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Yu, Chong Ho; Lee, Hyun Seo; Lara, Emily; Gan, Siyan – Practical Assessment, Research & Evaluation, 2018
Big data analytics are prevalent in fields like business, engineering, public health, and the physical sciences, but social scientists are slower than their peers in other fields in adopting this new methodology. One major reason for this is that traditional statistical procedures are typically not suitable for the analysis of large and complex…
Descriptors: Data Analysis, Social Sciences, Social Science Research, Models
Katsioloudis, Petros J.; Stefaniak, Jill E. – Journal of Technology Education, 2018
Results from a number of studies indicate that the use of drafting models can positively influence the spatial visualization ability for engineering technology students. However, additional variables such as light, temperature, motion and color can play an important role but research provides inconsistent results. Considering this, a set of 5…
Descriptors: Drafting, Models, Spatial Ability, Visualization
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
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
Katsioloudis, Petros; Jovanovic, Vukica; Jones, Mildred – Journal of Technology Education, 2014
The main purpose of this study was to determine significant positive effects among the use of three different types of drafting models, and to identify whether any differences exist towards promotion of spatial visualization ability for students in Industrial Technology and Technology Education courses. In particular, the study compared the use of…
Descriptors: Models, Spatial Ability, Visualization, Industrial Education
Virk, Satyugjit Singh – ProQuest LLC, 2013
Previous cognitive models of memory have not comprehensively taken into account the internal cognitive load of chunking isolated information and have emphasized the external cognitive load of visual presentation only. Under the Virk Long Term Working Memory Multimedia Model of cognitive load, drawing from the Cowan model, students presented with…
Descriptors: STEM Education, Knowledge Representation, Visualization, Cognitive Processes
Hsu, Jack Shih-Chieh; Huang, Hsieh-Hong; Linden, Lars P. – Educational Technology & Society, 2011
This study explores a de-bias function for a decision support systems (DSS) that is designed to help a user avoid confirmation bias by increasing the user's learning opportunities. Grounded upon the theory of mental models, the use of DSS is viewed as involving a learning process, whereby a user is directed to build mental models so as to reduce…
Descriptors: Decision Support Systems, Computer Mediated Communication, Experiments, Decision Making
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

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