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Ilyse Resnick; Elizabeth Louise Chapman; Thomas F. Shipley – Journal of Science Education and Technology, 2024
Visual representations of data are widely used for communication and understanding, particularly in science, technology, engineering, and mathematics (STEM). However, despite their importance, many people have difficulty understanding data-based visualizations. This work presents a series of three studies that examine how understanding time-based…
Descriptors: Time Perspective, Graphs, Visual Aids, Visualization
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Lin, Jing-Wen – EURASIA Journal of Mathematics, Science & Technology Education, 2017
Cross-grade studies are valuable for the development of sequential curriculum. However such studies are time and resource intensive and fail to provide a clear representation to integrate different levels of representational complexity. Lin (Lin, 2006; Lin & Chiu, 2006; Lin, Chiu, & Hsu, 2006) proposed a cladistics approach in conceptual…
Descriptors: Cognitive Structures, Models, Visualization, Foreign Countries
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Anastopoulou, Stamatina; Sharples, Mike; Baber, Chris – British Journal of Educational Technology, 2011
This paper explores the value of employing multiple modalities to facilitate science learning with technology. In particular, it is argued that when multiple modalities are employed, learners construct strong relations between physical movement and visual representations of motion. Body interactions with visual representations, enabled by…
Descriptors: Graphs, Scientific Concepts, Science Instruction, Visualization
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection