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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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Menon, Pratibha – Information Systems Education Journal, 2023
Instruction in an introductory programming course is typically designed to introduce new concepts and to review and integrate the more recent concepts with what was previously learned in the course. Therefore, most exam questions in an introductory programming course require students to write lines of code that contain syntactic elements…
Descriptors: Introductory Courses, Programming Languages, Computer Science Education, Correlation
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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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Gutiérrez, Luz E.; Guerrero, Carlos A.; López-Ospina, Héctor A. – Education and Information Technologies, 2022
This study describes the most relevant problems and solutions found in the literature on teaching and learning of object-oriented programming (OOP). The identification of the problem was based on tertiary studies from the IEEE Xplore, Scopus, ACM Digital Library and Science Direct repositories. The problems and solutions identified were ranked…
Descriptors: Programming, Comprehension, Computer Science Education, Computer Software
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Tahir, Faiza; Mitrovic, Antonija; Sotardi, Valerie – Research and Practice in Technology Enhanced Learning, 2022
The practice of adding game elements to non-gaming educational environments has gained much popularity. Gamification has been shown in some studies to enhance engagement, motivation and learning outcomes in technology-supported learning environments. Although gamification research has matured, there are some shortcomings such as inconsistency in…
Descriptors: Recognition (Achievement), Credentials, Outcomes of Education, Programming Languages
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Qian, Yizhou; Lehman, James – Journal of Research on Technology in Education, 2022
This study investigated common student errors and underlying difficulties of two groups of Chinese middle school students in an introductory Python programming course using data in the automated assessment tool (AAT) Mulberry. One group of students was from a typical middle school while the other group was from a high-ability middle school. By…
Descriptors: Middle School Students, Programming, Computer Science Education, Error Patterns
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Ragonis, Noa; Shmallo, Ronit – Informatics in Education, 2022
Object-oriented programming distinguishes between instance attributes and methods and class attributes and methods, annotated by the "static" modifier. Novices encounter difficulty understanding the means and implications of "static" attributes and methods. The paper has two outcomes: (a) a detailed classification of aspects of…
Descriptors: Programming, Computer Science Education, Concept Formation, Thinking Skills
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