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van der Meij, J.; de Jong, T. – Journal of Computer Assisted Learning, 2011
Processing of multiple representations in multimedia learning environments is considered to help learners obtain a more complete overview of the domain and gain deeper knowledge. This is based on the idea that relating and translating different representations leads to reflection beyond the boundaries and details of the separate representations.…
Descriptors: Test Items, Computer Assisted Instruction, Learning Processes, Cues
Dalgarno, Barney; Lee, Mark J. W. – British Journal of Educational Technology, 2010
This article explores the potential learning benefits of three-dimensional (3-D) virtual learning environments (VLEs). Drawing on published research spanning two decades, it identifies a set of unique characteristics of 3-D VLEs, which includes aspects of their representational fidelity and aspects of the learner-computer interactivity they…
Descriptors: Experiential Learning, Knowledge Representation, Virtual Classrooms, Educational Research
Mislevy, Robert J.; Behrens, John T.; Bennett, Randy E.; Demark, Sarah F.; Frezzo, Dennis C.; Levy, Roy; Robinson, Daniel H.; Rutstein, Daisy Wise; Shute, Valerie J.; Stanley, Ken; Winters, Fielding I. – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2007
People use external knowledge representations (EKRs) to identify, depict, transform, store, share, and archive information. Learning how to work with EKRs is central to becoming proficient in virtually every discipline. As such, EKRs play central roles in curriculum, instruction, and assessment. Five key roles of EKRs in educational assessment are…
Descriptors: Educational Assessment, Computer Networks, Test Construction, Computer Assisted Testing

Bradford, James H.; Cote-Laurence, Paulette – Computers and the Humanities, 1995
Describes an experimental computer program that attempts to simulate a choreographers' knowledge and expertise. The user expresses a set of rules that describe some of the dynamic aspects of a dance. These rules are applied nondeterministically by a "rule driver" program. The rule driver embodies a heuristic algorithm. (MJP)
Descriptors: Artificial Intelligence, Cognitive Processes, Computer Assisted Instruction, Computer Oriented Programs