• Aug 09, 2018 News! Vol. 6, No. 4-No. 7, No. 3 has been indexed by EI(Inspec)!   [Click]
  • Aug 09, 2018 News!Good News! All papers from Volume 8, Number 3 have been indexed by Scopus!   [Click]
  • May 23, 2018 News![CFP] 2018 the annual meeting of IJMLC Editorial Board, ACMLC 2018, will be held in Ho Chi Minh, Vietnam, December 7-9, 2018   [Click]
Search
General Information
Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2018 Vol.8(5): 488-494 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2018.8.5.734

System Framework for an Intelligent Question Bank and Examination System

S. Janpla and P. Wanapiron
Abstract—This documentary research purposed to design the System Framework for an intelligent question bank and examination system. It was divided into three periods: (1) the synthesis for functions in the question bank system; (2) design of the system framework for an intelligent question bank and examination system; (3) to evaluate the appropriateness of the system framework for an intelligent question bank and examination system. A content analysis was applied to analyze the data. The results found that:
1. The question bank system consisted of five modules: 1. User Management, 2. Question Management, 3. Examination Management, 4. Evaluation Management and 5. Scoring Management.
2. The system framework of the question bank system consisted of three parts: 1. Relevant persons for the question bank system: teachers, students, and administrators; 2. Framework of the question bank system consisted of five main modules and 15 sub-modules: 1. User Management: 1.1 Login, 1.2 Edit Profiles, 1.3 Set Permission. 2. Question Management: 2.1 Item Management, 2.2 Setting Item, 2.3 Classification Machine Learning. 3. Examination Management: 3.1 Setting Examination, 3.2 Monitoring Examination, 3.3 Select Item Machine Learning. 4. Evaluation Management: 4.1 Evaluation Examination, 4.2 Suggestions, 4.3 Prediction Machine Learning. 5. Scoring Management: 5.1 View Scores, 5.2 View Item Statistics, 5.3 Export Scores and 3.NUMBER? Cloud Computing.
3. The evaluation of the appropriateness of the intelligent question bank system and examination system was checked by five experts regarding the question bank system and machine learning. Statistics used in this research were the mean and standard deviation. The results found that the rate of this framework was in “the most appropriate” (overall mean was 4.70 and S.D. was 0.50.).

Index Terms—Artificial intelligence, framework, question bank system, machine learning.

S. Janpla is with the Suan Sunandha Rajabhat University, Department of Computer Science, Bangkok, Thailand (e-mail: satien@ssru.ac.th).
P. Wanapiron is with Division of Information and Communication Technology for Education, King Mongkut’s University of Technology North Bangkok KMUTNB Bangkok, Thailand (e-mail: panita.w@hotmail.com).

[PDF]

Cite: S. Janpla and P. Wanapiron, "System Framework for an Intelligent Question Bank and Examination System," International Journal of Machine Learning and Computing vol. 8, no. 5, pp. 488-494, 2018.

Copyright © 2008-2018. International Journal of Machine Learning and Computing. All rights reserved.
E-mail: ijmlc@ejournal.net