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Showing 1 to 15 of 129 results Save | Export
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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
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Dan Sun; Fan Xu – Journal of Educational Computing Research, 2025
Real-time collaborative programming (RCP), which allows multiple programmers to work concurrently on the same codebase with changes instantly visible to all participants, has garnered considerable popularity in higher education. Despite this trend, little work has rigorously examined how undergraduates engage in collaborative programming when…
Descriptors: Cooperative Learning, Programming, Computer Science Education, Undergraduate Students
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Jule Scheper; Robin Leuppert; Daniel Possler; Anna Freytag; Sophie Bruns; Julia Niemann-Lenz – Journalism and Mass Communication Educator, 2025
Despite the increasing use of the statistical programming language R in statistics and data analysis (SDA), its implementation in communication science education is limited. Experiences, recommendations, and a critical exchange are therefore scarce. The following contribution addresses this very gap. At the Department of Journalism and…
Descriptors: Journalism Education, Programming Languages, Statistical Analysis, Data Analysis
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Ruijie Zhou; Chong Xie; Xiuling He; Yangyang Li; Qiong Fan; Ying Yu; Zhonghua Yan – Journal of Educational Computing Research, 2024
Computational thinking (CT), an essential competency for comprehending and addressing intricate issues in the digital world, has been incorporated into curriculum planning as a goal for programming education. This study introduced flow design into programming curricula to investigate its impact on undergraduates 'CT skills during pair work. Two…
Descriptors: Undergraduate Students, Thinking Skills, Computation, Programming
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Ting-Ting Wu; Hsin-Yu Lee; Pei-Hua Chen; Wei-Sheng Wang; Yueh-Min Huang – Journal of Computer Assisted Learning, 2025
Background: Conventional reflective learning methodologies in programming education often lack structured guidance and individualised feedback, limiting their pedagogical effectiveness. Whilst computational thinking (CT) offers a systematic problem-solving framework with decomposition, pattern recognition, abstraction, and algorithm design, its…
Descriptors: Computation, Thinking Skills, Educational Diagnosis, Diagnostic Tests
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Carscadden, Kelly; Martin, Andrew – International Journal of Higher Education, 2022
An essential skill for STEM undergraduates is the ability to understand the world by manipulating, visualizing, and analyzing data to make or evaluate claims. Current online debate, without peer-reviewed literature, explores which of two common R syntax environments (base R or tidyverse) is best for teaching novice R users. In an in-person…
Descriptors: Biology, Undergraduate Students, Programming Languages, Teaching Methods
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Tippawan Meepung – International Education Studies, 2024
This study explores the application of the Project-Based Learning with Gamification Model (PBLGM) through Visual Programming Language (VPL) to enhance digital competencies and problem-solving skills in learners. The PBLGM model integrates project-based learning and gamification techniques using Kodu Game Lab, aiming to develop essential…
Descriptors: Student Projects, Active Learning, Gamification, Foreign Countries
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Yang Shi; Robin Schmucker; Keith Tran; John Bacher; Kenneth Koedinger; Thomas Price; Min Chi; Tiffany Barnes – Journal of Educational Data Mining, 2024
Understanding students' learning of knowledge components (KCs) is an important educational data mining task and enables many educational applications. However, in the domain of computing education, where program exercises require students to practice many KCs simultaneously, it is a challenge to attribute their errors to specific KCs and,…
Descriptors: Programming Languages, Undergraduate Students, Learning Processes, Teaching Models
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Toni Taipalus; Hilkka Grahn; Saima Ritonummi; Valtteri Siitonen; Tero Vartiainen; Denis Zhidkikh – ACM Transactions on Computing Education, 2025
SQL compiler error messages are the primary way users receive feedback when they encounter syntax errors or other issues in their SQL queries. Effective error messages can enhance the user experience by providing clear, informative, and actionable feedback. Despite the age of SQL compilers, it still remains largely unclear what contributes to an…
Descriptors: Computer Science Education, Novices, Information Systems, Programming Languages
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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
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Tamas Balla; Sandor Kiraly; Roland Kiraly – Discover Education, 2025
Educational games have gained widespread interest among teachers and researchers across various fields due to their capacity to engage students, foster active participation, and improve learning outcomes. In the context of computer programming, which demands significant cognitive effort, the use of educational games has grown substantially. While…
Descriptors: Educational Games, Gamification, Programming, Programming Languages
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Esche, Svana; Weihe, Karsten – IEEE Transactions on Education, 2023
Contribution: Most work on languages in computing education currently focuses on non-native speakers. In contrast, to the best of the authors' knowledge, this article is the first response to the call for research on terms that takes into account the terms used by novices in their language. Background: Terms are key factors in communication,…
Descriptors: Programming Languages, Computer Science Education, Misconceptions, Undergraduate Students
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Amelia McNamara – Journal of Statistics and Data Science Education, 2024
When incorporating programming into a statistics course, there are many pedagogical considerations. In R, one consideration is the particular R syntax used. This article reports on a head-to-head comparison of a pair of introductory statistics labs, one conducted in the formula syntax, the other in tidyverse. Pre- and post-surveys show minimal…
Descriptors: Teaching Methods, Introductory Courses, Statistics Education, Programming Languages
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Erik Hombre Cuevas; Daniel Zaldivar; Marco Perez – International Journal of Information and Communication Technology Education, 2025
The integration of various programming languages into the undergraduate engineering curriculum often occurs without adequate evaluation of their effectiveness within specific disciplines. Recently, Python and MATLAB have garnered significant attention as preferred languages for teaching subjects such as image processing and computer vision.…
Descriptors: Influence of Technology, Technology Uses in Education, Programming Languages, Academic Achievement
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Rebeckah K. Fussell; Megan Flynn; Anil Damle; Michael F. J. Fox; N. G. Holmes – Physical Review Physics Education Research, 2025
Recent advancements in large language models (LLMs) hold significant promise for improving physics education research that uses machine learning. In this study, we compare the application of various models for conducting a large-scale analysis of written text grounded in a physics education research classification problem: identifying skills in…
Descriptors: Physics, Computational Linguistics, Classification, Laboratory Experiments
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