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Oscar Karnalim; Simon; William Chivers – Computer Science Education, 2024
Background and Context: To educate students about programming plagiarism and collusion, we introduced an approach that automatically reports how similar a submitted program is to others. However, as most students receive similar feedback, those who engage in plagiarism and collusion might feel inadequately warned. Objective: When students are…
Descriptors: Teaching Methods, Plagiarism, Computer Science Education, Programming
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
Dan Sun; Fan Ouyang; Yan Li; Chengcong Zhu; Yang Zhou – Journal of Computer Assisted Learning, 2024
Background: With the development of computational literacy, there has been a surge in both research and practice application of text-based and block-based modalities within the field of computer programming education. Despite this trend, little work has actually examined how learners engaging in programming process when utilizing these two major…
Descriptors: Computer Science Education, Programming, Computer Literacy, Comparative Analysis
Michael C. Robbins; Zhuping Li – Field Methods, 2025
The Nolan Index (NI) is a normed, quantitative measure for comparing the degree of resemblance (similarity or dissimilarity) between free listings with an Excel program for calculating it. This article enhances that effort with the addition of an R program and additional applications. Free-list resemblance measures have been used to investigate…
Descriptors: Computation, Norm Referenced Tests, Comparative Analysis, Spreadsheets
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
Chengliang Wang; Xiaojiao Chen; Yifei Li; Pengju Wang; Haoming Wang; Yuanyuan Li – Journal of Educational Computing Research, 2025
This study explored the impact of MetaClassroom, a virtual immersive programming learning environment designed based on the three-dimensional learning progression (3DLP) concept, on students' multidimensional development. Utilizing a quasi-experimental research design, this study compared students' programming learning achievements (PLA),…
Descriptors: Programming, Computer Science Education, Metacognition, Computer Simulation
Carlos Sandoval-Medina; Carlos Argelio Arévalo-Mercado; Estela Lizbeth Muñoz-Andrade; Jaime Muñoz-Arteaga – Journal of Information Systems Education, 2024
Learning basic programming concepts in computer science-related fields poses a challenge for students, to the extent that it becomes an academic-social problem, resulting in high failure and dropout rates. Proposed solutions to the problem can be found in the literature, such as the development of new programming languages and environments, the…
Descriptors: Cognitive Ability, Computer Science Education, Programming, Instructional Materials
Shi, Yang; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2022
Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…
Descriptors: Programming, Knowledge Level, Prediction, Instructional Innovation
Tan, Teck Kiang – Practical Assessment, Research & Evaluation, 2023
Researchers often have hypotheses concerning the state of affairs in the population from which they sampled their data to compare group means. The classical frequentist approach provides one way of carrying out hypothesis testing using ANOVA to state the null hypothesis that there is no difference in the means and proceed with multiple comparisons…
Descriptors: Comparative Analysis, Hypothesis Testing, Statistical Analysis, Guidelines
Shin, Yoonhee; Song, Donggil – Journal of Educational Computing Research, 2022
This study explores the effect of self-regulated learning support on learners' cognitive load and problem-solving performance, considering cases from well-structured to ill-structured tasks in a computer programing course. Sixty-seven undergraduate students in a computer programing fundamentals course were randomly assigned into one of two groups:…
Descriptors: Cognitive Ability, Computer Science Education, Programming, Problem Solving
W. Paige Hall; Kevin Cantrell – Journal of Chemical Education, 2024
Human-driven carbon emissions have resulted in increased levels of dissolved carbon dioxide in the Earth's oceans. This dissolved carbon dioxide reacts with water to form carbonic acid, which impacts ocean acidity as well as the solubility of carbonate-containing compounds, with far-reaching impacts on marine ecosystems and the human communities…
Descriptors: Programming Languages, Computer Science Education, Chemistry, Marine Biology
Teck Kiang Tan – Practical Assessment, Research & Evaluation, 2024
The procedures of carrying out factorial invariance to validate a construct were well developed to ensure the reliability of the construct that can be used across groups for comparison and analysis, yet mainly restricted to the frequentist approach. This motivates an update to incorporate the growing Bayesian approach for carrying out the Bayesian…
Descriptors: Bayesian Statistics, Factor Analysis, Programming Languages, Reliability
Wang, Jianlan; Zhang, Yuanlin; Jones, Arthur; Eckel, Rory; Hawkins, Joshua; Musslewhite, Darrel – Journal of Computers in Mathematics and Science Teaching, 2022
Despite the importance of computer science education and computational thinking, there have been limited examples of computer science education at K-12 classrooms that authentically represents the work of computer scientists, especially programming. One reason is the lack of a measurable definition of computational thinking and a programming…
Descriptors: Teaching Methods, Computer Science Education, Programming, Thinking Skills
Podworny, Susanne; Hüsing, Sven; Schulte, Carsten – Statistics Education Research Journal, 2022
Data science surrounds us in contexts as diverse as climate change, air pollution, route-finding, genomics, market manipulation, and movie recommendations. To open the "data-science-black-box" for lower secondary school students, we developed a data science teaching unit focusing on the analysis of environmental data, which we embedded…
Descriptors: Statistics Education, Programming, Programming Languages, Data Analysis
Imran, Hazra – Journal of Educational Computing Research, 2023
Adding gaming elements to conventional teaching methodologies has gained a lot of attention because of its ability to incorporate an engaging, motivating, and fun-based environment. As a result, learners' dedication and performance are also better. Unfortunately, current gamification models do not consider the effect of different levels of…
Descriptors: Introductory Courses, Game Based Learning, Learning Motivation, Learner Engagement