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Yingbin Zhang; Yafei Ye; Luc Paquette; Yibo Wang; Xiaoyong Hu – Journal of Computer Assisted Learning, 2024
Background: Learning analytics (LA) research often aggregates learning process data to extract measurements indicating constructs of interest. However, the warranty that such aggregation will produce reliable measurements has not been explicitly examined. The reliability evidence of aggregate measurements has rarely been reported, leaving an…
Descriptors: Learning Analytics, Learning Processes, Test Reliability, Psychometrics
Stephanie Yang; Miles Baird; Eleanor O’Rourke; Karen Brennan; Bertrand Schneider – ACM Transactions on Computing Education, 2024
Students learning computer science frequently struggle with debugging errors in their code. These struggles can have significant downstream effects--negatively influencing how students assess their programming ability and contributing to their decision to drop out of CS courses. However, debugging instruction is often an overlooked topic, and…
Descriptors: Computer Science Education, Troubleshooting, Programming, Teaching Methods
Han Wan; Hongzhen Luo; Mengying Li; Xiaoyan Luo – IEEE Transactions on Learning Technologies, 2024
Automatic program repair (APR) tools are valuable for students to assist them with debugging tasks since program repair captures the code modification to make a buggy program pass the given test-suite. However, the process of manually generating catalogs of code modifications is intricate and time-consuming. This article proposes contextual error…
Descriptors: Programming, Computer Science Education, Introductory Courses, Assignments
Ivanilse Calderon; Williamson Silva; Eduardo Feitosa – Informatics in Education, 2024
Teaching programming is a complex process requiring learning to develop different skills. To minimize the challenges faced in the classroom, instructors have been adopting active methodologies in teaching computer programming. This article presents a Systematic Mapping Study (SMS) to identify and categorize the types of methodologies that…
Descriptors: Foreign Countries, Undergraduate Study, Programming, Computer Science Education
Mehmet Arif Demirta¸; Max Fowler; Kathryn Cunningham – International Educational Data Mining Society, 2024
Analyzing which skills students develop in introductory programming education is an important question for the computer science education community. These key skills and concepts have been formalized as knowledge components, which are units of knowledge that can be measured by performance on a set of tasks. While knowledge components in other…
Descriptors: Programming, Computer Science Education, Skill Development, Knowledge Level
Rong, Wenge; Xu, Tianfan; Sun, Zhiwei; Sun, Zian; Ouyang, Yuanxin; Xiong, Zhang – IEEE Transactions on Education, 2023
Contribution: In this study, an object tuple model has been proposed, and a quasi-experimental study on its usage in an introductory programming language course has been reported. This work can be adopted by all C language teachers and students in learning pointer and array-related concepts. Background: C language has been extensively employed in…
Descriptors: Models, Introductory Courses, Programming, Computer Science Education
Hawlitschek, Anja; Berndt, Sarah; Schulz, Sandra – Computer Science Education, 2023
Background and Context: Pair programming is an important approach to fostering students' programming and collaborative learning skills. However, the empirical findings on pair programming are mixed, especially concerning effective instructional design. Objective: The objective of this literature review is to provide lecturers with systematic…
Descriptors: Cooperative Learning, Programming, Computer Science Education, College Students
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
Demir, Faruk – Education and Information Technologies, 2022
The abstract structure, logic, negative perceptions, and anxiety of programming are seen as obstacles to novice programmers. The importance of educational programming languages is increasing day by day in overcoming these obstacles. In this study, it was aimed to investigate the effect of educational programming language integration on academic…
Descriptors: Programming, Computer Science Education, Anxiety, Academic Achievement
W. Monty Jones; Katherine Hansen; Douglas Lusa Krug; Michael L. Schad; Nakisha Whittington; Xun Liu – Computer Science Education, 2025
Background and Context: Efforts to engage adult learners in computer science in the United States have been largely unsuccessful. While research examining the use of music for teaching computer programming with K-12 learners is emerging, little research with adult learners exists. Objective: This study evaluates the effect of computer coding…
Descriptors: Musical Composition, Computer Software, Adult Students, Student Attitudes
Christina Glasauer; Martin K. Yeh; Lois Anne DeLong; Yu Yan; Yanyan Zhuang – Computer Science Education, 2025
Background and Context: Feedback on one's progress is essential to new programming language learners, particularly in out-of-classroom settings. Though many study materials offer assessment mechanisms, most do not examine the accuracy of the feedback they deliver, nor give evidence on its validity. Objective: We investigate the potential use of a…
Descriptors: Novices, Computer Science Education, Programming, Accuracy
Smitha S. Kumar; Michael A. Lones; Manuel Maarek; Hind Zantout – ACM Transactions on Computing Education, 2025
Programming demands a variety of cognitive skills, and mastering these competencies is essential for success in computer science education. The importance of formative feedback is well acknowledged in programming education, and thus, a diverse range of techniques has been proposed to generate and enhance formative feedback for programming…
Descriptors: Automation, Computer Science Education, Programming, Feedback (Response)
Lynch, Tom Liam; Ardito, Gerald; Amendola, Pam – Eye on Education, 2020
"Integrating Computer Science Across the Core" is a guide to systematizing computer science and computational thinking practices in your school. While most books explain how to teach computer science as a stand-alone discipline, this innovative approach will help you leverage your existing curriculum to deepen and expand students'…
Descriptors: Elementary Secondary Education, Computer Science, Computer Science Education, Thinking Skills
Davis Krumins; Sandra Schumann; Veiko Vunder; Rauno Põlluäär; Kristjan Laht; Renno Raudmäe; Alvo Aabloo; Karl Kruusamäe – IEEE Transactions on Learning Technologies, 2024
Teaching robotics with the robot operating system (ROS) is valuable for instating good programming practices but requires significant setup steps from the learner. Providing a ready-made ROS learning environment over the web can make robotics more accessible; however, most of the previous remote labs have abstracted the authentic ROS developer…
Descriptors: Teaching Methods, Robotics, Programming, Computer Science Education
Adrian Salguero – ProQuest LLC, 2024
Introductory computer programming (i.e. CS1) is the entry point into the computer science major at higher education institutions worldwide. It introduces foundational concepts to students that are then built upon in future courses. Computer science as a whole has struggled to attract and retain students in the major, particularly women and…
Descriptors: Computer Science, Programming, Introductory Courses, Disproportionate Representation

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