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Pakiso J. Khomokhoana; Rouxan C. Fouché; Tlholohelo S. Nkalai – Discover Education, 2025
Unified Modelling Language (UML) class diagrams are standard tools in software engineering education, typically analysed for syntactical correctness rather than their communicative dimensions. This study applies semiotic theory to investigate how first-year Bachelor of Computer Information Systems students engage with UML class diagrams as…
Descriptors: Semiotics, Programming Languages, Computer Software, Information Systems
Niloofar Mansoor; Cole S. Peterson; Michael D. Dodd; Bonita Sharif – ACM Transactions on Computing Education, 2024
Background and Context: Understanding how a student programmer solves different task types in different programming languages is essential to understanding how we can further improve teaching tools to support students to be industry-ready when they graduate. It also provides insight into students' thought processes in different task types and…
Descriptors: Biofeedback, Eye Movements, Computer Science Education, Programming Languages
Pere J. Ferrando; Ana Hernández-Dorado; Urbano Lorenzo-Seva – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A frequent criticism of exploratory factor analysis (EFA) is that it does not allow correlated residuals to be modelled, while they can be routinely specified in the confirmatory (CFA) model. In this article, we propose an EFA approach in which both the common factor solution and the residual matrix are unrestricted (i.e., the correlated residuals…
Descriptors: Correlation, Factor Analysis, Models, Goodness of Fit
Xiao Liu; Zhiyong Zhang; Lijuan Wang – Grantee Submission, 2024
In psychology, researchers are often interested in testing hypotheses about mediation, such as testing the presence of a mediation effect of a treatment (e.g., intervention assignment) on an outcome via a mediator. An increasingly popular approach to testing hypotheses is the Bayesian testing approach with Bayes factors (BFs). Despite the growing…
Descriptors: Sample Size, Bayesian Statistics, Programming Languages, Simulation
Mehmet Arif Demirta¸; Max Fowler; Kathryn Cunningham – International Educational Data Mining Society, 2024
Analyzing which skills students develop in introductory programming education is an important question for the computer science education community. These key skills and concepts have been formalized as knowledge components, which are units of knowledge that can be measured by performance on a set of tasks. While knowledge components in other…
Descriptors: Programming, Computer Science Education, Skill Development, Knowledge Level
Nie, Rui; Guo, Qi; Morin, Maxim – Educational Measurement: Issues and Practice, 2023
The COVID-19 pandemic has accelerated the digitalization of assessment, creating new challenges for measurement professionals, including big data management, test security, and analyzing new validity evidence. In response to these challenges, "Machine Learning" (ML) emerges as an increasingly important skill in the toolbox of measurement…
Descriptors: Artificial Intelligence, Electronic Learning, Literacy, Educational Assessment
Rong, Wenge; Xu, Tianfan; Sun, Zhiwei; Sun, Zian; Ouyang, Yuanxin; Xiong, Zhang – IEEE Transactions on Education, 2023
Contribution: In this study, an object tuple model has been proposed, and a quasi-experimental study on its usage in an introductory programming language course has been reported. This work can be adopted by all C language teachers and students in learning pointer and array-related concepts. Background: C language has been extensively employed in…
Descriptors: Models, Introductory Courses, Programming, Computer Science Education
Muradoglu, Melis; Cimpian, Joseph R.; Cimpian, Andrei – Journal of Cognition and Development, 2023
Mixed-effects models are an analytic technique for modeling repeated measurement or nested data. This paper explains the logic of mixed-effects modeling and describes two examples of mixed-effects analyses using R. The intended audience of the paper is psychologists who specialize in cognitive development research. Therefore, the concepts and…
Descriptors: Cognitive Development, Models, Programming Languages, Psychologists
Diamond, Harvey – PRIMUS, 2023
This paper presents a series of basic computational problems that are mathematically and/or graphically appealing, and provides an idea of places one might go in trying to understand what is happening, integrating mathematics, computation, and graphics. The real point of this paper is to make a case, through those examples, for computation as an…
Descriptors: Mathematics Instruction, Computation, College Mathematics, Undergraduate Study
Hagge, Julia – Literacy Research: Theory, Method, and Practice, 2023
Although participatory culture promotes productive engagement in online spaces, members may respond in ways that constrain digital composition practices. This article provides theoretical and contextual background regarding a shift toward digital media production and programming-as-writing for youth. In addition, I describe the intersecting of…
Descriptors: Productivity, Sustainability, Participation, Digital Literacy
Demir, Faruk – Education and Information Technologies, 2022
The abstract structure, logic, negative perceptions, and anxiety of programming are seen as obstacles to novice programmers. The importance of educational programming languages is increasing day by day in overcoming these obstacles. In this study, it was aimed to investigate the effect of educational programming language integration on academic…
Descriptors: Programming, Computer Science Education, Anxiety, Academic Achievement
Craig, Paul A.; Nash, Jessica A.; Crawford, T. Daniel – Biochemistry and Molecular Biology Education, 2022
A programming workshop has been developed for biochemists and molecular biologists to introduce them to the power and flexibility of solving problems with Python. The workshop is designed to move users beyond a "plug-and-play" approach that is based on spreadsheets and web applications in their teaching and research to writing scripts to…
Descriptors: Programming Languages, Biochemistry, Molecular Biology, Data Analysis
Representing DNA for Machine Learning Algorithms: A Primer on One-Hot, Binary, and Integer Encodings
Yash Munnalal Gupta; Satwika Nindya Kirana; Somjit Homchan – Biochemistry and Molecular Biology Education, 2025
This short paper presents an educational approach to teaching three popular methods for encoding DNA sequences: one-hot encoding, binary encoding, and integer encoding. Aimed at bioinformatics and computational biology students, our learning intervention focuses on developing practical skills in implementing these essential techniques for…
Descriptors: Science Instruction, Teaching Methods, Genetics, Molecular Biology
Ethan C. Brown; Mohammed A. A. Abulela – Practical Assessment, Research & Evaluation, 2025
Moderated multiple regression (MMR) has become a fundamental tool for applied researchers, since many effects are expected to vary based on other variables. However, the inherent complexity of MMR creates formidable challenges for adequately performing power analysis on interaction effects to ensure reliable and replicable research results. Prior…
Descriptors: Statistical Analysis, Multiple Regression Analysis, Models, Programming Languages
Christina Glasauer; Martin K. Yeh; Lois Anne DeLong; Yu Yan; Yanyan Zhuang – Computer Science Education, 2025
Background and Context: Feedback on one's progress is essential to new programming language learners, particularly in out-of-classroom settings. Though many study materials offer assessment mechanisms, most do not examine the accuracy of the feedback they deliver, nor give evidence on its validity. Objective: We investigate the potential use of a…
Descriptors: Novices, Computer Science Education, Programming, Accuracy

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