A MULTI AGENT INTELLIGENT TUTORING SYSTEM BASED ON BAYESIAN NETWORK

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

MONTAZER GH.A.; SABERI N.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Technology of Education Journal Year:2011 | Volume:5 | Issue:2 Page(s): 87-99

Download Full-Text

Persian Verion

View:

1,234

Download:

Cites:

Information Journal Paper

Title

A MULTI AGENT INTELLIGENT TUTORING SYSTEM BASED ON BAYESIAN NETWORK

Author(s)

MONTAZER GH.A. | SABERI N. | Issue Writer Certificate

Keywords

E-LEARNINGQ2

INTELLIGENT TUTORING SYSTEM(ITS)Q3

ITEM RESPONSE THEORY(IRT)Q2

LEARNING STYLEQ3

BAYESIAN NETWORKQ3

MULTI AGENT ARCHITECTUREQ3

Abstract

Environmental monitoring for extraction of learner’s features and accurately learner modeling is a time and cost consuming task. This paper proposes a flexible framework using agent architecture capabilities in learners’ monitoring and also in optimization of Intelligent Tutoring subsystems interactions. In this research learner’s learning approaches have been recognized by LEARNING STYLE theory then their uncertainty has been reduced by BAYESIAN NETWORK. This framework prepares recommendations by combination of learners’ LEARNING STYLE and learner’s abilities (that are computed by Item Response Theory (IRT)) for three groups: learners, tutors and system designer. The architecture of proposed tutoring system has been presented in three layers. In middle layer there are four agents that monitor learners, create learner’s model, update it and prepare some recommendations based on courseware features, learner’s abilities and his/her LEARNING STYLE. A study was conducted on 30 Computer Engineering students during one semester. The implementation of the proposed system on participants indicates an increase in all evaluation factors, for example it doubles educational success rate and learner’s satisfaction rate.

Cites

No record.

References

Cite

APA: Copy

MONTAZER, GH.A., & SABERI, N.. (2011). A MULTI AGENT INTELLIGENT TUTORING SYSTEM BASED ON BAYESIAN NETWORK. JOURNAL OF TECHNOLOGY OF EDUCATION (JOURNAL OF TECHNOLOGY AND EDUCATION), 5(2), 87-99. SID. https://sid.ir/paper/155362/en

Vancouver: Copy

MONTAZER GH.A., SABERI N.. A MULTI AGENT INTELLIGENT TUTORING SYSTEM BASED ON BAYESIAN NETWORK. JOURNAL OF TECHNOLOGY OF EDUCATION (JOURNAL OF TECHNOLOGY AND EDUCATION)[Internet]. 2011;5(2):87-99. Available from: https://sid.ir/paper/155362/en

IEEE: Copy

GH.A. MONTAZER, and N. SABERI, “A MULTI AGENT INTELLIGENT TUTORING SYSTEM BASED ON BAYESIAN NETWORK,” JOURNAL OF TECHNOLOGY OF EDUCATION (JOURNAL OF TECHNOLOGY AND EDUCATION), vol. 5, no. 2, pp. 87–99, 2011, [Online]. Available: https://sid.ir/paper/155362/en

Related Journal Papers