Nadia Refat
Universiti Malaysia Pahang
11 Papers
30 Citations
Nadia Refat is an academic researcher from Universiti Malaysia Pahang. The author has contributed to research in topics: Computer science & Cognitive load. The author has an hindex of 5, co-authored 9 publications.
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Papers
Interactive Learning Experience-Driven Smart Communications Networks for Cognitive Load Management in Grammar Learning Context
Nadia Refat,Md. Arafatur Rahman,A. Taufiq Asyhari,Ibnu Febry Kurniawan,Md. Zakirul Alam Bhuiyan,Hafizoah Kassim +5 more
TL;DR: Empirical studies and numerical simulations show that the overall smart network-enabled e-grammar learning system has desirable characteristics to motivate learners and manage their overall cognitive load, which suggest the promising capability of the proposed system.
Reliable Decision Making of Accepting Friend Request on Online Social Networks
Md. Arafatur Rahman,Vitaliy Mezhuyev,Zakirul Alam Bhuiyan,S. M. Nazmus Sadat,Siti Aishah Binti Zakaria,Nadia Refat +5 more
TL;DR: A method for reliable decision making (RDM) of accepting friend request on OSNs in order to identify the attributes of a friend-to-be is proposed, which results indicated user's preferences for proposed method compared with the existing FRA methods.
MATT: A Mobile Assisted Tense Tool for Flexible m-Grammar Learning Based on Cloud-Fog-Edge Collaborative Networking
Nadia Refat,Md. Arafatur Rahman,A. Taufiq Asyhari,Hafizoah Kassim,Ibnu Febry Kurniawan,Mahbubur Rahman +5 more
TL;DR: With an appropriate condition of delay-tolerant network-enabled learning data exchange, the results suggest that the students’ cognitive load is low and motivational nature is high after using this system, which led them to perform more positively in the post-test evaluation.
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Cloud Enabled e-Glossary System: A Smart Campus Perspective
Musaddiq Majid Khan Al-Nadwi,Nadia Refat,Nafees Zaman,Arafatur Rahman,Zakirul Alam Bhuiyan,Ramdan Razali +5 more
- 11 Dec 2018
TL;DR: The quantitative research method is applied to validate the proposed system that provides the positive outcome and is an important research finding for vocabulary learning that can contribute to the building of smart campus exploiting the e-learning technologies.
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Evaluation of the Likelihood of Friend Request Acceptance in Online Social Networks
TL;DR: A method for evaluating the likelihood to become a friend in support of promoting hazard-free cyber environments is proposed and its favorable characteristics against existing methods in the current OSN platforms are proved.