Rating learning object quality with distributed bayesian belief networks: The why and the how

Vive Kumar, John Nesbit, Kate Han

Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

22 Citations (Scopus)

Abstract

As differing evaluation instruments are adopted in learning object repositories serving specialized communities of users, what methods can be adopted for translating evaluative data across instruments in order to share this data among different repositories? How can evaluation from different reviewers be properly integrated? How can explicit and implicit measures of preference and quality be combined to recommend objects to users? In this research we studied the application of Bayesian Belief Network (BBN) to the problem of insufficient and incomplete reviews during learning objects evaluation, and translating and integrating data among different quality evaluation instruments and measures. Two BBNs were constructed to probabilistically model relationships among different roles of reviewers as well as among items of different evaluation measurements. Initial testing using hypothetic data showed that the model was able to make potentially useful inferences about different dimensions of learning object quality. We further extend our model over geographic distances assuming that the reviewers would be distributed and that each reviewerwould change the underlying BBN network (to a certain extent) to suit his/her expertise. We highlight issues that arise due to a highly distributed and personalized BBN network that can be used to make valid inferences about learning object quality.

Original languageEnglish
Title of host publicationProceedings - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005
Pages685-687
Number of pages3
DOIs
Publication statusPublished - 2005
Event5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005 - Kaohsiung, Taiwan, Province of China
Duration: 5 Jul. 20058 Jul. 2005

Publication series

NameProceedings - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005
Volume2005

Conference

Conference5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005
Country/TerritoryTaiwan, Province of China
CityKaohsiung
Period5/07/058/07/05

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