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Heinsen Egan, Matthew; McDonald, Chris – Computer Science Education, 2021
Background and Context: Students learning the C programming language struggle to debug, and to understand the runtime behaviour of, their programs. Objective: We examine a tool that combines several novice-focused error detection, program visualization, and debugging techniques, to investigate which features students use in real study sessions,…
Descriptors: Computer Science Education, Programming Languages, Programming, Novices
Manuel T. Rein; Jeroen K. Vermunt; Kim De Roover; Leonie V. D. E. Vogelsmeier – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Researchers often study dynamic processes of latent variables in everyday life, such as the interplay of positive and negative affect over time. An intuitive approach is to first estimate the measurement model of the latent variables, then compute factor scores, and finally use these factor scores as observed scores in vector autoregressive…
Descriptors: Measurement Techniques, Factor Analysis, Scores, Validity
Shmallo, Ronit Shmallo; Shrot, Tammar – Journal of Information Systems Education, 2020
A class diagram is one of the most important diagrams of Unified Modeling Language (UML) and can be used for modeling the static structure of a software system. Learning from errors is a teaching approach based on the assumption that errors can promote learning. We applied a constructive approach of using errors in designing a UML class diagram in…
Descriptors: Programming Languages, Programming, Information Systems, Engineering Education
Guozhu Ding; Xiangyi Shi; Shan Li – Education and Information Technologies, 2024
In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…
Descriptors: Programming, Computer Science Education, Classification, Graphs
Weiss, Charles J. – Biochemistry and Molecular Biology Education, 2022
This article reports a workshop from the 2021 IUBMB/ASBMB Teaching Science with Big Data conference held virtually in June 2021 where participants learned to explore and visualize large quantities of protein PBD data using Jupyter notebooks and the Python programming language. This activity instructs participants using Jupyter notebooks, Python…
Descriptors: Visual Aids, Programming Languages, Data Analysis, Science Instruction
Lijin Zhang; Xueyang Li; Zhiyong Zhang – Grantee Submission, 2023
The thriving developer community has a significant impact on the widespread use of R software. To better understand this community, we conducted a study analyzing all R packages available on CRAN. We identified the most popular topics of R packages by text mining the package descriptions. Additionally, using network centrality measures, we…
Descriptors: Computer Software, Programming Languages, Data Analysis, Visual Aids
Zhanxia Yang; Marina Bers – Computer Science Education, 2024
Background and Context: Historically, women have been underrepresented in computer science. To address this gender gap, researchers advocate for high-quality computer science programs for early childhood. Objectives: This study examines gender differences in coding performance before and after implementing a 24-lesson visual programming curriculum…
Descriptors: Gender Differences, Grade 1, Elementary School Students, Programming
Logachev, Maxim Sergeevich; Laamarti, Yuliya A.; Rudneva, Svetlana Evgenievna; Ekimov, Anisim Ivanovich; Zemlyakov, Dmitry Nikolaevich; Barkov, Alexey – International Journal of Instruction, 2022
The study develops a method for monitoring and management of the quality of educational programs using software instruments. The method describes each of the monitoring implementation stages in detail specifying the input and output data, as well as the controls that affect the time and quality of the implementation of the corresponding stage.…
Descriptors: Information Systems, Educational Quality, Computer Software, Visual Aids
Dayal, Vikram – International Journal of Mathematical Education in Science and Technology, 2023
Epidemiological models have enhanced relevance because of the COVID-19 pandemic. In this note, we emphasize visual tools that can be part of a learning module geared to teaching the SIR epidemiological model, suitable for advanced undergraduates or beginning graduate students in disciplines where the level of prior mathematical knowledge of…
Descriptors: Biology, Visual Aids, Epidemiology, Science Instruction
Langbeheim, Elon – Journal of Chemical Education, 2020
Excluded-volume interactions are ubiquitous to modeling the average size of polymers in solution. This paper shows how simulations can be used by students to explore the emergence of mathematical scaling relations from excluded-volume interactions. Simulations provide robust visual representations of the system, and can be used to investigate a…
Descriptors: Simulation, Plastics, Teaching Methods, Learning Processes
Baosen Zhang; Ariana Frkonja-Kuczin; Zhong-Hui Duan; Aliaksei Boika – Journal of Chemical Education, 2023
Computer vision (CV) is a subfield of artificial intelligence (AI) that trains computers to understand our visual world based on digital images. There are many successful applications of CV including face and hand gesture detection, weather recording, smart farming, and self-driving cars. Recent advances in computer vision with machine learning…
Descriptors: Classification, Laboratory Equipment, Visual Aids, Optics
Ali Alqarni – Journal of Educational Computing Research, 2025
This study examined the effect of gamification on visual programming and computational thinking skills among primary school students, aiming to investigate how gamified learning environments enhance cognitive skill development and conceptual integration compared to traditional teaching methods. A quasi-experimental design was employed, involving…
Descriptors: Thinking Skills, Game Based Learning, Achievement Tests, Teaching Methods
Corlatescu, Dragos-Georgian; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2021
Reading comprehension is key to knowledge acquisition and to reinforcing memory for previous information. While reading, a mental representation is constructed in the reader's mind. The mental model comprises the words in the text, the relations between the words, and inferences linking to concepts in prior knowledge. The automated model of…
Descriptors: Reading Comprehension, Memory, Inferences, Syntax
Enhancement of the Command-Line Environment for Use in the Introductory Statistics Course and Beyond
Gerbing, David W. – Journal of Statistics and Data Science Education, 2021
R and Python are commonly used software languages for data analytics. Using these languages as the course software for the introductory course gives students practical skills for applying statistical concepts to data analysis. However, the reliance upon the command line is perceived by the typical nontechnical introductory student as sufficiently…
Descriptors: Statistics Education, Teaching Methods, Introductory Courses, Programming Languages
Kostousov, Sergei A.; Simonova, Irina V. – International Association for Development of the Information Society, 2019
The purpose of the article is to identify conditions for the effective use of visual modeling tools that can help reduce the difficulty level of solving problems during the teaching high school students programming. Visual modeling tools are a type of software that allows you to create visual abstractions that reproduce concepts and objects of the…
Descriptors: Visual Aids, Models, Problem Solving, Computer Science Education