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Rau, Martina Angela – International Journal of Artificial Intelligence in Education, 2017
Traditional knowledge-component models describe students' content knowledge (e.g., their ability to carry out problem-solving procedures or their ability to reason about a concept). In many STEM domains, instruction uses multiple visual representations such as graphs, figures, and diagrams. The use of visual representations implies a…
Descriptors: Knowledge Representation, Models, Competence, Learning Processes
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Twissell, Adrian – Educational Technology & Society, 2018
Abstract electronics concepts are difficult to develop because the phenomena of interest cannot be readily observed. Visualisation skills support learning about electronics and can be applied at different levels of representation and understanding (observable, symbolic and abstract). Providing learners with opportunities to make transitions…
Descriptors: Electronics, Case Studies, Concept Formation, Scientific Concepts
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Garrett, Lauretta – Journal of Developmental Education, 2013
Adult developmental mathematics students often work under great pressure to complete the mathematics sequences designed to help them achieve success (Bryk & Treisman, 2010). Results of a teaching experiment demonstrate how the ability to reason can be impeded by flaws in students' mental representations of mathematics. The earnestness of the…
Descriptors: Adult Education, Adult Learning, Developmental Programs, Mathematics Education
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Knauf, Rainer; Sakurai, Yoshitaka; Tsuruta, Setsuo; Jantke, Klaus P. – Journal of Educational Computing Research, 2010
University education often suffers from a lack of an explicit and adaptable didactic design. Students complain about the insufficient adaptability to the learners' needs. Learning content and services need to reach their audience according to their different prerequisites, needs, and different learning styles and conditions. A way to overcome such…
Descriptors: Prerequisites, College Instruction, Educational Experiments, Cognitive Style
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Ernst, Jeremy V.; Clark, Aaron C. – Engineering Design Graphics Journal, 2008
The objective of this study was to identify changes in dominant preferred learning styles of students based on instructional presentation of course content. This study evaluates dominant preferred learning styles of two groups of university students. The first group of students was enrolled in a course that introduces graphical representation in…
Descriptors: Cognitive Style, Questionnaires, Course Content, Teaching Methods
Lim, Kyu Yon – ProQuest LLC, 2008
The purpose of this study was to investigate the effectiveness of concept mapping strategies with different levels of generativity in terms of knowledge acquisition and knowledge representation. Also, it examined whether or not learners' self-regulated learning (SRL) skills influenced the effectiveness of concept mapping strategies with different…
Descriptors: Concept Mapping, Undergraduate Students, Knowledge Representation, Program Effectiveness
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Marshall, Byron B.; Chen, Hsinchun; Shen, Rao; Fox, Edward A. – Journal on Educational Resources in Computing, 2006
The GetSmart system was built to support theoretically sound learning processes in a digital library environment by integrating course management, digital library, and concept mapping components to support a constructivist, six-step, information search process. In the fall of 2002 more than 100 students created 1400 concept maps as part of…
Descriptors: Constructivism (Learning), Concept Mapping, Knowledge Representation, Electronic Libraries
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Michael, Joel; Rovick, Allen; Glass, Michael; Zhou, Yujian; Evens, Martha – Interactive Learning Environments, 2003
CIRCSIM-Tutor is a computer tutor designed to carry out a natural language dialogue with a medical student. Its domain is the baroreceptor reflex, the part of the cardiovascular system that is responsible for maintaining a constant blood pressure. CIRCSIM-Tutor's interaction with students is modeled after the tutoring behavior of two experienced…
Descriptors: Natural Language Processing, Medical Students, Computer Mediated Communication, Artificial Intelligence