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Acar, Tülin – International Journal of Assessment Tools in Education, 2019
The purpose of this study was to write programs to define sampling sizes and observation units by probability sampling methods and to provide an idea for software developers. The algorithms of the programs were written in Python 3. The programs may be run by double-clicking on the Windows operating system or by the command prompt of the DOS…
Descriptors: Sample Size, Computer Software, Probability, Statistical Analysis
Felienne Hermans – Informatics in Education, 2024
This autoethnographic paper is part of a special issue trying to answer the question "How to design or choose languages for programming novices?" I will describe how my programming language Hedy was created, how the initial design goals were formed, how my perspectives on learning and teaching changed along the way, and how Hedy changed…
Descriptors: Decision Making, Programming Languages, Novices, Computer Science Education
Kumar, Amruth N. – International Educational Data Mining Society, 2023
Is there a pattern in how students solve Parsons puzzles? Is there a difference between the puzzle-solving strategies of C++ and Java students? We used Markov transition matrix to answer these questions. We analyzed the solutions of introductory programming students solving Parsons puzzles involving if-else statements and while loops in C++ and…
Descriptors: Markov Processes, Puzzles, Introductory Courses, Computer Science Education
Grajdura, Sarah; Niemeier, Deb – Journal of Civil Engineering Education, 2023
Addressing societal issues in civil and environmental engineering increasingly requires skills in data science and programming. To date, there is not much known about the extent students are learning these skills in current civil and environmental engineering curricula. We conducted a survey of accredited civil and environmental engineering…
Descriptors: Civil Engineering, Engineering Education, Social Problems, Programming Languages
Soltys, Michael; Dang, Hung D.; Reyes Reilly, Ginger; Soltys, Katharine – Strategic Enrollment Management Quarterly, 2021
A Machine Learning framework for predicting enrollment is proposed. The framework consists of Amazon Web Services SageMaker together with standard Python tools for data analytics, including Pandas, NumPy, MatPlotLib, and ScikitLearn. The tools are deployed with Jupyter Notebooks running on AWS SageMaker. Based on three years of enrollment history,…
Descriptors: Enrollment Management, Strategic Planning, Prediction, Computer Software
Metcalf, Shari J.; Reilly, Joseph M.; Jeon, Soobin; Wang, Annie; Pyers, Allyson; Brennan, Karen; Dede, Chris – Computer Science Education, 2021
Background and Context: This study looks at computational thinking (CT) assessment of programming artifacts within the context of CT integrated with science education through computational modeling. Objective: The goal is to explore methodologies for assessment of student-constructed computational models through two lenses: functionality and…
Descriptors: Evaluation Methods, Computation, Thinking Skills, Science Education
Krajcsi, Attila; Csapodi, Csaba; Stettner, Eleonóra – Interactive Learning Environments, 2021
An educational computer game is presented, used for beginner students to introduce some basic concepts of code execution and code writing. In this mini-language microworld game, a code should be written with which a robot can escape from a procedurally generated labyrinth. The game uses a simple language and utilizes a virtual environment, where…
Descriptors: Educational Games, Computer Games, Programming, Computer Science Education
Thomas, Paul JoseKutty – ProQuest LLC, 2021
Software modeling is an integral practice for software engineers especially as the complexity of software solutions increase. There is precedent in industry to model information systems in terms of functions, structures, and behaviors. While constructing these models, abstraction and systems thinking are employed to determine elements essential to…
Descriptors: Computer Science Education, Programming Languages, Academic Achievement, College Students
Jordan, Greg Madison – ProQuest LLC, 2022
Software has become central to every part of modern life and supports everything from managing personal schedules to managing global supply chain systems. In creating new or updating existing software, software developers often need to incorporate new technology. When software developers learn new technology using tutorials, their experience with…
Descriptors: Computer Software, Prior Learning, Technological Literacy, Networks
Hajar Darif; Mohammed Amine Lafraxo – Educational Process: International Journal, 2025
Background/purpose: The emergence of educational technologies has profoundly transformed teaching and learning methods in health sciences. This bibliometric study aims to identify the most widely used educational practices in this field between 2014 and 2024, exploring their applications within a constantly evolving technological context.…
Descriptors: Programming Languages, Bibliometrics, Research Reports, Educational Technology
Price, Thomas W.; Dong, Yihuan; Zhi, Rui; Paaßen, Benjamin; Lytle, Nicholas; Cateté, Veronica; Barnes, Tiffany – International Journal of Artificial Intelligence in Education, 2019
In the domain of programming, a growing number of algorithms automatically generate data-driven, next-step hints that suggest how students should edit their code to resolve errors and make progress. While these hints have the potential to improve learning if done well, few evaluations have directly assessed or compared the quality of different…
Descriptors: Comparative Analysis, Programming Languages, Data Analysis, Evaluation Methods
Erdem-Kara, Basak – International Journal of Assessment Tools in Education, 2019
Computer adaptive testing is an important research field in educational measurement, and simulation studies play a critically important role in CAT development and evaluation. Both Monte Carlo and Post Hoc simulations are frequently used in CAT studies in order to investigate the effects of different factors on test efficiency and to compare…
Descriptors: Computer Assisted Testing, Adaptive Testing, Programming Languages, Monte Carlo Methods
Phung, Tung; Cambronero, José; Gulwani, Sumit; Kohn, Tobias; Majumdarm, Rupak; Singla, Adish; Soares, Gustavo – International Educational Data Mining Society, 2023
Large language models (LLMs), such as Codex, hold great promise in enhancing programming education by automatically generating feedback for students. We investigate using LLMs to generate feedback for fixing syntax errors in Python programs, a key scenario in introductory programming. More concretely, given a student's buggy program, our goal is…
Descriptors: Computational Linguistics, Feedback (Response), Programming, Computer Science Education
Holman, Justin O.; Hacherl, Allie – Journal of Statistics and Data Science Education, 2023
It has become increasingly important for future business professionals to understand statistical computing methods as data science has gained widespread use in contemporary organizational decision processes in recent years. Used by scores of academics and practitioners in a variety of fields, Monte Carlo simulation is one of the most broadly…
Descriptors: Teaching Methods, Monte Carlo Methods, Programming Languages, Statistics Education
Saatcioglu, Fatima Munevver; Atar, Hakan Yavuz – International Journal of Assessment Tools in Education, 2022
This study aims to examine the effects of mixture item response theory (IRT) models on item parameter estimation and classification accuracy under different conditions. The manipulated variables of the simulation study are set as mixture IRT models (Rasch, 2PL, 3PL); sample size (600, 1000); the number of items (10, 30); the number of latent…
Descriptors: Accuracy, Classification, Item Response Theory, Programming Languages