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Showing 1 to 15 of 71 results Save | Export
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Stephanie Jill Lunn; Ellen Zerbe; Monique Ross – ACM Transactions on Computing Education, 2024
Although there is a great demand for graduates in computing fields, companies frequently struggle to find enough workers. They may also grapple with obtaining racial, ethnic, and gender diversity in representation. It has been suggested that the hiring process further contributes to these inequities. This study examined undergraduate computing…
Descriptors: Undergraduate Students, Computer Science Education, Disproportionate Representation, Employment
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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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El-Hamamsy, Laila; Pellet, Jean-Philippe; Roberts, Matthew; Kovacs, Helena; Bruno, Barbara; Zufferey, Jessica Dehler; Mondada, Francesco – ACM Transactions on Computing Education, 2023
Context: Introducing Computer Science (CS) into formal education can be challenging, notably when considering the numerous stakeholders involved which include the students, teachers, schools, and policy makers. We believe these perspectives should be considered conjointly, which is possible within Research Practice Partnerships (RPPs). RPPs look…
Descriptors: Theory Practice Relationship, Research and Development, Partnerships in Education, Computer Science Education
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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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Rodrigo Duran; Silvia Amélia Bim; Itana Gimenes; Leila Ribeiro; Ronaldo Celso Messias Correia – ACM Transactions on Computing Education, 2023
"Motivation": Enrollments in Brazilian computing degrees are at an all-time high, but graduation numbers have not increased at the same rate. Moreover, enrollment growth has mainly attracted male students, steadily expanding the gender gap in Brazilian computing programs. Such high attrition rates have a great economic impact and may…
Descriptors: Foreign Countries, Academic Persistence, Intention, Dropout Characteristics
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Antonija Mitrovic; Matthias Galster; Sanna Malinen; Jay Holland; Ja'afaru Musa; Negar Mohammadhassan; Raul Vincent Lumapas – ACM Transactions on Computing Education, 2023
Objectives: Communication skills are crucial for effective software development teams, but those skills are difficult to teach. The goal of our project is to evaluate the effectiveness of teaching face-to-face communication skills using AVW-Space, a platform for video-based learning that provides personalized nudges to support student's engagement…
Descriptors: Video Technology, Computer Software, Communication Skills, Electronic Learning
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Arif Rachmatullah; Jessica Vandenberg; Sein Shin; Eric Wiebe – ACM Transactions on Computing Education, 2023
The current study compared American, Korean, and Indonesian middle and high school students' CS attitudes. Concurrently, this study also examined whether the items in the CS attitudes scale exhibit country and gender measurement biases. We gathered data on CS attitudes from middle and high school students in the US, Korea, and Indonesia. The…
Descriptors: Foreign Countries, Middle School Students, High School Students, Computer Science
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Atiq, Zahra; Loui, Michael C. – ACM Transactions on Computing Education, 2022
In introductory computer programming courses, students experience a range of emotions. Students often experience anxiety and frustration when they encounter difficulties in writing programs. Continued frustration can discourage students from pursuing engineering and computing careers. Although prior research has shown how emotions affect students'…
Descriptors: Psychological Patterns, College Freshmen, Engineering Education, Programming
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Jacob, Sharin Rawhiya; Montoya, Jonathan; Nguyen, Ha; Richardson, Debra; Warschauer, Mark – ACM Transactions on Computing Education, 2022
Developing student interest is critical to supporting student learning in computer science. Research indicates that student interest is a key predictor of persistence and achievement. While there is a growing body of work on developing computing identities for diverse students, little research focuses on early exposure to develop multilingual…
Descriptors: Multilingualism, Student Development, Self Concept, Computer Science
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Bolloju, Narasimha – ACM Transactions on Computing Education, 2022
Domain models in software engineering--often represented as class diagrams--depict relevant classes in a given problem domain along with necessary relationships among those classes. These models are important because they establish links between the requirements of a given system under development and the subsequent phases of the systems…
Descriptors: Models, Computer Software, Student Attitudes, Cooperation
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Loksa, Dastyni; Margulieux, Lauren; Becker, Brett A.; Craig, Michelle; Denny, Paul; Pettit, Raymond; Prather, James – ACM Transactions on Computing Education, 2022
Metacognition and self-regulation are important skills for successful learning and have been discussed and researched extensively in the general education literature for several decades. More recently, there has been growing interest in understanding how metacognitive and self-regulatory skills contribute to student success in the context of…
Descriptors: Metacognition, Programming, Computer Science Education, Learning Processes
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McDonald, Nora; Akinsiku, Adegboyega; Hunter-Cevera, Jonathan; Sanchez, Maria; Kephart, Kerrie; Berczynski, Mark; Mentis, Helena M. – ACM Transactions on Computing Education, 2022
We studied the impact of introducing first-year computer science (CS) students to ethical thinking about the social justice impacts of data collection, tracking, bias, internet privacy, and competitive "real world" system design and critique activities. While basic content was consistent for all, one group was involved throughout the…
Descriptors: College Freshmen, Computer Science Education, Ethics, Social Justice
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Lee, Lina; Latulipe, Celine; Frevert, Tonya – ACM Transactions on Computing Education, 2022
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…
Descriptors: Student Attitudes, Diversity, Inclusion, Computer Science Education
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Flanigan, Abraham E.; Peteranetz, Markeya S.; Shell, Duane F.; Soh, Leen-Kiat – ACM Transactions on Computing Education, 2022
Two studies investigated change in computer science (CS) students' implicit intelligence beliefs. Across both studies, we found that the strength of incremental and entity beliefs changed across time. In Study 1, we found that incremental beliefs decreased and entity beliefs increased across the semester. Change in implicit intelligence beliefs…
Descriptors: Attitude Change, Computer Science Education, Student Attitudes, Intelligence
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Allen, Becky; McGough, Andrew Stephen; Devlin, Marie – ACM Transactions on Computing Education, 2022
Artificial Intelligence and its sub-disciplines are becoming increasingly relevant in numerous areas of academia as well as industry and can now be considered a core area of Computer Science. The Higher Education sector are offering more courses in Machine Learning and Artificial Intelligence than ever before. However, there is a lack of research…
Descriptors: Artificial Intelligence, Audiences, Computer Science Education, Higher Education
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