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Kane Meissel; Esther S. Yao – Practical Assessment, Research & Evaluation, 2024
Effect sizes are important because they are an accessible way to indicate the practical importance of observed associations or differences. Standardized mean difference (SMD) effect sizes, such as Cohen's d, are widely used in education and the social sciences -- in part because they are relatively easy to calculate. However, SMD effect sizes…
Descriptors: Computer Software, Programming Languages, Effect Size, Correlation
Muhammed Murat Gümüs; Volkan Kukul; Özgen Korkmaz – Informatics in Education, 2024
This study aims to explain the relationships between secondary school students' digital literacy, computer programming self-efficacy and computational thinking self-efficacy. The study group consists of 204 secondary school students. A relational survey model was used in the research method and three different data collection tools were used to…
Descriptors: Correlation, Middle School Students, Thinking Skills, Digital Literacy
Tianxiao Yang; Jongpil Cheon – Computer Science Education, 2025
Background and context: There were few studies indicating if students' computational thinking (CT) self-efficacy and their CT performance were aligned with each other. Objectives: The study was to investigate if there was a discrepancy between students' CT self-efficacy and their CT performance. Method: Involving 104 non-CS undergraduate students…
Descriptors: Self Efficacy, Computer Science Education, Prediction, Teacher Expectations of Students
Sirazum Munira Tisha – ProQuest LLC, 2023
Most existing autograders used for grading programming assignments are based on unit testing, which is tedious to implement for programs with graphical output and does not allow testing for other code aspects, such as programming style or structure. We present a novel autograding approach based on machine learning that can successfully check the…
Descriptors: Computer Software, Grading, Programming, Assignments
Václav Dobiáš; Václav Šimandl; Jirí Vanícek – Informatics in Education, 2024
The paper discusses an alternative method of assessing the difficulty of pupils' programming tasks to determine their age appropriateness. Building a program takes the form of its successive iterations. Thus, it is possible to monitor the number of times such a program was built by the solver. The variance of the number of program builds can be…
Descriptors: Difficulty Level, Computer Science Education, Programming, Task Analysis
McCall, Davin; Kölling, Michael – ACM Transactions on Computing Education, 2019
The types of programming errors that novice programmers make and struggle to resolve have long been of interest to researchers. Various past studies have analyzed the frequency of compiler diagnostic messages. This information, however, does not have a direct correlation to the types of errors students make, due to the inaccuracy and imprecision…
Descriptors: Computer Software, Programming, Error Patterns, Novices
Iskrenovic-Momcilovic, Olivera – Education and Information Technologies, 2019
This paper examines the effectiveness of programming in pairs in the Scratch environment in primary school. The motivation for tackling this issue is based on the successful use of Scratch as a learning environment for any students of programming. The analysis has shown that that programming in pairs produces better results for beginners in…
Descriptors: Programming, Instructional Effectiveness, Teaching Methods, Cooperative Learning
Shaheen, Muhammad – Interactive Learning Environments, 2023
Outcome-based education (OBE) is uniquely adapted by most of the educators across the world for objective processing, evaluation and assessment of computing programs and its students. However, the extraction of knowledge from OBE in common is a challenging task because of the scattered nature of the data obtained through Program Educational…
Descriptors: Undergraduate Students, Programming, Computer Science Education, Educational Objectives
Tahereh Firoozi; Okan Bulut; Mark J. Gierl – International Journal of Assessment Tools in Education, 2023
The proliferation of large language models represents a paradigm shift in the landscape of automated essay scoring (AES) systems, fundamentally elevating their accuracy and efficacy. This study presents an extensive examination of large language models, with a particular emphasis on the transformative influence of transformer-based models, such as…
Descriptors: Turkish, Writing Evaluation, Essays, Accuracy
M. V. Lubarda; A. M. Phan; C. Schurgers; N. Delson; M. Ghazinejad; S. Baghdadchi; M. Minnes; M. Kim; C. Pilegard; J. Relaford-Doyle; C. L. Sandoval; H. Qi – Computer Science Education, 2025
Background and context: Pair programming and oral exams were deployed in tandem in a remote undergraduate computer programming course to promote social interaction and enhance learning. Objectives: We investigate their impact on social interactions, sense of connection, academic performance, and academic integrity within a virtual learning…
Descriptors: Distance Education, Undergraduate Students, Integrity, Computer Science 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
Bråting, Kajsa; Kilhamn, Cecilia – Scandinavian Journal of Educational Research, 2022
We characterize the recently included programming content in Swedish mathematics textbooks for elementary school. Especially, the connection between programming content and traditional mathematical content has been considered. The analytical tools used are based on the so-called 5E's, a theoretical framework of action, developed within the…
Descriptors: Foreign Countries, Programming, Computer Science Education, Mathematics Instruction
Hof, Barbara – History of Education, 2021
Drawing on historical epistemology and considerations on the function of scientific modelling, this article investigates how in the mid-twentieth century electronic and programmable animal models became tools for exploring the inaccessible ontology of the human mind. The article examines how machines have informed our understanding of the learning…
Descriptors: Constructivism (Learning), Learning Processes, Foreign Countries, Epistemology
Ezeamuzie, Ndudi O.; Leung, Jessica S. C.; Ting, Fridolin S. T. – Journal of Educational Computing Research, 2022
Although abstraction is widely understood to be one of the primary components of computational thinking, the roots of abstraction may be traced back to different fields. Hence, the meaning of abstraction in the context of computational thinking is often confounded, as researchers interpret abstraction through diverse lenses. To disentangle these…
Descriptors: Computer Science Education, Thinking Skills, Research Reports, Abstract Reasoning
DeLiema, David; Kwon, Yejin Angela; Chisholm, Andrea; Williams, Immanuel; Dahn, Maggie; Flood, Virginia J.; Abrahamson, Dor; Steen, Francis F. – Cognition and Instruction, 2023
When teachers, researchers, and students describe productively responding to moments of failure in the learning process, what might this mean? Blending prior theoretical and empirical research on the relationship between failure and learning, and empirical results from four data sets that are part of a larger design-based research project, we…
Descriptors: Guidelines, Learning Processes, Correlation, Failure

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