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Wickstrom, Megan H.; Carr, Ruth; Lackey, Dacia – Mathematics Teaching in the Middle School, 2017
Mathematical modeling, a practice standard in the Common Core State Standards for Mathematics (CCSSM) (CCSSI 2010), is a process by which students develop and use mathematics as a tool to make sense of the world around them. Students investigate a real-world situation by asking mathematical questions; along the way, they need to decide how to use…
Descriptors: Parks, Common Core State Standards, Mathematics Instruction, Mathematical Models
Pelánek, Radek; Rihák, Ji?rí – International Educational Data Mining Society, 2016
In online educational systems we can easily collect and analyze extensive data about student learning. Current practice, however, focuses only on some aspects of these data, particularly on correctness of students answers. When a student answers incorrectly, the submitted wrong answer can give us valuable information. We provide an overview of…
Descriptors: Foreign Countries, Online Systems, Geography, Anatomy
Shore, Felice S.; Cooper, Linda L. – Mathematics Teaching in the Middle School, 2010
The 2008 presidential election is a great backdrop for analyzing graphs, learning about population distributions, and studying the effect on the electoral voting process. To take advantage of the enthusiasm surrounding the election, the authors conducted two activities in the months leading up to the 2008 presidential elections with several groups…
Descriptors: Voting, Elections, Urban Areas, Mathematics Instruction
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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