Adaptive e-learning using ECpAA rules, Bayesian models, and group profile and performance data

Authors: Jeon, Sanghyun S.¹; Su, Stanley Y.W.²

Source: International Journal of Learning Technology, Volume 5, Number 4, March 2010 , pp. 415-434(20)

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Abstract:

An e-learning system must be capable of gathering and correctly evaluating a learner's profile and performance data in order to deliver individualised instruction to the learner. However, the learner's data can be incomplete, inaccurate and/or contradictory. They can also be correlated. This paper aims to alleviate these data problems by evaluating the data of each new learner probabilistically based on the data of earlier learners. Our probabilistic rule model allows our system to apply adaptation rules to examine learners' data at various stages of a learning activity, and determine the suitable actions to take to personalise the instruction. Adaptation rules are processed by a rule engine and a Bayesian model processor to achieve adaptive content search and selection, adaptive processing of learning objects, and continuous improvement on the accuracy of learner evaluation.

Keywords: COMPUTING AND MATHEMATICS; Communications and Mobile Technology; Computing Science, Applications and Software; Information Systems and Technology; Internet and Web Services; EDUCATION, KNOWLEDGE AND LEARNING; Learning and Human Resources Development

Document Type: Research article

DOI: http://dx.doi.org/10.1504/IJLT.2010.038776

Affiliations: 1: University of Florida, Database Systems R&D Center, Gainesville, FL 32611, USA. 2: University of Florida, Database Systems R&D Center, Gainesville, FL 32611, USA

Publication date: 2010-03-01

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International Journal of Learning and Technology is an international, refereed, scholarly journal providing an interdisciplinary forum for the presentation and discussion of important ideas, concepts, and exemplars that can deeply influence the role of learning technologies in learning and instruction. This unique and dynamic journal focuses on the epistemological thrust of learning vis-�-vis instruction and the technologies and tools that support the process. International Journal of Learning and Technology
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Adaptive e-learning using ECpAA rules, Bayesian models, and group profile and performance data

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