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Timothy Kluthe; Hannah Stabler; Amelia McNamara; Andreas Stefik – Computer Science Education, 2025
Background and Context: Data science and statistics are used across a broad spectrum of professions, experience levels and programming languages. The popular scientific computing languages, such as Matlab, Python and R, were organized without using empirical methods to show evidence for or against their design choices, resulting in them feeling…
Descriptors: Programming Languages, Data Science, Statistical Analysis, Vocabulary
Tianxiao Yang; Jongpil Cheon – Computer Science Education, 2025
Background and context: There were few studies indicating if students' computational thinking (CT) self-efficacy and their CT performance were aligned with each other. Objectives: The study was to investigate if there was a discrepancy between students' CT self-efficacy and their CT performance. Method: Involving 104 non-CS undergraduate students…
Descriptors: Self Efficacy, Computer Science Education, Prediction, Teacher Expectations of Students
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
Aljumaily, Harith; Cuadra, Dolores; Laefer, Debra F. – Computer Science Education, 2019
Background: Conceptual models are an essential phase in software design, but they can create confusion and reduced performance for students in Database Design courses. Objective: A novel Relational Data Model Validation Tool (MVTool) was developed and tested to determine (1) if students who use MVTool perform better than those who do not, and (2)…
Descriptors: Models, Databases, Computer Science Education, Skills
Chen, Chen; Haduong, Paulina; Brennan, Karen; Sonnert, Gerhard; Sadler, Philip – Computer Science Education, 2019
Background and Context: The relationship between novices' first programming language and their future achievement has drawn increasing interest owing to recent efforts to expand K-12 computing education. This article contributes to this topic by analyzing data from a retrospective study of more than 10,000 undergraduates enrolled in introductory…
Descriptors: Computer Science Education, Programming Languages, College Students, Computer Attitudes
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
Vogel, Sara; Hoadley, Christopher; Castillo, Ana Rebeca; Ascenzi-Moreno, Laura – Computer Science Education, 2020
Background and Context: In this theory paper, we explore the concept of translanguaging from bilingual education, and its implications for teaching and learning programming and computing in especially computer science (CS) for all initiatives. Objective: We use translanguaging to examine how programming is and isn't like using human languages. We…
Descriptors: Bilingual Education, Code Switching (Language), Computer Science Education, Programming Languages
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
Touretzky, David S. – Computer Science Education, 2013
Modern robots, like today's smartphones, are complex devices with intricate software systems. Introductory robot programming courses must evolve to reflect this reality, by teaching students to make use of the sophisticated tools their robots provide rather than reimplementing basic algorithms. This paper focuses on teaching with Tekkotsu, an open…
Descriptors: Robotics, Computer Science Education, Programming, Science Curriculum
Thompson, Errol; Kinshuk – Computer Science Education, 2011
Object-oriented programming is seen as a difficult skill to master. There is considerable debate about the most appropriate way to introduce novice programmers to object-oriented concepts. Is it possible to uncover what the critical aspects or features are that enhance the learning of object-oriented programming? Practitioners have differing…
Descriptors: Expertise, Novices, Phenomenology, Learning Processes
Akin, H. Levent; Meriçli, Çetin; Meriçli, Tekin – Computer Science Education, 2013
Teaching the fundamentals of robotics to computer science undergraduates requires designing a well-balanced curriculum that is complemented with hands-on applications on a platform that allows rapid construction of complex robots, and implementation of sophisticated algorithms. This paper describes such an elective introductory course where the…
Descriptors: Robotics, Computer Science Education, Undergraduate Study, Introductory Courses
Boustedt, Jonas – Computer Science Education, 2012
The software industry needs well-trained software designers and one important aspect of software design is the ability to model software designs visually and understand what visual models represent. However, previous research indicates that software design is a difficult task to many students. This article reports empirical findings from a…
Descriptors: Foreign Countries, Computer Software, Computer Science Education, Programming
Sanchez, Pablo; Zorrilla, Marta; Duque, Rafael; Nieto-Reyes, Alicia – Computer Science Education, 2011
Models in Software Engineering are considered as abstract representations of software systems. Models highlight relevant details for a certain purpose, whereas irrelevant ones are hidden. Models are supposed to make system comprehension easier by reducing complexity. Therefore, models should play a key role in education, since they would ease the…
Descriptors: Computer Science Education, Computer Software, Programming, Programming Languages
Tekinerdogan, Bedir – Computer Science Education, 2011
Model-driven software development (MDSD) aims to support the development and evolution of software intensive systems using the basic concepts of model, metamodel, and model transformation. In parallel with the ongoing academic research, MDSD is more and more applied in industrial practices. After being accepted both by a broad community of…
Descriptors: Foreign Countries, Computer Software, Graduate Study, Industry
Sien, Ven Yu – Computer Science Education, 2011
Object-oriented analysis and design (OOAD) is not an easy subject to learn. There are many challenges confronting students when studying OOAD. Students have particular difficulty abstracting real-world problems within the context of OOAD. They are unable to effectively build object-oriented (OO) models from the problem domain because they…
Descriptors: Foreign Countries, Computer Science Education, Undergraduate Students, Computer Software
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