Measuring VR QA Success with Key Performance Indicators (KPIs)

Author(s)	Komal Jasani
Country	United States
Abstract	VR, an industry that has grown rapidly in recent years, has many applications in different sectors, and to address these complex applications, proper QA is necessary for appropriate usability. However, it is challenging to determine the level of success of VR QA since it is a new concept that presents some challenges. This paper seeks to discuss the impact of KPIs in evaluating the success of VR QA. It includes technical efficiency, usefulness, features, and usage rates of the learning system's KPIs. The article also describes ways the VR QA can be assessed, including Automation Testing tools, End-user feedback, and Machine learning. Also, industry standards and future outlooks in the VR QA area are discussed in the context of today, and the idea of improvement and evolution of methods of measuring VR effectiveness is emphasized. For this reason, implementing these KPIs and measurement methods will enhance developers’ ability to ensure that the provision of VR applications meets the users, stakeholders, and industry standards’ expectations.
Field	Engineering
Published In	Volume 13, Issue 2, July-December 2022
Published On	2022-11-06
Cite This	Measuring VR QA Success with Key Performance Indicators (KPIs) - Komal Jasani - IJAIDR Volume 13, Issue 2, July-December 2022. DOI 10.5281/zenodo.14988577
DOI	https://doi.org/10.5281/zenodo.14988577
Short DOI	https://doi.org/g87cjc

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