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Cheers, Hayden; Lin, Yuqing – Computer Science Education, 2023
Background and Context: Source code plagiarism is a common occurrence in undergraduate computer science education. Many source code plagiarism detection tools have been proposed to address this problem. However, such tools do not identify plagiarism, nor suggest what assignment submissions are suspicious of plagiarism. Source code plagiarism…
Descriptors: Plagiarism, Programming, Computer Science Education, Identification
Kristina Litherland; Anders Kluge – Computer Science Education, 2024
Background and Context: We explore the potential for understanding the processes involved in students' programming based on studying their behaviour and dialogue with each other and "conversations" with their programs. Objective: Our aim is to explore how a perspective of inquiry can be used as a point of departure for insights into how…
Descriptors: Programming, Programming Languages, Secondary School Students, Computer Science Education
Heinsen Egan, Matthew; McDonald, Chris – Computer Science Education, 2021
Background and Context: Students learning the C programming language struggle to debug, and to understand the runtime behaviour of, their programs. Objective: We examine a tool that combines several novice-focused error detection, program visualization, and debugging techniques, to investigate which features students use in real study sessions,…
Descriptors: Computer Science Education, Programming Languages, Programming, Novices
Zhanxia Yang; Marina Bers – Computer Science Education, 2024
Background and Context: Historically, women have been underrepresented in computer science. To address this gender gap, researchers advocate for high-quality computer science programs for early childhood. Objectives: This study examines gender differences in coding performance before and after implementing a 24-lesson visual programming curriculum…
Descriptors: Gender Differences, Grade 1, Elementary School Students, Programming
Hao, Qiang; Smith, David H., IV; Ding, Lu; Ko, Amy; Ottaway, Camille; Wilson, Jack; Arakawa, Kai H.; Turcan, Alistair; Poehlman, Timothy; Greer, Tyler – Computer Science Education, 2022
Background and Context: automated feedback for programming assignments has great potential in promoting just-in-time learning, but there has been little work investigating the design of feedback in this context. Objective: to investigate the impacts of different designs of automated feedback on student learning at a fine-grained level, and how…
Descriptors: Computer Science Education, Feedback (Response), Teaching Methods, Comparative Analysis
Rich, Kathryn M.; Franklin, Diana; Strickland, Carla; Isaacs, Andy; Eatinger, Donna – Computer Science Education, 2022
Background and Context: We explored how learning trajectories (LTs) might be used to design variables instruction. Objective: We aimed to develop an LT for variables and use it to guide curriculum development for fourth graders working in Scratch in an integrated mathematics+CS curriculum. Method: We synthesized learning goals (LGs) and levels of…
Descriptors: Teaching Methods, Computer Science Education, Sequential Learning, Instructional Design
Hundhausen, C. D.; Conrad, P. T.; Carter, A. S.; Adesope, O. – Computer Science Education, 2022
Background and Context: Assessing team members' indivdiual contributions to software development projects poses a key problem for computing instructors. While instructors typically rely on subjective assessments, objective assessments could provide a more robust picture. To explore this possibility, In a 2020 paper, Buffardi presented a…
Descriptors: Computer Software, Computer Science Education, Correlation, Engineering Education
Pantic, Katarina; Clarke-Midura, Jody; Poole, Frederick; Roller, Jared; Allan, Vicki – Computer Science Education, 2018
Stereotypes people hold about computer scientists contribute to underrepresentation in computer science. Perceptions of computer scientists have historically been linked to males and a "nerd" culture, which can lead to lack of interest, particularly for girls. This article presents two studies conducted with two groups of middle…
Descriptors: Stereotypes, Computer Science, Disproportionate Representation, Gender Differences
Zakaria, Zarifa; Vandenberg, Jessica; Tsan, Jennifer; Boulden, Danielle Cadieux; Lynch, Collin F.; Boyer, Kristy Elizabeth; Wiebe, Eric N. – Computer Science Education, 2022
Background and Context: Researchers and practitioners have begun to incorporate collaboration in programming because of its reported instructional and professional benefits. However, younger students need guidance on how to collaborate in environments that require substantial interpersonal interaction and negotiation. Previous research indicates…
Descriptors: Feedback (Response), Intervention, Comparative Analysis, Programming
Teaching in an Open Village: A Case Study on Culturally Responsive Computing in Compulsory Education
Lachney, Michael; Bennett, Audrey G.; Eglash, Ron; Yadav, Aman; Moudgalya, Sukanya – Computer Science Education, 2021
Background: As teachers work to broaden the participation of racially and ethnically underrepresented groups in computer science (CS), culturally responsive computing (CRC) becomes more pertinent to formal settings. Objective: Yet, equity-oriented literature offers limited guidance for developing deep forms of CRC in the classroom. In response, we…
Descriptors: Culturally Relevant Education, Computer Science Education, Equal Education, Case Studies
Tushev, Miroslav; Williams, Grant; Mahmoud, Anas – Computer Science Education, 2020
Background and Context: GitHub has been recently used in Software Engineering (SE) classes to facilitate collaboration in student team projects as well as help teachers to evaluate the contributions of their students more objectively. Objective: We explore the benefits and drawbacks of using GitHub as a means for team collaboration and performance…
Descriptors: Computer Software, Engineering Education, Student Projects, Teamwork
Petrie, Christopher – Computer Science Education, 2022
Background and Context: Computational Thinking (CT) has been recently integrated into new and revised Digital Technologies content (DTC) in the Technology learning area of the New Zealand School Curriculum. Objective: To aid this change, this research examined how CT supports learning outcomes in both music and programming with the Sonic Pi…
Descriptors: Interdisciplinary Approach, Outcomes of Education, Computer Science Education, Programming
Lyon, Louise Ann; Green, Emily – Computer Science Education, 2020
Background and Context: Non-traditional training grounds such as coding boot camps that attract a higher proportion of women are important sites for understanding how to broaden participation in computing. Objective: This work aims to help us better understand the women choosing boot camps and their pathways through these camps and into the…
Descriptors: Coding, Females, Nontraditional Education, Computer Science Education
Prado, Yenda; Jacob, Sharin; Warschauer, Mark – Computer Science Education, 2022
Background and Context: Computational Thinking (CT) is a skill all students should learn. This requires using inclusive approaches to teach CT to a wide spectrum of students. However, strategies for teaching CT to students with exceptionalities are not well studied. Objective: This study draws on lessons learned in two fourth-grade classrooms --…
Descriptors: Thinking Skills, Computer Science Education, Special Education, Teaching Methods
de Ruiter, Laura E.; Bers, Marina U. – Computer Science Education, 2022
Background and Context: Despite the increasing implementation of coding in early curricula, there are few valid and reliable assessments of coding abilities for young children. This impedes studying learning outcomes and the development and evaluation of curricula. Objective: Developing and validating a new instrument for assessing young…
Descriptors: Programming Languages, Computer Software, Coding, Computer Science Education