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Renske Weeda; Sjaak Smetsers; Erik Barendsen – Computer Science Education, 2024
Background and Context: Multiple studies report that experienced instructors lack consensus on the difficulty of programming tasks for novices. However, adequately gauging task difficulty is needed for alignment: to select and structure tasks in order to assess what students can and cannot do. Objective: The aim of this study was to examine…
Descriptors: Novices, Coding, Programming, Computer Science Education
Zachary M. Savelson; Kasia Muldner – Computer Science Education, 2024
Background and Context: Productive failure (PF) is a learning paradigm that flips the order of instruction: students work on a problem, then receive a lesson. PF increases learning, but less is known about student emotions and collaboration during PF, particularly in a computer science context. Objective: To provide insight on students' emotions…
Descriptors: Student Attitudes, Psychological Patterns, Fear, Failure
Bikanga Ada, Mireilla; Foster, Mary Ellen – Computer Science Education, 2023
Objective: This study explores postgraduate students' perceptions of the modified team-based learning instructional approach used to teach it and the extent to which the Bootcamp course improves their practical skills. Method: In the beginning, participants (n = 185) were asked to rate their practical experience on the taught topics. At the end…
Descriptors: Graduate Students, Cooperative Learning, Program Length, Computer Science Education
Zdawczyk, Christina; Varma, Keisha – Computer Science Education, 2023
Background and Context: A continued gender disparity has driven a need for effective interventions for recruiting girls to computer science. Prior research has demonstrated that middle school girls hold beliefs and attitudes that keep them from learning computer science, which can be mitigated through classroom design. Objective: This study…
Descriptors: Females, Computer Science Education, Gender Differences, Student Attitudes
Indriasari, Theresia Devi; Denny, Paul; Lottridge, Danielle; Luxton-Reilly, Andrew – Computer Science Education, 2023
Background and Context: Peer code review activities provide well-documented benefits to students in programming courses. Students develop relevant skills through exposure to alternative coding solutions, producing and receiving feedback, and collaboration with peers. Despite these benefits, low student motivation has been identified as one of the…
Descriptors: Peer Evaluation, Student Motivation, Cooperative Learning, Programming
Moskal, Adon Christian Michael; Wass, Rob – Computer Science Education, 2019
Background and Context: Encouraging undergraduate programming students to think more about their software development processes is challenging. Most programming courses focus on coding skill development and mastering programming language features; subsequently software development processes (e.g. planning, code commenting, and error debugging) are…
Descriptors: Computer Software, Undergraduate Students, Programming, Programming Languages
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
Xu, Zhen; Ritzhaupt, Albert D.; Umapathy, Karthikeyan; Ning, Yang; Tsai, Chin-Chung – Computer Science Education, 2021
Background and context: Researchers have been looking into the complexity of computer science (CS) education and tried to apply rigorous and relevant educational research methods to understand and facilitate the learning experience of students. Objective: The purpose of this study was to explore college students' conceptions of learning CS to shed…
Descriptors: College Students, Student Attitudes, Computer Science Education, Freehand Drawing
Teresa M. Ober; Ying Cheng; Meghan R. Coggins; Paul Brenner; Janice Zdankus; Philip Gonsalves; Emmanuel Johnson; Tim Urdan – Computer Science Education, 2024
Background and Context: Differences in children's and adolescents' initial attitudes about computing and other STEM fields may form during middle school and shape decisions leading to career entry. Early emerging differences in career interest may propagate a lack of diversity in computer science and programming fields. Objective: Though middle…
Descriptors: Middle School Students, Student Attitudes, Computer Science Education, STEM Education
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
Hamouda, Sally; Edwards, Stephen H.; Elmongui, Hicham G.; Ernst, Jeremy V.; Shaffer, Clifford A. – Computer Science Education, 2020
Background and Context: Recursion in binary trees has proven to be a hard topic. There was not much research on enhancing student understanding of this topic. Objective: We present a tutorial to enhance learning through practice of recursive operations in binary trees, as it is typically taught post-CS2. Method: We identified the misconceptions…
Descriptors: Computer Science Education, Programming, Coding, Student Attitudes
Lui, Debora; Kafai, Yasmin; Litts, Breanne; Walker, Justice; Widman, Sari – Computer Science Education, 2020
Background and Context: Physical computing involves complex negotiations of multiple, on and off-screen tasks, which calls for research on how to best structure collaborative work to ensure equitable learning. Objective: We focus on how pairs self-organized their multi-domain tasks in physical computing, and how their social interactions supported…
Descriptors: Cooperative Learning, High School Students, 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
Campe, Shannon; Denner, Jill; Green, Emily; Torres, David – Computer Science Education, 2020
Background and Context: Pair programming is used in classrooms to promote learning and engage a more diverse group of students in computing fields, but little is known about what it looks like in middle school. Objective: The aim of this study was to examine how programming pairs were interacting and about what. Method: Video, audio, and screen…
Descriptors: Cooperative Learning, Programming, Computer Science Education, Middle School Students
Becker, Brett A.; Glanville, Graham; Iwashima, Ricardo; McDonnell, Claire; Goslin, Kyle; Mooney, Catherine – Computer Science Education, 2016
Programming is an essential skill that many computing students are expected to master. However, programming can be difficult to learn. Successfully interpreting compiler error messages (CEMs) is crucial for correcting errors and progressing toward success in programming. Yet these messages are often difficult to understand and pose a barrier to…
Descriptors: Computer Science Education, Programming, Novices, Error Patterns