https://orcid.org/0000-0002-1091-6392
Abstract
A performance evaluation matrix is based on questionnaires collected from users or customers to pinpoint the performance of a system operation and furthermore to locate the items that need to be improved to upgrade the performance of system operations. To achieve this, this article proposes a discrimination index and applies statistics inference to deduce confidence intervals of the discrimination index. Meanwhile, we refer to Buckley’s fuzzy testing method to construct a fuzzy affiliation function and address a fuzzy evaluation criterion for exploring the items considered critical to quality to overcome the complicated problems of the questionnaires’ sampling error and interviewees’ fuzzy linguistics. The advantages of the method in this article are that it keeps the simple filling pattern of Likert’s scale and provides efficacy of data collection. Subsequently, we reduce the fuzzy linguistics and questionnaires’ sampling error by statistics inference and fuzzy hypothesis testing. Finally, we use a case study with the computer-assisted language learning system to demonstrate an application of the proposed method.
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