ArticleHeliyon2024
User interface design in mobile learning applications: Developing and evaluating a questionnaire for measuring learners' extraneous cognitive load.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- AI System Usability and Learning Engagement in Nursing Simulation: Cross-Sectional Statistical Indirect Associations Through Extraneous Cognitive Load and Flow Experience.Nursing open · 2026Observational
- Digital Fatigue and Cognitive Load in E-Learning: Evidence From Nursing Students in Jordan.Nursing open · 2026Observational
- An integrated cognitive load-technology acceptance model for explaining behavioral intention to adopt Smart Physical Education Systems for extracurricular physical activity.Frontiers in psychology · 2026Article
- The Influence of the Information Richness of Interfaces on Consumers' Purchase Intention: The Sequential Mediating Effects of Cognitive Load, Mental Imagery, and Flow Experience.Behavioral sciences (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.