Vol. 1 No. 1 (2021): Human-Computer Interaction Perspectives
Articles

Usability Testing Methods: Investigating Usability Testing Methods and Techniques for Evaluating the Effectiveness and Efficiency of Interactive Systems

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  • Dr. Sofia Fernandez
Dr. Sofia Fernandez
Research Fellow in Usability Testing, University of Buenos Aires, Argentina
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Published 27-02-2024

Keywords

  • Usability testing,
  • interactive systems,
  • user experience,
  • evaluation methods,
  • heuristic evaluation,
  • cognitive walkthrough,
  • user testing,
  • usability metrics,
  • usability principles,
  • user satisfaction
    • ...More
    Less

How to Cite

[1]
D. S. Fernandez, “Usability Testing Methods: Investigating Usability Testing Methods and Techniques for Evaluating the Effectiveness and Efficiency of Interactive Systems”, Human-Computer Interaction Persp., vol. 1, no. 1, pp. 9–21, Feb. 2024.
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Abstract

This research paper explores the various usability testing methods and techniques employed to evaluate the effectiveness and efficiency of interactive systems. Usability testing is a crucial aspect of the design and development process, ensuring that the end product meets the needs and expectations of its users. This paper examines the key concepts of usability testing, including its importance, goals, and principles. It also provides a comprehensive overview of different usability testing methods and techniques, such as heuristic evaluation, cognitive walkthrough, and user testing. Furthermore, the paper discusses the applications of usability testing in different domains, highlighting its role in improving user satisfaction and product usability. By synthesizing existing literature and case studies, this paper aims to provide insights into the best practices and challenges associated with usability testing, ultimately contributing to the advancement of interactive system design.

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References

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  8. Pargaonkar, S. (2020). A Review of Software Quality Models: A Comprehensive Analysis. Journal of Science & Technology, 1(1), 40-53.
  9. Vyas, B. (2021). Ensuring Data Quality and Consistency in AI Systems through Kafka-Based Data Governance. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 10(1), 59-62.
  10. Pargaonkar, S. (2020). Bridging the Gap: Methodological Insights from Cognitive Science for Enhanced Requirement Gathering. Journal of Science & Technology, 1(1), 61-66.
  11. Rajendran, R. M. (2021). Scalability and Distributed Computing in NET for Large-Scale AI Workloads. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 10(2), 136-141.
  12. Pargaonkar, S. (2020). Future Directions and Concluding Remarks Navigating the Horizon of Software Quality Engineering. Journal of Science & Technology, 1(1), 67-81.