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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
Maya B. Mathur – Research Synthesis Methods, 2024
Meta-analyses can be compromised by studies' internal biases (e.g., confounding in nonrandomized studies) as well as publication bias. These biases often operate nonadditively: publication bias that favors significant, positive results selects indirectly for studies with more internal bias. We propose sensitivity analyses that address two…
Descriptors: Meta Analysis, Attribution Theory, Publications, Bias
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
Michael C. Robbins; Zhuping Li – Field Methods, 2025
The Nolan Index (NI) is a normed, quantitative measure for comparing the degree of resemblance (similarity or dissimilarity) between free listings with an Excel program for calculating it. This article enhances that effort with the addition of an R program and additional applications. Free-list resemblance measures have been used to investigate…
Descriptors: Computation, Norm Referenced Tests, Comparative Analysis, Spreadsheets
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
Rubén Buitrago; Jesús Salinas; Oscar Boude – Knowledge Management & E-Learning, 2024
Design patterns for learning are about articulating, testing and sharing the principles of problem solving in the educational context. In this way, multiple patterns are developed to solve common problems, described in various pattern language formats. Therefore, this work is about characterizing and establishing functional relationships between…
Descriptors: Delphi Technique, Programming Languages, Programming, Computer Software
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
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
David Shilane; Nicole Di Crecchio; Nicole L. Lorenzetti – Teaching Statistics: An International Journal for Teachers, 2024
Educational curricula in data analysis are increasingly fundamental to statistics, data science, and a wide range of disciplines. The educational literature comparing coding syntaxes for instruction in data analysis recommends utilizing a simple syntax for introductory coursework. However, there is limited prior work to assess the pedagogical…
Descriptors: Programming, Data Science, Programming Languages, Coding
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
Davi Bernardo Silva; Deborah Ribeiro Carvalho; Carlos N. Silla – IEEE Transactions on Learning Technologies, 2024
Throughout a programming course, students develop various source code tasks. Using these tasks to track students' progress can provide clues to the strengths and weaknesses found in each learning topic. This practice allows the teacher to intervene in learning in the first few weeks of class and maximize student gains. However, the biggest…
Descriptors: Computation, Models, Ability Grouping, Programming
Alex Yue Feng Zhu – British Journal of Educational Technology, 2024
Research has shown that even though standardized financial education has gained prevalence to promote financial literacy over the past decade, it has had little effect on personal financial planning. The present study used a randomized control trial to examine the effectiveness of a Python-based personalized financial projection on young working…
Descriptors: Financial Education, Programming Languages, Financial Literacy, Money Management
Lucy D'Agostino McGowan; Travis Gerke; Malcolm Barrett – Journal of Statistics and Data Science Education, 2024
This article introduces a collection of four datasets, similar to Anscombe's quartet, that aim to highlight the challenges involved when estimating causal effects. Each of the four datasets is generated based on a distinct causal mechanism: the first involves a collider, the second involves a confounder, the third involves a mediator, and the…
Descriptors: Statistics Education, Programming Languages, Statistical Inference, Causal Models

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