Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Evaluation and Research in Education (IJERE)
Zainab Othman
Universiti Teknologi Mara
Computer Science & IT Education Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
An educational game on the theories of driver education curriculum: An evaluation Zainab Othman; Nurul Hidayah Mat Zain; Ismassabah Ismail; Sharifah Affandi; Nor Azida Mohamed Noh; Anita Mohd Yasin
International Journal of Evaluation and Research in Education (IJERE) Vol 9, No 4: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v9i4.20659

Abstract

The purpose of this study was to evaluate the effectiveness of using an educational game application among driving school students on their understanding of driving rules and regulations. The application was developed and named as An Educational Game on the Theories of Driver Education Curriculum (DEC) to help students improve their visualization, understanding and memorization of the theories of driving rules and regulations as well as to be more prepared before taking the driving theory test. A preliminary study was conducted and it indicated that students had a hard time in visualizing, understanding and memorizing the theories of driving. The Game Development Life Cycle (GDLC) was implemented as a methodology to develop the DEC application which consists of initiation, pre-production, production, testing, beta, and release phases. The effectiveness of the DEC application was measured by Game-Based Learning Evaluation Model (GEM). The findings indicated that educational game helped students to visualize, memorize and understand the theories of driving easily.
A linear regression approach to predicting salaries with visualizations of job vacancies: a case study of Jobstreet Malaysia Khyrina Airin Fariza Abu Samah; Nurqueen Sayang Dinnie Wirakarnain; Raseeda Hamzah; Nor Aiza Moketar; Lala Septem Riza; Zainab Othman
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i3.pp1130-1142

Abstract

This study explicitly discusses helping job seekers predict salaries and visualize job vacancies related to their future careers. Jobstreet Malaysia is an ideal platform for discovering jobs across the country. However, it is challenging to identify these jobs, which are organized according to their respective and specific courses. Therefore, the linear regression approach and visualization techniques were applied to overcome the problem. This approach can provide predicted salaries, which is useful as this enables job seekers to choose jobs more easily based on their salary expectations. The extracted Jobstreet data runs the pre-processing, develops the model, and runs on real-world data. A web-based dashboard presents the visualization of the extracted data. This helps job seekers to gain a thorough overview of their desired employment field and compare the salaries offered. The system’s reliability as tested using mean absolute error, the functionality test was performed according to the use case description, and the usability test was performed using the system usability scale. The reliability results indicate a positive correlation with the actual values. The functionality test produced a successful result, and a score of 96.58% was achieved for the system usability scale result, proving the system grade is ‘A’ and usable.
Co-Authors Anita Mohd Yasin Ismassabah Ismail Khyrina Airin Fariza Abu Samah Lala Septem Riza Nor Aiza Moketar Nor Azida Mohamed Noh Nurqueen Sayang Dinnie Wirakarnain Nurul Hidayah Mat Zain Raseeda Hamzah Sharifah Affandi