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Mehmet Ceylan; Durmus Aslan – Education and Information Technologies, 2024
This study was conducted to investigate the effects of learning trajectories-based coding (LTs) and LTs-based program on preschoolers' length, area, volume, and angle measurement skills. A quasi-experimental research design was utilized with a quantitative approach. The study's participants were 47 children between the ages of 55-71 months who…
Descriptors: Learning Trajectories, Coding, Mathematics Skills, Measurement Techniques
Mark Johnson; Rafiq Saleh – Interactive Learning Environments, 2024
Educational assessment is inherently uncertain, where physiological, psychological and social factors play an important role in establishing judgements which are assumed to be "absolute". AI and other algorithmic approaches to grading of student work strip-out uncertainty, leading to a lack of inspectability in machine judgement and…
Descriptors: Artificial Intelligence, Evaluation Methods, Technology Uses in Education, Man Machine Systems
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
Abdullah Alamer; Florian Schuberth; Jörg Henseler – Studies in Second Language Acquisition, 2024
Researchers in second language (L2) and education domain use different statistical methods to assess their constructs of interest. Many L2 constructs emerge from elements/parts, i.e., the elements "define" and "form" the construct and not the other way around. These constructs are referred to as emergent variables (also called…
Descriptors: Factor Analysis, Factor Structure, Second Language Learning, Language Research
Arun-Balajiee Lekshmi-Narayanan; Priti Oli; Jeevan Chapagain; Mohammad Hassany; Rabin Banjade; Vasile Rus – Grantee Submission, 2024
Worked examples, which present an explained code for solving typical programming problems are among the most popular types of learning content in programming classes. Most approaches and tools for presenting these examples to students are based on line-by-line explanations of the example code. However, instructors rarely have time to provide…
Descriptors: Coding, Computer Science Education, Computational Linguistics, Artificial Intelligence
Janet E. Rosenbaum; Lisa C. Dierker – Journal of Statistics and Data Science Education, 2024
Self-efficacy is associated with a range of educational outcomes, including science and math degree attainment. Project-based statistics courses have the potential to increase students' math self-efficacy because projects may represent a mastery experience, but students enter courses with preexisting math self-efficacy. This study explored…
Descriptors: Self Efficacy, Statistics Education, Introductory Courses, Self Esteem
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
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
Zhou, Guojing; Moulder, Robert G.; Sun, Chen; D'Mello, Sidney K. – International Educational Data Mining Society, 2022
In collaborative problem solving (CPS), people's actions are interactive, interdependent, and temporal. However, it is unclear how actions temporally relate to each other and what are the temporal similarities and differences between successful vs. unsuccessful CPS processes. As such, we apply a temporal analysis approach, Multilevel Vector…
Descriptors: Cooperative Learning, Problem Solving, College Students, Physics
Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Journal of Information Systems Education, 2023
Educators who teach programming subjects are often wondering "which programming language should I teach first?" The debate behind this question has a long history and coming up with a definite answer to this question would be farfetched. Nonetheless, several efforts can be identified in the literature wherein pros and cons of mainstream…
Descriptors: Comparative Analysis, Programming Languages, Probability, Error Patterns
Nitesh Kumar Jha; Plaban Kumar Bhowmik; Kaushal Kumar Bhagat – Educational Technology Research and Development, 2024
A majority of research in Computational Thinking (CT) mainly focuses on teaching coding to school students. However, CT involves more than just coding and includes other skills like algorithmic thinking. The current study developed an Online Inquiry-based Learning Platform for Computational Thinking (CT-ONLINQ) that follows Inquiry-Based Learning…
Descriptors: Thinking Skills, Computer Science Education, Comparative Analysis, Problem Solving
Pishtari, Gerti; Prieto, Luis P.; Rodriguez-Triana, Maria Jesus; Martinez-Maldonado, Roberto – Journal of Learning Analytics, 2022
This research was triggered by the identified need in literature for large-scale studies about the kinds of designs that teachers create for mobile learning (m-learning). These studies require analyses of large datasets of learning designs. The common approach followed by researchers when analyzing designs has been to manually classify them…
Descriptors: Scaling, Classification, Context Effect, Telecommunications
Lee, Yew-Jin; Wan, Dongsheng – Research in Science Education, 2022
There has been a longstanding interest in the kinds of scientific knowledge that primary science learners must know and be able to do, which comprise the intellectual demands in this subject. These prescriptions chiefly take guidance from national curriculum documents, especially in the form of their learning outcomes (LO) or learning standards.…
Descriptors: Semantics, Science Education, Outcomes of Education, Elementary School Students
Hyeseong Lee; Seung H. Kim; Hae Min Yu – International Journal on E-Learning, 2024
Despite the benefits of teaching computational thinking (CT) and applying coding tools in schools, many teachers feel unprepared to use these technologies. Hence, we introduced CT concepts and coding tools to pre-service teachers (n=36; 17 in online class and 19 in in-person class), equipping them with digital competencies through activities with…
Descriptors: Coding, Mathematics Instruction, Pedagogical Content Knowledge, Faculty Development
Kyza, Eleni A.; Georgiou, Yiannis; Agesilaou, Andria; Souropetsis, Markos – Journal of Educational Computing Research, 2022
There are increasing calls to introduce computational thinking in schools; the arguments in favor call upon research suggesting that even kindergarten children can successfully engage in coding. This contribution presents a cross-sectional study examining the coding practices and computational thinking of fifty-one primary school children using…
Descriptors: Case Studies, Elementary School Students, Computer Science Education, Coding
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