The Development and Validation of a Survey to Predict Computing Career Intentions

Yvonne Kao,Daniel L. Murphy,Aleata Hubbard Cheuoua, Priya Kannan,Jennifer Tsan, Kyle E. Jennings, Heather Smith, Shameeka Emanuel, Emily R. Miller

PROCEEDINGS OF THE 2023 ACM CONFERENCE ON INTERNATIONAL COMPUTING EDUCATION RESEARCH V.1, ICER 2023 V1(2023)

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摘要
Computing education through informal (out-of-school-time) programs provide a pathway for students of all ages to learn introductory programming and enter computing careers. Many of these programs explicitly aim to broaden participation in computing careers by recruiting and meeting the needs of students from historically underrepresented groups in computer science (CS). These programs frequently conduct internal or external evaluations of their effectiveness. These evaluations typically include surveys to measure changes in students' attitudes towards computing during the course of the program. However, measuring changes in students' career intentions is more challenging. While there are validated measures for career intentions, these surveys are typically long and impractical for administering as one of several end-of-program measures. Our goal for this work was to develop and collect initial evidence for the validity of a short, approximately 10-item, survey instrument that can be embedded within a broader evaluation effort and used to measure the impact of informal learning programs on students' computing career intentions. This paper describes the theoretical frameworks that informed the survey design, validation work through interviews, and large-scale field-testing of the survey.
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关键词
survey,validity,informal learning
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