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Stieff, Mike; Origenes, Andrea; DeSutter, Dane; Lira, Matthew; Banevicius, Lukas; Tabang, Dylan; Cabel, Gervacio – Journal of Educational Psychology, 2018
Spatial ability predicts success in STEM (Science, Technology, Education, and Mathematics) fields, particularly chemistry. This paper reports two studies investigating the unique contribution of mental rotation ability to spatial thinking in a STEM discipline. Using authentic disciplinary tasks from chemistry, we show that the difficulty of a…
Descriptors: Cognitive Processes, STEM Education, Spatial Ability, Chemistry
Nitchot, Athitaya; Wettayaprasit, Wiphada; Gilbert, Lester – E-Learning and Digital Media, 2019
The aim of this research is to introduce a method of constructing knowledge structures which represent the relationships among the knowledge items in a pedagogically useful way. A prototype, "MyTeLeMap," was implemented to support both learners and instructors. Learners could visualize the knowledge structures of different knowledge…
Descriptors: Individualized Instruction, Visualization, Learning Processes, Cognitive Structures
Twissell, Adrian – Educational Technology & Society, 2018
Abstract electronics concepts are difficult to develop because the phenomena of interest cannot be readily observed. Visualisation skills support learning about electronics and can be applied at different levels of representation and understanding (observable, symbolic and abstract). Providing learners with opportunities to make transitions…
Descriptors: Electronics, Case Studies, Concept Formation, Scientific Concepts
Rau, Martina A. – Journal of Learning Analytics, 2017
STEM instruction often uses visual representations. To benefit from these, students need to understand how representations show domain-relevant concepts. Yet, this is difficult for students. Prior research shows that physical representations (objects that students manipulate by hand) and virtual representations (objects on a computer screen that…
Descriptors: High School Students, Charter Schools, STEM Education, Knowledge Representation
Gil, Einat; Gibbs, Alison L. – Statistics Education Research Journal, 2017
In this study, we follow students' modeling and covariational reasoning in the context of learning about big data. A three-week unit was designed to allow 12th grade students in a mathematics course to explore big and mid-size data using concepts such as trend and scatter to describe the relationships between variables in multivariate settings.…
Descriptors: Foreign Countries, Secondary School Students, Grade 12, Statistics

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