Intelligent Tutoring System Using Bayesian Network for Vocational High Schools in Indonesia

Muhammad Ikhwan Burhan,Eko Sediyono,Kusworo Adi,T.R Soeprobowati,B Warsito,T Triadi Putranto

doi:10.1051/e3sconf/202131705027

Muhammad Ikhwan Burhan, Eko Sediyono + Show 4 more

Open Access

https://doi.org/10.1051/e3sconf/202131705027

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Abstract

The lack of personal tutorials during school hours caused the learning approach at Vocational High Schools to be less optimal, and the student's competence is not achieved maximumly. Some computer-based self-learning systems have been developed as solutions to these problems. Unfortunately, the system's weakness is that learning does not pay attention to the diversity of students' abilities. Based on those, this research proposes an Intelligent Tutoring System (ITS) model using Bayesian Network at Vocational High Schools (SMK) to determine the level of students' abilities and teach skills competency materials based on each student's ability level. This is quantitative research with quasi-experimental using one group pretest-posttest design. The research participants were 69 students of the Computer and Network Engineering expertise program at SMK Negeri 4 Gowa and SMK Negeri 1 Gowa, South Sulawesi Province, Indonesia. The results showed significant differences in students' learning outcomes after the use of the proposed ITS; in other words, the proposed ITS was effective in increasing the skill competency of Vocational High School Students. The evaluation results showed that the created Bayesian Network model had a high level of accuracy, reaching 84%.

Highlights

Vocational High School (SMK) is one of the educational institutions that aims at providing knowledge and skills to students who enter the employment field and produce the skilled employee needed by the community [1]
The Confusion Matrix is a table with four different combinations containing True Positive (TP), True Negative (TN), False Positive (FP), and False Negative (FN)
This research proposes an Intelligent Tutoring System (ITS) model using Bayesian Network in Vocational High Schools that can determine the level of the students' abilities and teach skills competency materials based on each student's ability level

Summary

Introduction

Vocational High School (SMK) is one of the educational institutions that aims at providing knowledge and skills to students who enter the employment field and produce the skilled employee needed by the community [1]. Some Some computer-based self-learning systems have been developed as solutions to these problems, including [2, 3], which are designed to provide alternative tutorials personally to vocational school students and improve their understanding at the same time. This solution becomes successful because many software is being developed to provide personal tutorials. The research assumes that the knowledge level of all students is the same This learning tutorial approach is not optimal and does not reflect personal guidance between students and teachers

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Conclusion