Article Per Year (5 Year)
p-Index From 2020 - 2025
1.235
P-Index
This Author published in this journals
All Journal International Journal of Evaluation and Research in Education (IJERE) Bulletin of Electrical Engineering and Informatics Journal of Education and Learning (EduLearn) Journal of Education Technology
Salam, Sazilah
Unknown Affiliation
Humanities Computer Science & IT Education Electrical & Electronics Engineering Library & Information Science Social Sciences Other

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search
Journal : Bulletin of Electrical Engineering and Informatics

 1 
Automatic prediction of learning styles: a comprehensive analysis of classification models Lestari, Uning; Salam, Sazilah; Choo, Yun-Huoy; Alomoush, Ashraf; Al Qallab, Kholoud
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7456

Abstract

Learning styles are a topic of interest in educational research about how individuals acquire and process information in offline or online learning. Identification of learning styles in the online learning environment is challenging. The existing approaches for the identification of learning styles are limited. This study aims to review the many learning styles characterized by various classification approaches toward the automatic prediction of learning styles from learning management system (LMS) datasets. A systematic literature review (SLR) was conducted to select and analyze the most pertinent and significant papers for automatically predicting learning styles. Fifty-two research papers were published between 2015-2023. This research divides analysis into five categories: the classification of learning style models, the collection of the collected dataset, learning styles based on the curriculum, research objectives related to learning styles, and the comprehensive analysis of learning styles. This study found that learning style research encompasses diverse theories, models, and algorithms to understand individual learning preferences. Statistical analysis, explicit data collection, and the Felder-Silverman model are prevalent in research, highlighting the significance of algorithm improvement for optimizing learning processes, particularly in computer science. The categorization and understanding of various methods offer valuable insights for enhancing learning experiences in the future.
Conceptual design model of engaging gamification mechanic for online courses Mohd Yusoff, Azizul; Salam, Sazilah; Mohamad, Siti Nurul Mahfuzah; Lip, Rashidah; Pudjoatmodjo, Bambang; Rahmalan, Hidayah; Mazlan, Azlimi
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7261

Abstract

Online learning, or e-learning, delivers educational content and teaching through various formats, ranging from self-paced courses to synchronous virtual classrooms. Gamification, the incorporation of game-like elements into non-game contexts, enhances engagement through rewards, reputation points, and goal setting. In higher education, researchers seek effective methods to stimulate learning and boost learner engagement. This study employs the analytic hierarchy process (AHP) to identify suitable gamification elements for three types of learner interaction, breaking down the decision-making problem into a hierarchy. Through a pairwise comparison matrix, priorities among hierarchy elements are established. The research involves 36 learners from a technical and vocational education and training (TVET) Public University, selecting the top best six gamification mechanics for each construct: virtual goods, wally’s game, rewards, trophies-badges, skill points, and peer grading. The proposed conceptual design will be implemented in online courses to assess learning engagement in cognitive, behavioural, and affective domains in higher education.
Factors influencing technology acceptance for ubiquitous public transportation services in tourism Shafei, Nurazlina; Salam, Sazilah; Ahmad Fesol, Siti Feirusz; Rusdi, Jack Febrian
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5822

Abstract

This article discusses the factors that influence public transport users and the driver’s intentions towards ubiquitous features for public transport services. This study used convenience sampling for selecting tourists and a purposive sample to select bus drivers, taxi drivers, and trishaw pullers in Melaka, Malaysia, a popular tourist destination. The users' dataset contains three main results: factors influencing users' use of public transportation services, levels of user satisfaction with existing public transportation services, and elements influencing how often people choose to use the suggested ubiquitous features for public transportation services. The drivers' dataset, on the other hand, is divided into two primary sections: variables influencing drivers in delivering public transportation services and factors influencing drivers' adoption of the suggested ubiquitous features for public transportation services. The analysis included descriptive statistics on factors influencing users and drivers in using public transportation services, levels of user satisfaction with existing public transportation services, and factors influencing users' and drivers' adoption of proposed ubiquitous features for public transportation services. The findings can be used to investigate the demand for on-time delivery from public transport services.
Screening capabilities for the 3D dyscalculia identification game framework Pudjoatmodjo, Bambang; Salam, Sazilah; Naim Che Pee, Ahmad; Aherliwan Rudavan, Rikman; Setijadi Prihatmanto, Ary
Bulletin of Electrical Engineering and Informatics Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i4.8765

Abstract

Dyscalculia, a learning difficulty in mathematics, remains a concealed challenge affecting individuals of average intelligence or remarkable creativity. This inconspicuous disability often leads teacher to misinterpret students as lacking intellect. Regrettably, this condition can prompt students to disengage from routine activities, resulting in diminished performance and self-confidence. To address this issue, our research introduces a serious game framework, namely the “3D-dyscalculia identification game framework” (3D-DIG framework), integrating a screening feature aimed at detecting mathematical shortcomings in students. This paper focuses on detailing the screening feature, wherein a Petri net structure orchestrates its functionality within the 3D game environment. Specifically, our study highlights how this feature assesses and captures potential student deficiencies during work on game challenges. Employing game engine, and web server technologies, the dyscalculia screening feature captures students' responses, enabling an evaluation of their mathematical proficiency. Analysis of student data affirms that the screening feature's in identifying potential mathematics-related deficiencies. Moreover, the 3D game incorporates a distinctive element: it notifies teachers when a student surpasses a 60-second threshold while solving a problem, facilitating timely interventions. By offering actionable insights, the framework empowers teacher to identify student with the mathematics' deficiency and support the student with the appropriate intervention.
Co-Authors Aherliwan Rudavan, Rikman Ahmad Fesol, Siti Feirusz Al Qallab, Kholoud Alomoush, Ashraf Bambang Pudjoatmodjo Choo, Yun-Huoy Ismail, Nurmaisarah Kar Mee, Cheong Khoirunnisa, Azizah Nurul Laksmi Dewi, Laksmi Lip, Rashidah Mazlan, Azlimi Mohamad, Siti Nurul Mahfuzah Mohd Yusoff, Azizul Musa, Mohd Kamaruzaman Naim Che Pee, Ahmad Poh Ee, Tan Rahmalan, Hidayah Rujianto Eko Saputro Rusdi, Jack Febrian Setijadi Prihatmanto, Ary Shabarudin, Muhammad Syahmie Shafei, Nurazlina Uning Lestari