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Muradoglu, Melis; Cimpian, Joseph R.; Cimpian, Andrei – Journal of Cognition and Development, 2023
Mixed-effects models are an analytic technique for modeling repeated measurement or nested data. This paper explains the logic of mixed-effects modeling and describes two examples of mixed-effects analyses using R. The intended audience of the paper is psychologists who specialize in cognitive development research. Therefore, the concepts and…
Descriptors: Cognitive Development, Models, Programming Languages, Psychologists
Julius Meier; Peter Hesse; Stephan Abele; Alexander Renkl; Inga Glogger-Frey – Instructional Science: An International Journal of the Learning Sciences, 2024
Self-explanation prompts in example-based learning are usually directed backwards: Learners are required to self-explain problem-solving steps just presented ("retrospective" prompts). However, it might also help to self-explain upcoming steps ("anticipatory" prompts). The effects of the prompt type may differ for learners with…
Descriptors: Problem Based Learning, Problem Solving, Prompting, Models
Jonathan Robert Bowers – ProQuest LLC, 2024
To make sense of our interconnected and algorithm driven world, students increasingly need proficiency with computational thinking (CT), systems thinking (ST), and computational modeling. One aspect of computational modeling that can support students with CT, ST, and modeling is testing and debugging. Testing and debugging enables students to…
Descriptors: Troubleshooting, Thinking Skills, Computation, Computer Science Education
Schreiner, Claudia; Wiesner, Christian – European Educational Researcher, 2023
In the context of a rapid digital transformation, digital competence is now regarded as a fourth cultural skill complementing reading, writing, and arithmetic. We argue that a well-structured and sound competence model is needed as a shared foundation for learning, teaching, pedagogical diagnostics and evaluative schemes in the school system.…
Descriptors: Computation, Thinking Skills, Digital Literacy, Competence
Zhong, Baichang; Liu, Xiaofan; Xia, Liying; Sun, Wang – SAGE Open, 2022
Many countries and regions have reached a consensus to promote science, technology, engineering, and mathematics (STEM) education in the past decade. A body of studies have demonstrated that the design and organization of interdisciplinary teaching activities are important for the effective implementation of STEM education. So far, however, little…
Descriptors: STEM Education, Models, Teaching Methods, Robotics
Maksum, Hasan; Yuvenda, Dori; Purwanto, Wawan – Journal of Turkish Science Education, 2022
The purpose of this research was to ascertain whether there had been any improvement in students' metacognitive and critical thinking skills through the development of the 'Teaching Factory Based on Troubleshooting' (TEFA-T) model in automotive vocational learning. The research had both quantitative and qualitative components and applied the 4D…
Descriptors: Vocational Education, Troubleshooting, Metacognition, Critical Thinking