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Showing 1 to 15 of 41 results Save | Export
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Afeez Jinadu; Eugenia Okwilagwe – International Journal of Research in Education and Science, 2025
The study investigated the structural equation modelling of nine variables consisting of research undertaking, digi-tech construct (digital nativity, category of adoption of digital technologies, digital literacy, digital citizenship, statistical software anxiety, self-efficacy and knowledge) and researcher statistical software skills in the…
Descriptors: Statistical Analysis, Computer Software, Structural Equation Models, Foreign Countries
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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
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Ken Frank; Guan Saw; Qinyun Lin; Ran Xu; Joshua Rosenberg; Spiro Maroulis; Bret Staudt Willet – Grantee Submission, 2025
This is a practical guide for applying the Impact Threshold for a Confounding Variable and the Robustness of Inference to Replacement using the konfound packages in Stata and R as well as the R-shiny app. It includes motivation worked examples, and tutorials.
Descriptors: Robustness (Statistics), Statistical Inference, Programming Languages, Computer Software
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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
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Harikesh Singh; Li-Minn Ang; Dipak Paudyal; Mauricio Acuna; Prashant Kumar Srivastava; Sanjeev Kumar Srivastava – Technology, Knowledge and Learning, 2025
Wildfires pose significant environmental threats in Australia, impacting ecosystems, human lives, and property. This review article provides a comprehensive analysis of various empirical and dynamic wildfire simulators alongside machine learning (ML) techniques employed for wildfire prediction in Australia. The study examines the effectiveness of…
Descriptors: Artificial Intelligence, Computer Software, Computer Simulation, Prediction
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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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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
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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
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Gerit Wagner; Laureen Thurner – Journal of Information Systems Education, 2025
Git, as the leading version-control system, is frequently employed by software developers, digital product managers, and knowledge workers. Information systems (IS) students aspiring to fill software engineering, management, or research positions would therefore benefit from familiarity with Git. However, teaching Git effectively can be…
Descriptors: Computer Science Education, Information Systems, Teaching Methods, Computer Software
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Takafumi Tomura – Strategies: A Journal for Physical and Sport Educators, 2025
Communication with immigrant parents is becoming a challenge for teachers due to cultural, social, and linguistic differences as a result of globalization and the growing diversity in many schools. Especially in physical education (PE), miscommunication between teachers and parents may lead to educational disadvantages or health risks for…
Descriptors: Immigrants, Parent Teacher Cooperation, Physical Education Teachers, Cultural Influences
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Mahadi Hasan Miraz; Sanmugam Annamalah; Rohana Sham – Educational Process: International Journal, 2025
Background/purpose: It revisits Partial Least Squares Structural Equation Modeling (PLS-SEM) as a robust tool for analyzing non-normal data and small samples, offering predictive modeling advantages. This study also compares the merits, practical applications, and added value of both tools in tackling complicated research issues, notably in…
Descriptors: Evaluation Methods, Educational Research, Structural Equation Models, Data Analysis
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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
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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
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Xinyu Li; Yizhou Fan; Tongguang Li; Mladen Rakovic; Shaveen Singh; Joep van der Graaf; Lyn Lim; Johanna Moore; Inge Molenaar; Maria Bannert; Dragan Gaševic – Journal of Learning Analytics, 2025
The focus of education is increasingly on learners' ability to regulate their own learning within technology-enhanced learning environments. Prior research has shown that self-regulated learning (SRL) leads to better learning performance. However, many learners struggle to productively self-regulate their learning, as they typically need to…
Descriptors: Learning Analytics, Metacognition, Independent Study, Skill Development
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Ashish Gurung; Jionghao Lin; Zhongtian Huang; Conrad Borchers; Ryan S. Baker; Vincent Aleven; Kenneth R. Koedinger – International Educational Data Mining Society, 2025
Prior work has developed a range of automated measures ("detectors") of student self-regulation and engagement from student log data. These measures have been successfully used to make discoveries about student learning. Here, we extend this line of research to an underexplored aspect of self-regulation: students' decisions about when to…
Descriptors: Decision Making, Computer Software, Tutoring, Electronic Learning
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