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Leah Bidlake; Eric Aubanel; Daniel Voyer – ACM Transactions on Computing Education, 2025
Research on mental model representations developed by programmers during parallel program comprehension is important for informing and advancing teaching methods including model-based learning and visualizations. The goals of the research presented here were to determine: how the mental models of programmers change and develop as they learn…
Descriptors: Schemata (Cognition), Programming, Computer Science Education, Coding
Bhagya Munasinghe; Tim Bell; Anthony Robins – ACM Transactions on Computing Education, 2023
In learning to program and understanding how a programming language controls a computer, learners develop both insights and misconceptions whilst their mental models are gradually refined. It is important that the learner is able to distinguish the different elements and roles of a computer (compiler, interpreter, memory, etc.), which novice…
Descriptors: Computation, Thinking Skills, Programming, Programming Languages
Matthieu Branthôme – ACM Transactions on Computing Education, 2024
This article reports on a design-based research study centered on the conception and the assessment of the "Pyrates" application. This online serious game aims at introducing Python programming to K-12 students while easing the transition from block-based to text-based languages. After we present the various aspects underlying the…
Descriptors: Educational Games, Programming, Elementary Secondary Education, Programming Languages
Brown, Neil C. C.; Weill-Tessier, Pierre; Sekula, Maksymilian; Costache, Alexandra-Lucia; Kölling, Michael – ACM Transactions on Computing Education, 2023
Objectives: Java is a popular programming language for use in computing education, but it is difficult to get a wide picture of the issues that it presents for novices; most studies look only at the types or frequency of errors. In this observational study, we aim to learn how novices use different features of the Java language. Participants:…
Descriptors: Novices, Programming, Programming Languages, Data
Rita Garcia; Michelle Craig – ACM Transactions on Computing Education, 2025
Introduction: Computer Science Education does not have a universally defined set of concepts consistently covered in all introductory courses (CS1). One approach to understanding the concepts covered in CS1 is to ask educators. In 2004, Nell Dale did just this. She also collected their perceptions on challenging topics to teach. Dale mused how the…
Descriptors: Replication (Evaluation), Teaching Methods, Computer Science Education, Introductory Courses
Miedema, Daphne; Fletcher, George; Aivaloglou, Efthimia – ACM Transactions on Computing Education, 2023
Prior studies in the Computer Science education literature have illustrated that novices make many mistakes in composing SQL queries. Query formulation proves to be difficult for students. Only recently, some headway was made towards understanding why SQL leads to so many mistakes, by uncovering student misconceptions. In this article, we shed new…
Descriptors: Computer Science Education, Novices, Misconceptions, Programming Languages
Meija Lohiniva; Ville Isomöttönen – ACM Transactions on Computing Education, 2025
Context: Introductory programming courses often face high dropout and failure rates, a challenge widely addressed in computing education research. Collaborative methods, such as group work and pair programming, have been proposed as potential solutions, as they are believed to enhance students' study motivation. Objective: This article provides a…
Descriptors: Cooperative Learning, Student Motivation, Introductory Courses, Computer Science Education
Muldner, Kasia; Jennings, Jay; Chiarelli, Veronica – ACM Transactions on Computing Education, 2023
This article reviews literature on worked examples in the context of programming activities. We focus on two types of examples, namely, code-tracing and code-generation, because there is sufficient research on these to warrant a review. We synthesize key results according to themes that emerged from the review. This synthesis aims to provide…
Descriptors: Problem Solving, Programming, Computer Science Education, Literature Reviews
Radek Pelánek – ACM Transactions on Computing Education, 2025
Learning environments for programming education need a comprehensive task set that guides students from basic programming concepts to complex challenges. For creating such a task set, it is beneficial to utilize the concept of a design space--a systematic mapping of design dimensions and choices along these dimensions. We propose an iterative…
Descriptors: Computer Science Education, Programming, Design, Task Analysis
Kao, Yvonne; Matlen, Bryan; Weintrop, David – ACM Transactions on Computing Education, 2022
The 1980s and 1990s saw a robust connection between computer science education and cognitive psychology as researchers worked to understand how students learn to program. More recently, academic disciplines such as science and engineering have begun drawing on cognitive psychology research and theories of learning to create instructional materials…
Descriptors: Computer Science Education, Cognitive Psychology, Transfer of Training, Programming
Neil C. C. Brown; Pierre Weill-Tessier; Juho Leinonen; Paul Denny; Michael Kölling – ACM Transactions on Computing Education, 2025
Motivation: Students learning to program often reach states where they are stuck and can make no forward progress--but this may be outside the classroom where no instructor is available to help. In this situation, an automatically generated next-step hint can help them make forward progress and support their learning. It is important to know what…
Descriptors: Artificial Intelligence, Programming, Novices, Technology Uses in Education
Anna Rechtácková; Radek Pelánek; Tomáš Effenberger – ACM Transactions on Computing Education, 2025
Code quality is a critical aspect of programming, as high-quality code is easier to maintain, and code maintenance constitutes the majority of software costs. Consequently, code quality should be emphasized in programming education. While previous research has identified numerous code quality defects commonly made by students, the current state…
Descriptors: Programming, Computer Science Education, Error Patterns, Automation
Camilo Vieira; Andrea Vásquez; Federico Meza; Roxana Quintero-Manes; Pedro Godoy – ACM Transactions on Computing Education, 2024
Currently, there is little evidence about how non-English-speaking students learn computer programming. For example, there are few validated assessment instruments to measure the development of programming skills, especially for the Spanish-speaking population. Having valid assessment instruments is essential to identify the difficulties of the…
Descriptors: Programming, Spanish Speaking, Translation, Test Validity
Yun Huang; Christian Dieter Schunn; Julio Guerra; Peter L. Brusilovsky – ACM Transactions on Computing Education, 2024
Programming skills are increasingly important to the current digital economy, yet these skills have long been regarded as challenging to acquire. A central challenge in learning programming skills involves the simultaneous use of multiple component skills. This article investigates why students struggle with integrating component skills--a…
Descriptors: Programming, Computer Science Education, Error Patterns, Classification
Ibrahim Albluwi; Raghda Hriez; Raymond Lister – ACM Transactions on Computing Education, 2025
Explain-in-Plain-English (EiPE) questions are used by some researchers and educators to assess code reading skills. EiPE questions require students to briefly explain (in plain English) the purpose of a given piece of code, without restating what the code does line-by-line. The premise is that novices who can explain the purpose of a piece of code…
Descriptors: Questioning Techniques, Programming, Computer Science Education, Student Evaluation

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