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Isotani, Seiji; Reis, Helena M.; Alvares, Danilo; Brandão, Anarosa A. F.; Brandão, Leônidas O. – Interactive Learning Environments, 2018
Interactive or Dynamic Geometry System (DGS) is a tool that help to teach and learn geometry using a computer-based interactive environment. Traditionally, the interaction with DGS is based on keyboard and mouse events where the functionalities are accessed using a menu of icons. Nevertheless, recent findings suggest that such a traditional model…
Descriptors: Computer Assisted Instruction, Mathematics Instruction, Geometry, Dictionaries
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Abrahamson, Dor; Trninic, Dragan; Gutierrez, Jose F.; Huth, Jacob; Lee, Rosa G. – Technology, Knowledge and Learning, 2011
Radical constructivists advocate discovery-based pedagogical regimes that enable students to incrementally and continuously adapt their cognitive structures to the instrumented cultural environment. Some sociocultural theorists, however, maintain that learning implies discontinuity in conceptual development, because novices must appropriate expert…
Descriptors: Feedback (Response), Cognitive Structures, Concept Formation, Cultural Context
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Lee, Sun-Hee; Jang, Seok Bae; Seo, Sang-Kyu – CALICO Journal, 2009
In this study, we focus on particle errors and discuss an annotation scheme for Korean learner corpora that can be used to extract heuristic patterns of particle errors efficiently. We investigate different properties of particle errors so that they can be later used to identify learner errors automatically, and we provide resourceful annotation…
Descriptors: Feedback (Response), Error Patterns, Korean, Computational Linguistics
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Veermans, Koen; van Joolingen, Wouter; de Jong, Ton – International Journal of Science Education, 2006
This article describes a study into the role of heuristic support in facilitating discovery learning through simulation-based learning. The study compares the use of two such learning environments in the physics domain of collisions. In one learning environment (implicit heuristics) heuristics are only used to provide the learner with guidance…
Descriptors: Pretests Posttests, Physics, Heuristics, Educational Environment
Glaser, Robert; And Others – 1991
This study seeks to establish which scientific reasoning skills are primarily domain-general and which appear to be domain-specific. The subjects, 12 university undergraduates, each participated in self-directed experimentation with three different content domains. The experimentation contexts were computer-based laboratories in d.c. circuits…
Descriptors: Computer Assisted Instruction, Discovery Learning, Heuristics, Higher Education
Landa, Lev N. – Educational Technology, 1998
After reviewing 50 educational software titles produced by 21 companies to assess how thinking and thinking skills were developed, the author found most had similar methodological drawbacks. Describes the algo-heuristic methodological position and outlines drawbacks of current software. (PEN)
Descriptors: Algorithms, Comparative Analysis, Computer Assisted Instruction, Computer Software Evaluation
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Hoppe, H. Ulrich – Journal of Artificial Intelligence in Education, 1994
Examines the deductive approach to error diagnosis for intelligent tutoring systems. Topics covered include the principles of the deductive approach to diagnosis; domain-specific heuristics to solve the problem of generalizing error patterns; and deductive diagnosis and the hypertext-based learning environment. (Contains 26 references.) (JLB)
Descriptors: Algorithms, Artificial Intelligence, Computer Assisted Instruction, Deduction
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Liu, Chao-Lin – Educational Technology & Society, 2005
The author analyzes properties of mutual information between dichotomous concepts and test items. The properties generalize some common intuitions about item comparison, and provide principled foundations for designing item-selection heuristics for student assessment in computer-assisted educational systems. The proposed item-selection strategies…
Descriptors: Test Items, Heuristics, Classification, Item Analysis