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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
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
Jorge N. Tendeiro; Rink Hoekstra; Tsz Keung Wong; Henk A. L. Kiers – Teaching Statistics: An International Journal for Teachers, 2025
Most researchers receive formal training in frequentist statistics during their undergraduate studies. In particular, hypothesis testing is usually rooted on the null hypothesis significance testing paradigm and its p-value. Null hypothesis Bayesian testing and its so-called Bayes factor are now becoming increasingly popular. Although the Bayes…
Descriptors: Statistics Education, Teaching Methods, Programming Languages, Bayesian Statistics
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
Jérôme Brender; Laila El-Hamamsy; Christian Giang; Laura Mathex; Tanja Käser; Francesco Mondada – Educational Technology Research and Development, 2025
Generalist primary school computer science (CS) teachers are often reluctant to introduce CS activities that go beyond CS unplugged tasks. To address this challenge, we drew from constructive alignment principles to implement a new programming modality for primary school: the handwriting programming language (HPL). HPL brings programming…
Descriptors: Handwriting, Programming Languages, Computer Science Education, Teaching Methods
Austin T. Stroud – Journal of Education for Library and Information Science, 2025
Computer programming languages play a crucial role in the education and training of librarians. This study examines the extent to which ALA-accredited online Master of Library and Information Science (MLIS) programs integrate programming languages into their curricula. Using a mixed-methods approach, data were collected from program websites,…
Descriptors: Masters Programs, Library Education, Online Courses, Programming Languages
Joyce M. W. Moonen-van Loon; Jeroen Donkers – Practical Assessment, Research & Evaluation, 2025
The reliability of assessment tools is critical for accurately monitoring student performance in various educational contexts. When multiple assessments are combined to form an overall evaluation, each assessment serves as a data point contributing to the student's performance within a broader educational framework. Determining composite…
Descriptors: Programming Languages, Reliability, Evaluation Methods, Student Evaluation
Austin Wyman; Zhiyong Zhang – Grantee Submission, 2025
Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion detection programs that are accessible to R programmers: Google Cloud Vision, Amazon Rekognition, and…
Descriptors: Artificial Intelligence, Algorithms, Computer Software, Identification
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
Suppanut Sriutaisuk; Yu Liu; Seungwon Chung; Hanjoe Kim; Fei Gu – Educational and Psychological Measurement, 2025
The multiple imputation two-stage (MI2S) approach holds promise for evaluating the model fit of structural equation models for ordinal variables with multiply imputed data. However, previous studies only examined the performance of MI2S-based residual-based test statistics. This study extends previous research by examining the performance of two…
Descriptors: Structural Equation Models, Error of Measurement, Programming Languages, Goodness of Fit
Andrea Maffia; Carola Manolino; Elisa Miragliotta – Educational Studies in Mathematics, 2025
Research literature about visually impaired students' approach to mathematics is still very scarce, especially in the case of algebra, even though mathematical content is becoming increasingly accessible thanks to assistive technologies. This paper presents a case study aimed at describing a blind subject's process of algebraic symbol manipulation…
Descriptors: Algebra, Blindness, Mathematics Education, Symbols (Mathematics)
Amedeo Pachera; Stefania Dumbrava; Angela Bonifati; Andrea Mauri – ACM Transactions on Computing Education, 2025
Query languages are the foundations of database teaching and education practices. The broad adoption of graph databases contrasts with the limited research into how they are taught. Contrary to relational databases, graph databases allow navigational queries with higher expressivity and lack an a priori schema. In this article, we design a…
Descriptors: Error Patterns, Graphs, Programming Languages, Databases
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
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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