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Smith, Linsey A.; Gentner, Dedre – Society for Research on Educational Effectiveness, 2011
The authors explore the role of comparison in improving graph fluency. The ability to use graphs fluently is crucial for STEM achievement, but graphs are challenging to interpret and produce because they often involve integration of multiple variables, continuous change in variables over time, and omission of certain details in order to highlight…
Descriptors: Graphs, Laboratories, Instructional Effectiveness, Cognitive Processes
Kovalik, Susan J.; Olsen, Karen D. – Corwin, 2010
This book examines learning science from multiple perspectives--especially a child's. The whimsical character of Mary Froggins guides readers through the steps of igniting students' natural sense of wonder, incorporating brain research, integrating science concepts with other subjects, and applying science to daily life. The authors demonstrate…
Descriptors: Educational Strategies, Curriculum Development, Multiple Intelligences, Science Programs
Peer reviewedSwatton, P. – Educational Review, 1995
Analysis of a sample of 100 pupil scripts from a British Assessment of Performance Unit survey suggests that ability to read and interpret graphical data should not be seen as an independent process skill. Instead, hidden cognitive demands of assessment items require integrated understanding based on a sophisticated procedural model. (SK)
Descriptors: Cognitive Processes, Data Interpretation, Foreign Countries, Graphs
Peer reviewedArons, Arnold B. – Physics Teacher, 1983
Describes a continuous sequence of development of arithmetical and ratio reasoning capacity which very few students now attain in introductory science courses. Sequence progresses from verbal interpretation of ratio of two numbers, to arithmetical reasoning involving division, coupling arithmetical reasoning to graphical representation, and to…
Descriptors: Arithmetic, Cognitive Processes, College Science, Graphs
Brasell, Heather – 1987
Two questions about the effects of microcomputer-based laboratory (MBL) activities on graphing skills were addressed in this study: (1) the extent to which activities help students link their concrete experiences with motion with graphic representations of these experiences; and (2) the degree of importance of the real-time aspect of the MBL in…
Descriptors: Cognitive Processes, Computer Assisted Instruction, Computer Graphics, Distance
Peer reviewedBrasell, Heather M.; Rowe, Mary Budd – School Science and Mathematics, 1993
Examines the influence of two factors of the process of graphing on rural students' (n=93) ability to comprehend kinematics graphs on constant velocity events. Students exhibited difficulty in constructing and comprehending graphs of derived variables and were unaware of their own graphing skills deficiencies. (34 references) (MDH)
Descriptors: Cognitive Processes, Cognitive Structures, Computer Assisted Instruction, Graphs
Sampson, Demetrios G., Ed.; Spector, J. Michael, Ed.; Ifenthaler, Dirk, Ed.; Isaias, Pedro, Ed. – International Association for Development of the Information Society, 2014
These proceedings contain the papers of the 11th International Conference on Cognition and Exploratory Learning in the Digital Age (CELDA 2014), October 25-27, 2014, which has been organized by the International Association for Development of the Information Society (IADIS) and endorsed by the Japanese Society for Information and Systems in…
Descriptors: Conference Papers, Teaching Methods, Technological Literacy, Technology Uses in 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

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