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Abraham E. Flanigan; Markeya S. Peteranetz; Duane F. Shell; Leen-Kiat Soh – ACM Transactions on Computing Education, 2023
Objectives: Although prior research has uncovered shifts in computer science (CS) students' implicit beliefs about the nature of their intelligence across time, little research has investigated the factors contributing to these changes. To address this gap, two studies were conducted in which the relationship between ineffective self-regulation of…
Descriptors: Computer Science Education, Self Concept, Intelligence, Self Management
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Belland, Brian R.; Kim, Chanmin; Zhang, Anna Y.; Lee, Eunseo – ACM Transactions on Computing Education, 2023
This article reports the analysis of data from five different studies to identify predictors of preservice, early childhood teachers' views of (a) the nature of coding, (b) integration of coding into preschool classrooms, and (c) relation of coding to fields other than computer science (CS). Significant changes in views of coding were predicted by…
Descriptors: Predictor Variables, Preservice Teachers, Student Attitudes, Programming
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Sax, Linda J.; Newhouse, Kaitlin N. S.; Goode, Joanna; Nakajima, Tomoko M.; Skorodinsky, Max; Sendowski, Michelle – ACM Transactions on Computing Education, 2022
The Advanced Placement Computer Science Principles (APCSP) course was introduced in 2016 to address long-standing gender and racial/ethnic disparities in the United States among students taking Advanced Placement Computer Science (APCS) in high school, as well as among those who pursued computing majors in college. Although APCSP has drawn a more…
Descriptors: Advanced Placement Programs, Computer Science Education, Equal Education, High School Students
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Weston, Timothy J.; Dubow, Wendy M.; Kaminsky, Alexis – ACM Transactions on Computing Education, 2020
While demand for computer science and information technology skills grows, the proportion of women entering computer science (CS) fields has declined. One critical juncture is the transition from high school to college. In our study, we examined factors predicting college persistence in computer science- and technology-related majors from data…
Descriptors: Females, Academic Persistence, High School Students, Computer Science Education
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Tomkin, Jonathan H.; West, Matthew; Herman, Geoffrey L. – ACM Transactions on Computing Education, 2018
We present a methodological improvement for calculating Grade Point Averages (GPAs). Heterogeneity in grading between courses systematically biases observed GPAs for individual students: the GPA observed depends on course selection. We show how a logistic model can account for course selection by simulating how every student in a sample would…
Descriptors: Grade Point Average, Grading, Predictor Variables, Grades (Scholastic)
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Wagner, Isabel – ACM Transactions on Computing Education, 2016
The term "gender gap" refers to the significant underrepresentation of females in many subjects. In Computer Science, the gender gap exists at all career levels. In this article, we study whether there is a performance gap in addition to the gender gap. To answer this question, we analyzed statistical data on student performance in…
Descriptors: Gender Differences, Academic Achievement, Computer Science Education, College Students
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Pappas, Ilias O.; Giannakos, Michail N.; Jaccheri, Letizia; Sampson, Demetrios G. – ACM Transactions on Computing Education, 2017
This study uses complexity theory to understand the causal patterns of factors that stimulate students' intention to continue studies in computer science (CS). To this end, it identifies gains and barriers as essential factors in CS education, including motivation and learning performance, and proposes a conceptual model along with research…
Descriptors: Intention, Student Behavior, Computer Science Education, Barriers
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Rosson, Mary Beth; Carroll, John M.; Sinha, Hansa – ACM Transactions on Computing Education, 2011
Researchers have been working to understand the factors that may be contributing to low rates of participation by women and other minorities in the computer and information sciences (CIS). We describe a multivariate investigation of male and female university students' orientation to CIS careers. We focus on the roles of "self-efficacy"…
Descriptors: Careers, Social Support Groups, Career Planning, Females