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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
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
Walter Gander – Informatics in Education, 2024
When the new programming language Pascal was developed in the 1970's, Walter Gander did not like it because because many features which he appreciated in prior programming languages were missing in Pascal. For example the block structure was gone, there were no dynamical arrays, no functions or procedures were allowed as parameters of a procedure,…
Descriptors: Computer Software, Programming Languages, Algorithms, Automation
Kevin Sigayret; Nathalie Blanc; André Tricot – Journal of Computer Assisted Learning, 2025
Background: Teaching programming and computational thinking is becoming a major issue in many education systems. Numerous approaches are possible, but very few studies compare these different ways of implementing programming and computational thinking learning. Objectives: We compared three ways of teaching programming and computational thinking…
Descriptors: Educational Technology, Technology Uses in Education, Robotics, Computation
Guangrui Fan; Dandan Liu; Rui Zhang; Lihu Pan – International Journal of STEM Education, 2025
Purpose: This study investigates the impact of AI-assisted pair programming on undergraduate students' intrinsic motivation, programming anxiety, and performance, relative to both human-human pair programming and individual programming approaches. Methods: A quasi-experimental design was conducted over two academic years (2023-2024) with 234…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Programming
Rosziati Ibrahim; Mizani Mohamad Madon; Zhiang Yue Lee; Piraviendran A/L Rajendran; Jahari Abdul Wahab; Faaizah Shahbodin – International Society for Technology, Education, and Science, 2023
This paper discusses the steps involve in project development for developing the mobile application, namely Blood Bank Application and developing the convertor for software testing. The project development is important for Computer Science students for them to learn the important steps in developing the application and testing the reliability of…
Descriptors: Program Administration, Educational Technology, Computer Software, Testing
Dilmen, Kaan; Kert, Serhat Bahadir; Ugras, Tuba – Education and Information Technologies, 2023
Programming education is an important educational process that enables the development of children's problem solving and algorithmic thinking skills. It is known that children frequently encounter syntax problems in coding activities. Many block-based programming software has been developed to eliminate this difficulty in the learning process.…
Descriptors: Children, Adolescents, Coding, Programming Languages
Peer reviewedPriti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2023
This paper systematically explores how Large Language Models (LLMs) generate explanations of code examples of the type used in intro-to-programming courses. As we show, the nature of code explanations generated by LLMs varies considerably based on the wording of the prompt, the target code examples being explained, the programming language, the…
Descriptors: Computational Linguistics, Programming, Computer Science Education, Programming Languages
Kristina Litherland; Anders Kluge – Computer Science Education, 2024
Background and Context: We explore the potential for understanding the processes involved in students' programming based on studying their behaviour and dialogue with each other and "conversations" with their programs. Objective: Our aim is to explore how a perspective of inquiry can be used as a point of departure for insights into how…
Descriptors: Programming, Programming Languages, Secondary School Students, Computer Science Education
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
Yong Li – ProQuest LLC, 2024
Geometry processing holds a foundational position within the realm of computer graphics, with advancements in this field regularly published at SIGGRAPH annually. The journey from writing the paper to implementing the algorithms is a meticulous and error-prone process, demanding significant dedication and attention to detail. Authors frequently…
Descriptors: Geometry, Mathematics Instruction, Programming Languages, Computer Software
Muhammad Fawad Akbar Khan; Max Ramsdell; Erik Falor; Hamid Karimi – International Educational Data Mining Society, 2024
This paper undertakes a thorough evaluation of ChatGPT's code generation capabilities, contrasting them with those of human programmers from both educational and software engineering standpoints. The emphasis is placed on elucidating its importance in these intertwined domains. To facilitate a robust analysis, we curated a novel dataset comprising…
Descriptors: Artificial Intelligence, Automation, Computer Science Education, Programming
Daniele Traversaro; Giorgio Delzanno; Giovanna Guerrini – Informatics in Education, 2024
Concurrency is a complex to learn topic that is becoming more and more relevant, such that many undergraduate Computer Science curricula are introducing it in introductory programming courses. This paper investigates the combined use of Sonic Pi and Team-Based Learning to mitigate the difficulties in early exposure to concurrency. Sonic Pi, a…
Descriptors: Misconceptions, Programming Languages, Computer Science Education, Undergraduate Students
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
Peer reviewedKen 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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