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Austin M. Shin; Ayaan M. Kazerouni – ACM Transactions on Computing Education, 2024
Background and Context: Students' programming projects are often assessed on the basis of their tests as well as their implementations, most commonly using test adequacy criteria like branch coverage, or, in some cases, mutation analysis. As a result, students are implicitly encouraged to use these tools during their development process (i.e., so…
Descriptors: Feedback (Response), Programming, Student Projects, Computer Software
Yiting Wang; Tong Li; Jiahui You; Xinran Zhang; Congkai Geng; Yu Liu – ACM Transactions on Computing Education, 2025
Understanding software modelers' difficulties and evaluating their performance is crucial to Model-Driven Engineering (MDE) education. The software modeling process contains fine-grained information about the modelers' analysis and thought processes. However, existing research primarily focuses on identifying obvious issues in the software…
Descriptors: Computer Software, Engineering Education, Models, Identification
Kelvin T. Afolabi; Timothy R. Konold – Practical Assessment, Research & Evaluation, 2024
Exploratory structural equation (ESEM) has received increased attention in the methodological literature as a promising tool for evaluating latent variable measurement models. It overcomes many of the limitations attached to exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), while capitalizing on the benefits of each. Given…
Descriptors: Measurement Techniques, Factor Analysis, Structural Equation Models, Comparative Analysis
Selcuk Acar; Peter Organisciak; Denis Dumas – Journal of Creative Behavior, 2025
In this three-study investigation, we applied various approaches to score drawings created in response to both Form A and Form B of the Torrance Tests of Creative Thinking-Figural (broadly TTCT-F) as well as the Multi-Trial Creative Ideation task (MTCI). We focused on TTCT-F in Study 1, and utilizing a random forest classifier, we achieved 79% and…
Descriptors: Scoring, Computer Assisted Testing, Models, Correlation
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
Kuan-Yu Jin; Wai-Lok Siu – Journal of Educational Measurement, 2025
Educational tests often have a cluster of items linked by a common stimulus ("testlet"). In such a design, the dependencies caused between items are called "testlet effects." In particular, the directional testlet effect (DTE) refers to a recursive influence whereby responses to earlier items can positively or negatively affect…
Descriptors: Models, Test Items, Educational Assessment, Scores
André de Sá Braga Oliveira; Luciano César P. C. Leonel; Edward R. LaHood; Bachtri T. Nguyen; Anahid Ehtemami; Stephen P. Graepel; Michael J. Link; Carlos D. Pinheiro-Neto; Nirusha Lachman; Jonathan M. Morris; Maria Peris-Celda – Anatomical Sciences Education, 2024
The 3D stereoscopic technique consists in providing the illusional perception of depth of a given object using two different images mimicking how the right and left eyes capture the object. Both images are slightly different and when overlapped gives a three-dimensional (3D) experience. Considering the limitations for establishing surgical…
Descriptors: Computer Simulation, Photography, Visualization, Models
Ia Williamsson; Linda Askenäs – Learning Organization, 2024
Purpose: This study aims to understand how practitioners use their insights in software development models to share experiences within and between organizations. Design/methodology/approach: This is a qualitative study of practitioners in software development projects, in large-, medium- or small-size businesses. It analyzes interview material in…
Descriptors: Organizational Learning, Computer Software, Business, Reflection
Elkhatat, Ahmed M. – International Journal for Educational Integrity, 2023
Academic plagiarism is a pressing concern in educational institutions. With the emergence of artificial intelligence (AI) chatbots, like ChatGPT, potential risks related to cheating and plagiarism have increased. This study aims to investigate the authenticity capabilities of ChatGPT models 3.5 and 4 in generating novel, coherent, and accurate…
Descriptors: Artificial Intelligence, Plagiarism, Integrity, Models
Bolloju, Narasimha – ACM Transactions on Computing Education, 2022
Domain models in software engineering--often represented as class diagrams--depict relevant classes in a given problem domain along with necessary relationships among those classes. These models are important because they establish links between the requirements of a given system under development and the subsequent phases of the systems…
Descriptors: Models, Computer Software, Student Attitudes, Cooperation
Weikang Lu; Chenghua Lin – Asia-Pacific Education Researcher, 2025
Based on the UTAUT model, many studies have analyzed the factors influencing the use of artificial intelligence by teachers and students, but the conclusions are not uniform. This study chose high quality studies and encoded them to do meta analysis. After heterogeneity testing, sensitivity analysis and publication bias test, it has been found…
Descriptors: Meta Analysis, Technology Integration, Computer Software, Artificial Intelligence
Ben Markey; David West Brown; Michael Laudenbach; Alan Kohler – Written Communication, 2024
ChatGPT and other LLMs are at the forefront of pedagogical considerations in classrooms across the academy. Many studies have spoken to the technology's capacity to generate one-off texts in a variety of genres. This study complements those by inquiring into its capacity to generate compelling texts at scale. In this study, we quantitatively and…
Descriptors: Content Analysis, Language Usage, Artificial Intelligence, Computer Software
Diana Kirk; Andrew Luxton-Reilly; Ewan Tempero – ACM Transactions on Computing Education, 2025
Objectives: Code style is an important aspect of text-based programming because programs written with good style are considered easier to understand and change and so improve the maintainability of the delivered software product. However teaching code style is complicated by the existence of many style guides and standards that contain…
Descriptors: Computer Science Education, Programming, Computer Software, Teaching Methods
Ivaylo Staribratov; Nikol Manolova – Discover Education, 2024
The article presents the application of 3D technologies in STEAM education through a conducted scientific research, highlighting the role of 3D modeling and 3D printing as an innovative approach in achieving an interdisciplinary learning model. The research included the following stages: preparation for designing a detailed 3D steam locomotive…
Descriptors: Art Education, STEM Education, Educational Technology, Technology Uses in Education
Kamil Çelik; Ahmet Ayaz – Educational Technology Research and Development, 2025
Technological advancements in recent years have accelerated the development of information and communication technologies, introducing numerous innovations. One prominent innovation is the concept of the metaverse, which has gained significant popularity and is increasingly influencing various sectors, including the economy, art, entertainment,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Intention, Computer Science Education