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Active learning models and instructional systems
Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).ORCID iD: 0000-0001-6671-6157
Umeå Universitet.
2002 (English)In: @ – Learning in Higher Education / [ed] F. Buchberger, S. Berghammer & K. Enser, Linz: Trauner Verlag , 2002Chapter in book (Other academic)
Abstract [en]

Contemporary society puts forward need for new learning possibilities, which are provided by distance education methods using networked settings. The success of computer-aided instruction is determined by not only involved computer science methods and information technologies but also by deep research into pedagogical methodology. This paper makes an attempt to establish how modern teaching and learning scenarios can be supported by learning technology standards, systems, and specialized computer tools. To give students good learning experience active learning methods ought to be employed in distance education. First, we will consider several learning methods such as case-based learning, team learning/informative testing, learning by designing, discovery learning, and the Jigsaw method. It will allow for determination of what kind of support is needed for students and teachers. Then, we will discuss different learning technology standards, projects and systems to find out what capabilities they provide for the considered methods. Finally, a learning environment architecture will be presented for supporting active learning. The learning environment architecture includes four layers that contain functionality required for active learning. We will dwell upon the functionality and two implementation examples of the environment – PharmaPaC and SwedKid.

Place, publisher, year, edition, pages
Linz: Trauner Verlag , 2002.
Keywords [en]
Active learning, Learning models, Learning environments, Instructional systems, Computer-aided instruction, Distance education, Online learning
National Category
Computer Sciences Information Systems Educational Sciences
Identifiers
URN: urn:nbn:se:hj:diva-20290OAI: oai:DiVA.org:hj-20290DiVA, id: diva2:589706
Available from: 2013-01-18 Created: 2013-01-18 Last updated: 2025-02-18Bibliographically approved

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Tarasov, Vladimir

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CiteExportLink to record
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Citation style
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  • asciidoc
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