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Germia, Erell; Panorkou, Nicole – Mathematics Teacher: Learning and Teaching PK-12, 2020
We present a Scratch task we designed and implemented for teaching and learning coordinates in a dynamic and engaging way. We use the 5Es framework to describe the students' interactions with the task and offer suggestions of how other teachers may adopt it to successfully implement Scratch tasks.
Descriptors: Programming, Mathematical Concepts, Mathematics Instruction, Programming Languages
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Wolthuis, Stuart L.; Slade, Christopher – Information Systems Education Journal, 2020
In this research project we describe the legacy software landscape, its current state, and challenges associated with aging information systems and access to its data. We briefly describe the popularity of dynamic languages and how a specific dynamic programming language, Ruby on Rails (RoR or Rails), is used to create a system to extract data…
Descriptors: Computer Software, Data Use, Programming Languages, Information Systems
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Fávero, Luiz Paulo; Souza, Rafael de Freitas; Belfiore, Patrícia; Corrêa, Hamilton Luiz; Haddad, Michel F. C. – Practical Assessment, Research & Evaluation, 2021
In this paper is proposed a straightforward model selection approach that indicates the most suitable count regression model based on relevant data characteristics. The proposed selection approach includes four of the most popular count regression models (i.e. Poisson, negative binomial, and respective zero-inflated frameworks). Moreover, it…
Descriptors: Regression (Statistics), Selection, Statistical Analysis, Models
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Sanosi, Abdulaziz; Abdalla, Mohamed – Australian Journal of Applied Linguistics, 2021
This study aimed to examine the potentials of the NLP approach in detecting discourse markers (DMs), namely okay, in transcribed spoken data. One hundred thirty-eight concordance lines were presented to human referees to judge the functions of okay in them as a DM or Non-DM. After that, the researchers used a Python script written according to the…
Descriptors: Natural Language Processing, Computational Linguistics, Programming Languages, Accuracy
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Mirolo, Claudio; Izu, Cruz; Lonati, Violetta; Scapin, Emanuele – Informatics in Education, 2021
When we "think like a computer scientist," we are able to systematically solve problems in different fields, create software applications that support various needs, and design artefacts that model complex systems. Abstraction is a soft skill embedded in all those endeavours, being a main cornerstone of computational thinking. Our…
Descriptors: Computer Science Education, Soft Skills, Thinking Skills, Abstract Reasoning
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Strömbäck, Filip; Mannila, Linda; Kamkar, Mariam – Informatics in Education, 2021
Concurrency is often perceived as difficult by students. One reason for this may be due to the fact that abstractions used in concurrent programs leave more situations undefined compared to sequential programs (e.g., in what order statements are executed), which makes it harder to create a proper mental model of the execution environment. Students…
Descriptors: College Students, Programming, Programming Languages, Concept Formation
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Custer, Gordon F.; van Diepen, Linda T. A.; Seeley, Janel – Natural Sciences Education, 2021
Quantitative literacy is necessary to keep pace with the exponentially increasing magnitude of biological data and the complexity of statistical tools. However, statistical programming can cause anxiety in new learners and educators alike. In order to produce graduates that are well-prepared for quantitative research, overcoming the initial…
Descriptors: Programming Languages, Computer Science Education, Student Attitudes, Time Management
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Obeidat, Raghad; Alzoubi, Hussein – International Journal of Information and Communication Technology Education, 2021
Curricula in computer engineering, computer science, and other related fields include several courses about hardware design. Examples of these courses are digital logic design, computer architecture, microprocessors, computer interfacing, hardware design, embedded systems, switching theorem, and others. In order for the students to realize the…
Descriptors: Programming Languages, Computer Science Education, Concept Formation, Engineering Education
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Kim, Brian; Henke, Graham – Journal of Statistics and Data Science Education, 2021
One of the biggest hurdles of teaching data science and programming techniques to beginners is simply getting started with the technology. With multiple versions of the same coding language available (e.g., Python 2 and Python 3), various additional libraries and packages to install, as well as integrated development environments to navigate, the…
Descriptors: Computer Software, Data Analysis, Programming Languages, Computer Science Education
Merkle, Edgar C.; Fitzsimmons, Ellen; Uanhoro, James; Goodrich, Ben – Grantee Submission, 2021
Structural equation models comprise a large class of popular statistical models, including factor analysis models, certain mixed models, and extensions thereof. Model estimation is complicated by the fact that we typically have multiple interdependent response variables and multiple latent variables (which may also be called random effects or…
Descriptors: Bayesian Statistics, Structural Equation Models, Psychometrics, Factor Analysis
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Yang, Fan; Akanbi, Temitope; Chong, Oscar Wong; Zhang, Jiansong; Debs, Luciana; Chen, Yunfeng; Hubbard, Bryan J. – Journal of Civil Engineering Education, 2024
Computing technology is reshaping the way in which professionals in the architecture, engineering, and construction industries conduct their business. The execution of construction tasks is changing from traditional 2D to 3D building information modeling (BIM)-based concepts. The use of BIM is expanded and enriched by the introduction of advanced…
Descriptors: Civil Engineering, Engineering Education, Programming Languages, Construction Management
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Leonardo D. Garma; Nuno S. Osório – Biochemistry and Molecular Biology Education, 2024
Dimensionality reduction techniques are essential in analyzing large 'omics' datasets in biochemistry and molecular biology. Principal component analysis, t-distributed stochastic neighbor embedding, and uniform manifold approximation and projection are commonly used for data visualization. However, these methods can be challenging for students…
Descriptors: Biochemistry, Molecular Biology, Science Instruction, Learning Experience
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Sanal Kumar T. S.; R. Thandeeswaran – Education and Information Technologies, 2024
The COVID-19 pandemic has forced a significant increase in the utilization of video-based e-learning platforms for programming education. These platforms never considered the essential attributes of student characteristics and learning preferences while designing such a problematic subject having high dropout and failure rates. The traditional…
Descriptors: Blended Learning, Electronic Learning, Higher Education, Programming
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Maertens, Rien; Van Petegem, Charlotte; Strijbol, Niko; Baeyens, Toon; Jacobs, Arne Carla; Dawyndt, Peter; Mesuere, Bart – Journal of Computer Assisted Learning, 2022
Background: Learning to code is increasingly embedded in secondary and higher education curricula, where solving programming exercises plays an important role in the learning process and in formative and summative assessment. Unfortunately, students admit that copying code from each other is a common practice and teachers indicate they rarely use…
Descriptors: Plagiarism, Benchmarking, Coding, Computer Science Education
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Cuervo-Cely, Karen D.; Restrepo-Calle, Felipe; Ramírez-Echeverry, Jhon J. – Journal of Information Technology Education: Research, 2022
Aim/Purpose: The purpose of this research is to examine the effect of computer-assisted gamification on the learning motivation of computer programming students. Background: The teaching-learning of computer programming involves challenges that imply using learning environments in which the student is actively involved. Gamification is an…
Descriptors: Game Based Learning, Student Motivation, Computer Science Education, Programming
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