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Designing Personalized Online Learning Environments for Adult Learners

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Authors

Kim, Kyong-Jee; Yu, Byeong-Min

Issue Date
2002
Publisher
서울대학교 교육종합연구원
Citation
SNU Journal of Education Research, Vol.12, pp. 49-76
Keywords
personalized learningadult online learningcustomizing instructionadult learning
Description
2002
Abstract
Customizing instruction to meet individual needs is one of the foundational cornerstones of

today's learner-centered paradigms. Adult learners have a wide range of differences in their

backgrounds, interests, abilities, and learning styles; instruction, therefore, needs to be

designed in such a way as to meet the highly diverse needs of adult education settings. The

World Wide Web presents enormous potential for providing a technological environment for

the optimal delivery of personalized instruction for individual learners. It is argued, however,

that existing Web-based instruction fails to effectively customize instructions for individual

learners. Therefore, we are in need of an ongoing refinement and creativity in our generation

and treatment of theories of instruction geared towards the generation of personalized

learning environments. Here, the attempt is made to develop an instructional-design theory

for personalized online learning for online adult learners, with a special focus on the question

of solving ill-structured problems. Theory, on a general level, is discussed insofar as it has

emerged from the goals, preconditions, and underlying values, with an eye to the methods of

instruction that are optimal for achieving the goals. The methods of instruction in this

instructional-design theory are composed of four major components (goal-setting activities,

engaging in the learning task, performing the task, and reviewing and reflecting upon the

output of the task), with some corollaries detailing each major component. These methods

incorporate the use of such Web technology as the learner management system, the learning

objects system, and pedagogical agents to foster personalized learning process in online

learning environments.
ISSN
1225-5335
Language
English
URI
https://hdl.handle.net/10371/70623
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