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ERIC Number: EJ1073864
Record Type: Journal
Publication Date: 2008
Abstractor: As Provided
Reference Count: 38
Addressing Diverse Learner Preferences and Intelligences with Emerging Technologies: Matching Models to Online Opportunities
Zhang, Ke; Bonk, Curtis J.
Canadian Journal of Learning and Technology, v34 n2 Spr 2008
This paper critically reviews various learning preferences and human intelligence theories and models with a particular focus on the implications for online learning. It highlights a few key models, Gardner's multiple intelligences, Fleming and Mills' VARK model, Honey and Mumford's Learning Styles, and Kolb's Experiential Learning Model, and attempts to link them to trends and opportunities in online learning with emerging technologies. By intersecting such models with online technologies, it offers instructors and instructional designers across educational sectors and situations new ways to think about addressing diverse learner needs, backgrounds, and expectations. Learning technologies are important for effective teaching, as are theories and models and theories of learning. We argue that more immense power can be derived from connections between the theories, models and learning technologies.
Descriptors: Online Courses, Student Diversity, Preferences, Cognitive Style, Models, Multiple Intelligences, Experiential Learning, Educational Opportunities, Educational Trends, Student Needs, Student Characteristics, Student Educational Objectives, Educational Technology, Learning Theories, Electronic Learning, Instructional Design, Design Requirements, Alignment (Education), Schematic Studies, Measures (Individuals)
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Authoring Institution: N/A