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Showing 1 to 15 of 18 results Save | Export
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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
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Ainhoa Berciano; Astrid Cuida; María-Luisa Novo – Education and Information Technologies, 2025
In the last two decades, computational thinking has gained wide relevance in international educational systems. The inclusion of this new type of thinking poses educational challenges with some underlying research questions that need to be answered to meet these challenges with quality. Thus, this study focuses on analyzing the difficulties that…
Descriptors: Coding, Translation, Programming Languages, Sequential Approach
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Xiaoheng Yan; Gila Hanna – International Journal of Mathematical Education in Science and Technology, 2025
As new technological developments continue to change the educational landscape, it is not an exception in the area of proof and proving. This classroom note introduces the use of one of the trending proofs assistants -- the Lean theorem prover. We first provide a technical account of Lean, then exemplify Lean proofs in propositional logic, number…
Descriptors: Mathematics Instruction, Undergraduate Students, Mathematical Logic, Validity
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Mark W. Isken – INFORMS Transactions on Education, 2025
A staple of many spreadsheet-based management science courses is the use of Excel for activities such as model building, sensitivity analysis, goal seeking, and Monte-Carlo simulation. What might those things look like if carried out using Python? We describe a teaching module in which Python is used to do typical Excel-based modeling and…
Descriptors: Spreadsheets, Models, Programming Languages, Monte Carlo Methods
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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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Guangyao Zhang; Lili Wang; Furong Shang; Xianwen Wang – Journal of Higher Education Policy and Management, 2025
The growth in digitalisation has led to an increasing demand for digital skills in various job sectors. In particular, employers in scientific job areas have shown interest in candidates possessing digital competencies. This study aims to analyse the digital skill requirements for candidates in scientific job opportunities. The content analysis is…
Descriptors: Technological Literacy, Job Skills, Employment Qualifications, Employer Attitudes
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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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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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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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Jila Niknejad; Margaret Bayer – International Journal of Mathematical Education in Science and Technology, 2025
In Spring 2020, the need for redesigning online assessments to preserve integrity became a priority to many educators. Many of us found methods to proctor examinations using Zoom and proctoring software. Such examinations pose their own issues. To reduce the technical difficulties and cost, many Zoom proctored examination sessions were shortened;…
Descriptors: Mathematics Instruction, Mathematics Tests, Computer Assisted Testing, Computer Software
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Wesley F. Reinhart; Reed Williams; Ryan Solnosky; R. Allen Kimel; Rebecca Napolitano – Advances in Engineering Education, 2025
Data science has become an increasingly popular topic among engineering students and practitioners as high-profile engineering applications of machine learning and artificial intelligence continue to make headlines. Companies in engineering domains are placing a growing emphasis on hiring engineers who can extract insights and create value from…
Descriptors: Engineering Education, Statistics Education, Education Work Relationship, Artificial Intelligence
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David Kocsis; Morgan Shepherd; Daniel L. Segal – Journal of Information Systems Education, 2025
This paper describes the development of a training module to improve students' individual online behaviors. We developed this module to integrate cyber hygiene concepts into a hands-on learning activity where students develop and secure a mobile web application using the Salesforce Developer tool. This new module aims to prepare the next…
Descriptors: Tutorial Programs, Computer Science Education, Computer Security, Programming
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Ethan C. Campbell; Katy M. Christensen; Mikelle Nuwer; Amrita Ahuja; Owen Boram; Junzhe Liu; Reese Miller; Isabelle Osuna; Stephen C. Riser – Journal of Geoscience Education, 2025
Scientific programming has become increasingly essential for manipulating, visualizing, and interpreting the large volumes of data acquired in earth science research. Yet few discipline-specific instructional approaches have been documented and assessed for their effectiveness in equipping geoscience undergraduate students with coding skills. Here…
Descriptors: Earth Science, Undergraduate Students, Programming Languages, Computer Software
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Christine Eith; Denise Zawada – Impacting Education: Journal on Transforming Professional Practice, 2025
This paper proposes a framework for integrating generative artificial intelligence (AI) tools into statistical training for Doctor of Education (EdD) students. The rigorous demands of doctoral education, coupled with the challenges of learning complex statistical software and coding language, often lead to anxiety and frustration among students,…
Descriptors: Doctoral Programs, Artificial Intelligence, Technology Integration, Statistics Education
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