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Kastens, Kim A.; Zrada, Melissa; Turrin, Margie – Journal of Geoscience Education, 2020
Question-asking is a necessary step towards formulating hypotheses, making decisions, and solving problems, and is Practice #1 in the Next Generation Science Standards. To improve question-asking, educators and researchers need a way to categorize and evaluate students' questions, so as to judge whether an intervention has been effective. We…
Descriptors: Undergraduate Students, Problem Solving, Data Collection, Visualization
Undergraduate Non-Science Majors' Descriptions and Interpretations of Scientific Data Visualizations
Swenson, Sandra Signe – ProQuest LLC, 2010
Professionally developed and freely accessible through the Internet, scientific data maps have great potential for teaching and learning with data in the science classroom. Solving problems or developing ideas while using data maps of Earth phenomena in the science classroom may help students to understand the nature and process of science. Little…
Descriptors: Majors (Students), Public Colleges, Maps, Internet
Goldin, Sarah E.; Thorndyke, Perry W. – 1981
This research attempts to diagnose the skills required for successful spatial performance in order to provide a theoretical foundation for military training in such tasks as map reading, surveying, and navigation. It is known that successful performance on spatial tasks depends on task requirements (e.g., requisite knowledge, alternative paths to…
Descriptors: Adults, Cognitive Ability, Cognitive Processes, Cognitive Style
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