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Ramon Mayor Martins; Christiane Gresse Von Wangenheim – Informatics in Education, 2024
Information technology (IT) is transforming the world. Therefore, exposing students to computing at an early age is important. And, although computing is being introduced into schools, students from a low socio-economic status background still do not have such an opportunity. Furthermore, existing computing programs may need to be adjusted in…
Descriptors: Information Technology, Socioeconomic Status, Social Class, Computer Literacy
Bradley Hayes – ProQuest LLC, 2024
This dissertation in practice explores the intersection of computer science education, specifically computational thinking and programming, with mathematics achievement among 15- year-old students in selected English-speaking countries. The research addresses a gap in understanding whether skills developed through computer science can positively…
Descriptors: Programming, Computer Science Education, Mathematics Achievement, Secondary School Students
Josef Guggemos; Roman Rietsche; Stephan Aier; Jannis Strecker; Simon Mayer – International Association for Development of the Information Society, 2024
Technological advancements, particularly in artificial intelligence, significantly transform our society and work practices. Computational thinking (CT) has emerged as a crucial 21st-century skill, enabling individuals to solve problems more effectively through an automation-oriented perspective and fundamental concepts of computer science. To…
Descriptors: Computation, Thinking Skills, 21st Century Skills, Test Construction
Hurst, Chris; Huntley, Ray – Journal of Research and Advances in Mathematics Education, 2020
Multiplicative thinking underpins much of the mathematics learned beyond the middle primary years. As such, it needs to be understood conceptually to highlight the connections between its many aspects. This paper focuses on one such connection; that is how the array, place value partitioning and the distributive property of multiplication are…
Descriptors: Multiplication, Mathematics Instruction, Teaching Methods, Concept Formation
Lonati, Violetta – Informatics in Education, 2020
The Bebras challenge offers pupils and teachers an engaging opportunity to discover informatics, by solving small tasks that aim at promoting computational thinking. Explanations and comments that reveal the computing concepts underlying the tasks are published after the contest, and teachers are encouraged to use this material in their school…
Descriptors: Foreign Countries, Computer Science Education, Information Science, Computation
Pelanek, Radek – IEEE Transactions on Learning Technologies, 2020
A measure of similarity of educational items has many applications in adaptive learning systems and can be useful also for teachers and content creators. We provide a thorough overview of approaches for measuring item similarity. We document the computation pipeline, explicitly highlighting many choices that have to be made in order to quantify…
Descriptors: Educational Technology, Instructional Materials, Measurement Techniques, Differences
Yazici, Sevil – International Journal of Technology and Design Education, 2020
Digital design and fabrication tools obtain constraints affecting creativity in conceptual design phase. There is a necessity to have a better understanding of issues related to the rationalization process of form, material and fabrication. The objective of this paper is to integrate analogue craft into architectural design studio that can be…
Descriptors: Manufacturing, Building Design, Architectural Education, Computer Uses in Education
A Machine Learning-Based Computational System Proposal Aiming at Higher Education Dropout Prediction
Nicoletti, Maria do Carmo; de Oliveira, Osvaldo Luiz – Higher Education Studies, 2020
In the literature related to higher education, the concept of dropout has been approached from several perspectives and, over the years, its definition has been influenced by the use of diversified semantic interpretations. In a general higher education environment dropout can be broadly characterized as the act of a student engaged in a course…
Descriptors: Artificial Intelligence, Man Machine Systems, Computation, Prediction
MacDonald, Beth L.; Moss, Diana L.; Hunt, Jessica H. – Mathematics Teacher: Learning and Teaching PK-12, 2020
In this article, the authors share how gameplay with dominoes can leverage students' quantitative reasoning to promote number development and additive reasoning. This article explores three domino games (Basic Dominoes, Just Before/Just After, and Ten Train), and considers the following: (1) rules and details; (2) students' subitizing and unit…
Descriptors: Games, Mathematics Instruction, Computation, Numeracy
Metsämuuronen, Jari – International Journal of Educational Methodology, 2020
Kelley's Discrimination Index (DI) is a simple and robust, classical non-parametric short-cut to estimate the item discrimination power (IDP) in the practical educational settings. Unlike item-total correlation, DI can reach the ultimate values of +1 and -1, and it is stable against the outliers. Because of the computational easiness, DI is…
Descriptors: Test Items, Computation, Item Analysis, Nonparametric Statistics
Peugh, James; Feldon, David F. – CBE - Life Sciences Education, 2020
Structural equation modeling is an ideal data analytical tool for testing complex relationships among many analytical variables. It can simultaneously test multiple mediating and moderating relationships, estimate latent variables on the basis of related measures, and address practical issues such as nonnormality and missing data. To test the…
Descriptors: Structural Equation Models, Goodness of Fit, Statistical Analysis, Computation
Dennis, Minyi Shih; Gratton-Fisher, Emma – Learning Disabilities Research & Practice, 2020
Secondary students with persistent mathematics difficulties need the most intensive intervention in order to improve their mathematics outcomes. One approach to intensifying and individualizing intervention is through data-based individualization (DBI). The present study used a single-subject, multiple-baseline-across-participants,…
Descriptors: High School Students, Mathematics Skills, Computation, Mathematical Concepts
Bortz, Whitney Wall; Gautam, Aakash; Tatar, Deborah; Lipscomb, Kemper – Journal of Science Education and Technology, 2020
Integrating computational thinking (CT) and science education is complex, and assessing the resulting learning gains even more so. Arguments that assessment should match the learning (Biggs, "Assessment & Evaluation in Higher Education," 21(1), 5-16. 1996; Airasian and Miranda, "Theory into Practice," 41(4), 249-254. 2002;…
Descriptors: Computation, Thinking Skills, Science Education, Evaluation Methods
Calderon, Ana C.; Skillicorn, Deiniol; Watt, Andrew; Perham, Nick – Education and Information Technologies, 2020
We propose the first steps towards a rigorous analysis of the effectiveness of an emerging pedagogy, Computational Thinking. We found that two aspects of the pedagogy have a positive effect with regard to enhancing two cognitive processes, namely sequential thinking and in abstract thinking. Our data was gathered experimentally with a cohort of…
Descriptors: Computation, Thinking Skills, Cognitive Processes, Logical Thinking
Bejjanki, Vikranth R.; Randrup, Emily R.; Aslin, Richard N. – Developmental Science, 2020
Human adults are adept at mitigating the influence of sensory uncertainty on task performance by integrating sensory cues with learned prior information, in a Bayes-optimal fashion. Previous research has shown that young children and infants are sensitive to environmental regularities, and that the ability to learn and use such regularities is…
Descriptors: Young Children, Sensory Experience, Cues, Learning Processes