Analyzing the Usability of an E-Learning Application Using the Heuristics Evaluation Method

The rise of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$E$</tex>-Learning, especially during the COVID-19 pandemic, has highlighted the importance of evaluating its usability to improve the user experience and interface design of educational platforms. This study focuses on GreatNusa, an E-Learning platform by Bina Nusantara University. It uses heuristic evaluation principles to identify and address usability issues in its mobile application. The study adopts a quantitative-descriptive approach with data obtained from an online questionnaire completed by 473 respondents, predominantly undergraduate and diploma students. The analysis is based on 33 indicators obtained from previous research and aligned with the 10 heuristic evaluation principles, focusing on usability components such as Learnability, Efficiency, Memorability, Errors, and Satisfaction. The data is analyzed using SMARTPLS with SEM PLS for structural modeling. Results indicate that the variables; Efficiency, Memorability, and Satisfaction significantly affect usability while Learnability and Error do not show a significant impact. Overall, despite minor usability issues identified through this study, the design of GreatNusa's application is well-received, suggesting that it meets established usability standards and offers a satisfactory user experience. The findings provide actionable insights for enhancing the application's UI/UX, to ensure an even more user-friendly experience.

Authors

Institutions

Publication Details

Published
2024-08-29
DOI
https://doi.org/10.1109/icitacee62763.2024.10762770
Primary Topic
Varied Academic Research Topics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analyzing the Usability of an E-Learning Application Using the Heuristics Evaluation Method

Stephanie Surja, Sarinthar Julius Then
Varied Academic Research Topics
article

Analyzing the Usability of an E-Learning Application Using the Heuristics Evaluation Method

Stephanie Surja, Sarinthar Julius Then
article en

Abstract

The rise of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$E$</tex>-Learning, especially during the COVID-19 pandemic, has highlighted the importance of evaluating its usability to improve the user experience and interface design of educational platforms. This study focuses on GreatNusa, an E-Learning platform by Bina Nusantara University. It uses heuristic evaluation principles to identify and address usability issues in its mobile application. The study adopts a quantitative-descriptive approach with data obtained from an online questionnaire completed by 473 respondents, predominantly undergraduate and diploma students. The analysis is based on 33 indicators obtained from previous research and aligned with the 10 heuristic evaluation principles, focusing on usability components such as Learnability, Efficiency, Memorability, Errors, and Satisfaction. The data is analyzed using SMARTPLS with SEM PLS for structural modeling. Results indicate that the variables; Efficiency, Memorability, and Satisfaction significantly affect usability while Learnability and Error do not show a significant impact. Overall, despite minor usability issues identified through this study, the design of GreatNusa's application is well-received, suggesting that it meets established usability standards and offers a satisfactory user experience. The findings provide actionable insights for enhancing the application's UI/UX, to ensure an even more user-friendly experience.

Binus University (ID)
Openalex Percentile: Top 66%
Varied Academic Research Topics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.