Masyura Faudzi

Ms. Masyura Faudzi

Informatics, Universiti Tenaga Nasional, Putrajaya, Malaysia
orcid

Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 September 2024 in Heliyon
Verified
Journal Article
Open access
MFMasyura Faudzi
Masyura Faudzi
ZCZaihisma Che Cob
Zaihisma Che Cob
MGMasitah Ghazali
Masitah Ghazali
RORidha Omar
Ridha Omar
SSSharul Azim Sharudin
Sharul Azim Sharudin
Mobile learning is increasingly popular due to its flexibility in timing and location. However, challenges such as small screen sizes and poor user interface design can elevate learners' cognitive load, especially extraneous cognitive load, which hinders learning. Extraneous cognitive load, stemming from user interface design complexity, must be minimized to enhance learning focus. Currently, there is no dedicated instrument for measuring extraneous cognitive load specific to mobile learning user interface design. This study aims to develop and evaluate a subjective instrument for measuring extraneous cognitive load caused by user interface design in mobile learning applications. Two sets of experiments were conducted: pretesting to establish the instrument's foundation with a small participant group, followed by pilot experiments to validate the instruments and refine experimental procedures. The NASA-TLX score was used to analyze the relationship between overall cognitive load and extraneous load across various user interface criteria. Understanding these relationships can guide user interface improvements to reduce extraneous cognitive load. Challenges encountered during pretesting and pilot experiments included participant fatigue, scale reliability issues, and incomplete data collection. To enhance reliability, adjustments were made: tasks were reduced, the scale was expanded from a 4-point to a 10-point format, and facilitators thoroughly verified data before participants concluded sessions. Creating a tool to measure how user interface design impacts users' extraneous load is important because it is the UI design, not the mobile app's content that affects extraneous load. However, general methods for measuring cognitive load may not accurately identify problems with user interface design. Therefore, an extraneous load-based method is needed. This will also eventually improve usability.

16 January 2023 in Education Sciences
Verified
Journal Article
Open access
PDF file
MFMasyura Faudzi
Masyura Faudzi
ZCZaihisma Che Cob
Zaihisma Che Cob
RORidha Omar
Ridha Omar
SSSharul Azim Sharudin
Sharul Azim Sharudin
MGMasitah Ghazali
Masitah Ghazali
Online learning has replaced traditional face-to-face classroom instruction in the educational system. Learning via mobile, or mobile learning, is one of the solutions that most learners use since it is less expensive and easier to adopt on the go. However, in addition to hindering information transfer, issues such as small screen size and bad interface design can also make learning more cognitively demanding. This paper presents a systematic literature review on the user interface design of mobile learning applications based on the preferred reporting items for systematic reviews and meta-analyses approach. Articles selected for this study were published after the COVID-19 outbreak, between 2020 and 2022. The goal of this research was to outline the current user interface design criteria and guidelines applied when designing a mobile learning application and explore how these factors affect the learner’s cognitive load. It also aimed to identify potential research gaps and future opportunities in the creation of a UID guideline/framework for mobile learning. The findings of this study may be used as a guideline for designers, developers, educators, instructors, and others who are interested in creating a mobile learning application that provides learners with an effective knowledge and mobile learning experience.


16 November 2021
Verified
Book Chapter
Closed access
PDF file
FAFeninferina Azman
Feninferina Azman
AGAzimah Abdul Ghapar
Azimah Abdul Ghapar
MFMasyura Faudzi
Masyura Faudzi
HBHasventhran Baskaran
Hasventhran Baskaran
FRFiza Abdul Rahim
Fiza Abdul Rahim