Search results for author:"Mohd A Rahman"
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Understanding Learning Styles, Attitudes and Intentions in Using e-Learning System: Evidence from Brunei
World Journal of Education Vol. 5, No. 3 (2015) pp. 61–72
This study investigates the students' learning style, their attitudes about educational technologies in general and e-learning management system (e-LMS) in particular and their behavioral intentions to use the e-learning platform in a single...
International Journal of Emerging Technologies in Learning (iJET) Vol. 11, No. 10 (Oct 27, 2016) pp. 76–79
Discussion on teacher learning is often limited to a focus on formal professional development programmes. What and how teachers learn informally through their daily experiences is rarely explored. This research attempts to investigate how teachers...
International Journal of Emerging Technologies in Learning (iJET) Vol. 12, No. 5 (May 31, 2017) pp. 195–201
This interdisciplinary study integrates ICT in education through the innovation of an interactive audio-based application as a tool to enhance English language speaking skills among less proficient students. Drawing on the sociocultural perspective...
Blended Learning (BL) as Pedagogical Alternative to Teach Business Communication Course: Case Study of UUM Executive Diploma Program
Turkish Online Journal of Distance Education Vol. 13, No. 3 (July 2012) pp. 297–315
Globally, blended learning (BL) technologies have been increasingly applied in a variety of fields, both public and private sectors. In recent years, universities, public and private businesses and organizations are among those employing blended...
Nayan Nazrul Anuar; Hamid Hafifah; Suboh Mohd Zubir; Abdullah Noraidatulakma; Jaafar Rosmina; Mhd Nurul Ain; Hamid Mariatul Akma; Zubiri Nur Farawahida; Kamalul Azwa Shawani; Mohd Syakila; Kamaruddin Mohd Arman; A. Rahman
International Journal of Online Engineering Vol. 16, No. 7 (Jun 19, 2020) pp. 34–48
Cardiovascular disease (CVD) is the leading cause of deaths worldwide. In 2017, CVD contributed to 13,503 deaths in Malaysia. The current approaches for CVD prediction are usually invasive and costly. Machine learning (ML) techniques allow an...