Sharing Knowledge in Adaptive Learning Systems

Milos Kravcik; Dragan Gasevic

Sharing Knowledge in Adaptive Learning Systems

Milos Kravcik
, Dragan Gasevic

Research output: Contribution to conference › Conference Paper until 1 July 2025 › Academic

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Abstract

In this paper we deal with knowledge representation in the area of learning design and adaptive learning. Specification of concrete instances is usually context-dependent and does not support reusability very well, thus we need to represent the knowledge that could help us in generating the instances dynamically.

Original language	English
Publication status	Published - 18 Sept 2006

Keywords

IMS Learning Design
Adaptive Learning

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W5-1kraAccepted author manuscript, 75.7 KBLicence: CC BY-NC-ND

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title = "Sharing Knowledge in Adaptive Learning Systems",

abstract = "In this paper we deal with knowledge representation in the area of learning design and adaptive learning. Specification of concrete instances is usually context-dependent and does not support reusability very well, thus we need to represent the knowledge that could help us in generating the instances dynamically.",

keywords = "IMS Learning Design, Adaptive Learning",

author = "Milos Kravcik and Dragan Gasevic",

note = "DS\_Description: Please, cite this publication as: Kravcik, M. \& Gasevic, D. (2006). Sharing Knowledge in Adaptive Learning Systems. Proceedings of ICALT2006. July, Kerkrade, The Netherlands: IEEE. Retrieved July 30th, 2006, from http://dspace.learningnetworks.org DS\_Sponsorship:ProLearn Project",

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AU - Gasevic, Dragan

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PY - 2006/9/18

Y1 - 2006/9/18

N2 - In this paper we deal with knowledge representation in the area of learning design and adaptive learning. Specification of concrete instances is usually context-dependent and does not support reusability very well, thus we need to represent the knowledge that could help us in generating the instances dynamically.

AB - In this paper we deal with knowledge representation in the area of learning design and adaptive learning. Specification of concrete instances is usually context-dependent and does not support reusability very well, thus we need to represent the knowledge that could help us in generating the instances dynamically.

KW - IMS Learning Design

KW - Adaptive Learning

M3 - Conference Paper until 1 July 2025

ER -

Sharing Knowledge in Adaptive Learning Systems

Abstract

Keywords

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