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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.
Empirical analysis of language learning strategies for optimizing online language courses Lip, Rashidah; Salam, Sazilah; Mohamad, Siti Nurul Mahfuzah; Kar Mee, Cheong; Poh Ee, Tan; Ismail, Nurmaisarah; Mohd Yusoff, Azizul; Lestari, Uning; Ahmad Fesol, Siti Feirusz
International Journal of Evaluation and Research in Education (IJERE) Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v13i6.29418

Abstract

In today’s changing education world, online language classes are becoming more important. Recognizing the important role of the relationship between language learning strategies and students’ preferences, our empirical study examines the patterns or factors that explain the observed correlations among variables to provide insights in optimizing online language courses. Addressing a critical gap in the existing literature that has traditionally treated language learning strategies and online language education as distinct entities, our survey-based research collected comprehensive data from students enrolled in online language courses. Focused on six key language learning strategies: memory, cognitive, compensation, metacognitive, affective, and social. The research shows a delicate connection between these strategies and students’ preferences in online teaching mode. The empirical findings provide insights into certain strategies that work better for specific online learning methods. This helps us grasp the varied preferences of groups of students. This research enriches online language education by revealing an unexplored connection between strategies and preferences and provides a valuable resource for educators and course designers. The information given helps make online language classes better. It ensures that students learn languages more effectively online, considering their functional and practical needs in online learning.
Elevating Student Motivation: Constructing a Gamified Massive Open Online Courses using the MARC Framework Saputro, Rujianto Eko; Salam, Sazilah
Journal of Education Technology Vol. 8 No. 1 (2024): February
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jet.v8i1.67624

Abstract

Education is undergoing a profound revolution in the current era of digital technology, primarily due to the implementation of Massive Open Online Courses (MOOCs). These courses have facilitated worldwide accessibility to education of exceptional quality, transcending geographical and institutional limitations. This study aims to evaluates the implementation of gamification in Massive Open Online Courses (MOOCs) to enhance students' intrinsic motivation and graduation rates. Facing the challenge of low graduation rates in MOOCs, this study designed and implemented a Gamified MOOC (GMOOC) platform using a new gamification framework, MARC. Through an experimental method, this study involved 101 students and collected data through a questionnaire based on the Instructional Materials Motivation Survey (IMMS) and ARCS Model. The data was analyzed using Structural Equation Modelling (SEM), and the results showed that all MARC variables have high reliability and positively impact students' intrinsic motivation, with the Autonomy variable having the most significant impact. This study underlines the importance of a gamification framework in enhancing motivation and graduation rates in MOOCs, as well as the importance of considering the correct design elements and gamification components in the development of MOOCs. This study provides significant implications for developing and implementing effective and engaging MOOCs.
Issues and challenges in the implementation of micro-credential language courses: educators’ perspectives Lip, Rashidah; Salam, Sazilah; Mohamad, Siti Nurul Mahfuzah; Mohd Yusoff, Azizul; Shabarudin, Muhammad Syahmie; Musa, Mohd Kamaruzaman; Dewi, Laksmi; Khoirunnisa, Azizah Nurul
Journal of Education and Learning (EduLearn) Vol 19, No 3: August 2025
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/edulearn.v19i3.21820

Abstract

Micro-credential language courses have gained significant attention in the field of language education due to their potential to offer targeted and flexible learning experiences. However, the successful implementation of these courses relies on understanding the perceptions of language educators and addressing the associated issues and challenges. This study aims to identify language educators’ perceptions of online language learning platforms and micro-credential online language learning platforms and explore the issues and challenges in developing micro-credential language courses. Employing a quantitative approach, data was collected from 30 respondents from language educators at the centre for language learning, in a public university in Malaysia. Through survey questionnaires, quantitative insights into educators’ perceptions and experiences were gathered. The survey questionnaire gathered quantitative data on educators’ perceptions and experiences. This research sheds light on language educators’ perceptions of online language learning platforms and micro-credentials while identifying the challenges inherent in developing such courses. The findings underscore the significance of addressing these challenges to ensure the effective implementation of micro-credential-based language courses within online education contexts.
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.