A Bayesian network knowledge engineering and validation using structural and parameter learning a C-based intelligent tutoring system
College
College of Computer Studies
Document Type
Conference Proceeding
Source Title
Philippine Computing Science Congress
Publication Date
3-2019
Abstract
This paper presents our design and knowledge engineering aspect of a C-based Intelligent Tutoring System (ITS) using Bayesian Networks (BNs). We present and compare two Bayesian Networks constructed using alternative methods: one was constructed manually using domain knowledge, and the other BN was constructed using structural learning algorithms. Both networks were designed using examination results collected from 80 student-respondents. This data was used by the parameter learning algorithm to determine the conditional probability distributions of the nodes. Our analysis after performing parameter learning algorithm have shown that the resulting BN s beliefs are close to the beliefs defined in the manually constructed BN. However the BN constructed using structural learning algorithms was substantially different and we present our findings in this paper.
html
Recommended Citation
Limoanco, T. C., Guzman, J. S., & Sison, R. C. (2019). A Bayesian network knowledge engineering and validation using structural and parameter learning a C-based intelligent tutoring system. Philippine Computing Science Congress Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/14935
Disciplines
Computer Sciences
Keywords
Intelligent tutoring systems
Upload File
wf_no
