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Booth, Julie L.; Barbieri, Christina; Eyer, Francie; Paré-Blagoev, E. Juliana – Journal of Problem Solving, 2014
Students hold many misconceptions as they transition from arithmetic to algebraic thinking, and these misconceptions can hinder their performance and learning in the subject. To identify the errors in Algebra I which are most persistent and pernicious in terms of predicting student difficulty on standardized test items, the present study assessed…
Descriptors: Algebra, Mathematics Instruction, Misconceptions, Mathematical Concepts
de Villiers, Celéste; Hopkins, Sarah – Mathematics Education Research Group of Australasia, 2013
Counting strategies initially used by young children to perform simple addition are often replaced by more efficient counting strategies, decomposition strategies and rule-based strategies until most answers are encoded in memory and can be directly retrieved. Practice is thought to be the key to developing fluent retrieval of addition facts. This…
Descriptors: Addition, Mathematics Instruction, Mathematics Skills, Computation
Lupkowski, Ann E.; And Others – Gifted Child Today (GCT), 1990
The article describes application to mathematically gifted elementary age students of the diagnostic/prescriptive model developed by the Study of Mathematically Precocious Youth. A five-step procedure of beyond-level standardized testing is followed by mentored instruction based on analysis of testing errors. (DB)
Descriptors: Academically Gifted, Acceleration (Education), Diagnostic Teaching, Elementary Education
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