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Changpetch, Pannapa; Reid, Moya – Journal of Education for Business, 2021
Based on a statistical analysis, undergraduate business students are shown to prefer classification tree over six other standard data mining techniques. Data were collected over a 4-year period from students taking a data mining course offered at a business university in the US. The principal reason given by students for this preference is that…
Descriptors: Data Analysis, Models, Statistical Analysis, Undergraduate Students
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Lin, Jing; Zhang, Letong; Neumann, Knut; Cheng, Ping-Han; Wei, Wenting; Chang, Chun-Yen – Asia-Pacific Science Education, 2022
Scientific modeling (SM) is a core practice of science and an important component of scientific literacy. Supporting students in developing the competence to construct, use, evaluate, and revise models is hence of particular relevance. While research has shown that spatial visualization (SV), a core component of spatial ability, is correlated with…
Descriptors: Spatial Ability, Visualization, Scientific Concepts, Models
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Akle, Veronica; Peña-Silva, Ricardo A.; Valencia, Diego M.; Rincón-Perez, Carlos W. – Anatomical Sciences Education, 2018
Visualizing anatomical structures and functional processes in three dimensions (3D) are important skills for medical students. However, contemplating 3D structures mentally and interpreting biomedical images can be challenging. This study examines the impact of a new pedagogical approach to teaching neuroanatomy, specifically how building a…
Descriptors: Anatomy, Visualization, Brain, Medical Education
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Šafhalter, Andrej; Vukman, Karin Bakracevic; Glodež, Srecko – Journal of Educational Computing Research, 2016
The aim of this research was to establish whether gender and age have an impact on spatial reasoning and its development through the use of 3D modeling. The study was conducted on a sample of 196 children from sixth to ninth grade, of whom 95 represented the experimental group and 101 the control group. The experimental group received 3D modeling…
Descriptors: Spatial Ability, Visual Perception, Models, Visualization
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Harle, Marissa; Towns, Marcy – Journal of Chemical Education, 2011
Chemists and scientists use spatial abilities as part of the way they understand and communicate their subject areas. A review of the foundational research literature in spatial ability and its connections to chemistry as a field and chemical education research allows for the formulation of implications for teaching in chemistry. (Contains 7…
Descriptors: Chemistry, Spatial Ability, Literature, Science Instruction
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Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
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