first place). Students in our study were more likely to say they would deploy passive responses in real life, shying away from responses that involve direct confrontation. We observed some differences between student demographic subgroups. Women and BIPOC students in CS tend to think these issues are more severe than men and White and Asian students in CS. Women are more likely to ideate direct confrontation responses and report willingness to use direct confrontation responses in real situations. Our work contributes a methodology for examining student awareness and understanding of diversity issues as well as a demonstration that undergraduate computer science students need help in learning how to address common situations that involve either intentional or unintentional discrimination in an academic environment.
期刊介绍:
ACM Transactions on Computing Education (TOCE) (formerly named JERIC, Journal on Educational Resources in Computing) covers diverse aspects of computing education: traditional computer science, computer engineering, information technology, and informatics; emerging aspects of computing; and applications of computing to other disciplines. The common characteristics shared by these papers are a scholarly approach to teaching and learning, a broad appeal to educational practitioners, and a clear connection to student learning.