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Hafidi, Mohamed; Bensebaa, Taher – International Journal of Distance Education Technologies, 2015
The majority of adaptive and intelligent tutoring systems (AITS) are dedicated to a specific domain, allowing them to offer accurate models of the domain and the learner. The analysis produced from traces left by the users is didactically very precise and specific to the domain in question. It allows one to guide the learner in case of difficulty…
Descriptors: Intelligent Tutoring Systems, Foreign Countries, Interdisciplinary Approach, Universities
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Oviatt, Sharon L.; Cohen, Adrienne O. – Journal of Science Education and Technology, 2010
From a theoretical viewpoint, educational interfaces that facilitate communicative actions involving representations central to a domain can maximize students' effort associated with constructing new schemas. In addition, interfaces that minimize working memory demands due to the interface per se, for example by mimicking existing non-digital work…
Descriptors: Problem Solving, Short Term Memory, Science Education, Computer Interfaces
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Manches, Andrew; O'Malley, Claire; Benford, Steve – Computers & Education, 2010
This research aims to explore the role of physical representations in young children's numerical learning then identify the benefits of using a graphical interface in order to understand the potential for developing interactive technologies in this domain. Three studies are reported that examined the effect of using physical representations…
Descriptors: Young Children, Computer Interfaces, Problem Solving, Mathematics Instruction
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Aleven, Vincent; McLaren, Bruce M.; Sewall, Jonathan; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2009
The Cognitive Tutor Authoring Tools (CTAT) support creation of a novel type of tutors called example-tracing tutors. Unlike other types of ITSs (e.g., model-tracing tutors, constraint-based tutors), example-tracing tutors evaluate student behavior by flexibly comparing it against generalized examples of problem-solving behavior. Example-tracing…
Descriptors: Feedback (Response), Student Behavior, Intelligent Tutoring Systems, Problem Solving
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Ketelhut, Diane Jass; Nelson, Brian C.; Clarke, Jody; Dede, Chris – British Journal of Educational Technology, 2010
This study investigated novel pedagogies for helping teachers infuse inquiry into a standards-based science curriculum. Using a multi-user virtual environment (MUVE) as a pedagogical vehicle, teams of middle-school students collaboratively solved problems around disease in a virtual town called River City. The students interacted with "avatars" of…
Descriptors: Urban Areas, Virtual Classrooms, Science Education, Science Curriculum
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Scarlatos, Lori L. – Interactive Technology and Smart Education, 2006
Educators recognize that group work and physical involvement with learning materials can greatly enhance the understanding and retention of difficult concepts. As a result, math manipulatives--such as pattern blocks and number lines--have increasingly been making their way into classrooms and children's museums. Yet without the constant guidance…
Descriptors: Museums, Mathematical Concepts, Mathematics Instruction, Problem Solving
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers