IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Assisting Learners to Dynamically Adjust Learning Processes Through Software Agents

Assisting Learners to Dynamically Adjust Learning Processes Through Software Agents
View Sample PDF
Author(s): Weidong Pan (University of Technology-Sydney, Australia)and Igor Hawrysiewycz (University of Technology-Sydney, Australia)
Copyright: 2009
Pages: 13
Source title: Software Applications: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Pierre F. Tiako (Langston University, USA)
DOI: 10.4018/978-1-60566-060-8.ch077

Purchase

View Assisting Learners to Dynamically Adjust Learning Processes Through Software Agents on the publisher's website for pricing and purchasing information.

Abstract

To make online learning more productive, software agent technology has been applied to provide services for learners in order to assist them to construct knowledge in constructivist ways. This paper is focused on the application of software agents in assisting learners to dynamically adjust learning processes. Unlike pedagogical agents, the agents in this application do not hold domain knowledge but simply assist learners to get through learning processes by a variety of supportive services. They assist learners to develop personalized preferred learning plans and to guide them to dynamically adjust learning toward their goals. In this article, the online learning process is first investigated, and an approach to assisting learners to dynamically adjust learning is outlined. Then, the structure of the UOL (unit of learning) database that provides links between a practical learning scenario and the required services is explored. A multi-agent architecture for realizing the services is configured, and the roles of the involved agents are described. After that, the related agent algorithms for guiding learners to dynamically adjust learning are described.

Related Content

Babita Srivastava. © 2024. 21 pages.
Sakuntala Rao, Shalini Chandra, Dhrupad Mathur. © 2024. 27 pages.
Satya Sekhar Venkata Gudimetla, Naveen Tirumalaraju. © 2024. 24 pages.
Neeta Baporikar. © 2024. 23 pages.
Shankar Subramanian Subramanian, Amritha Subhayan Krishnan, Arumugam Seetharaman. © 2024. 35 pages.
Charu Banga, Farhan Ujager. © 2024. 24 pages.
Munir Ahmad. © 2024. 27 pages.
Body Bottom