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Developing Quantitative Assessment Metrics for Determining the Intelligence Level of a Human-Computer Interface

El Zarka, Ahmed
A Master of Science thesis in Computer Engineering by Ahmed El Zarka entitled, "Developing Quantitative Assessment Metrics for Determining the Intelligence Level of a Human-Computer Interface," submitted in January 2014. Thesis advisor is Dr. Tarik Ozkul. Available are both soft and hard copies of the thesis.
The quality of human-computer interfaces is becoming increasingly important as smart devices are becoming an essential part of our lives. Often what makes or breaks the market success of a device is not the hardware, but the quality and ease-of-use of the user interface of the smart device. Just as it is possible to discuss the intelligence level of machines in terms of their "machine intelligence quotient," it is becoming increasingly appropriate to discuss the "intelligence level" of a user interface. This new index would provide a quantitative assessment of user interface quality, and would be an indicator for rating the ease-of-use of the human-computer interface. In this study, a framework has been developed for the assessment of "user interface intelligence quotient" and is used to determine the quality of different smartphone interfaces. After conducting 200+ different human-smartphone experiments with popular smartphones and compiling the results using the methodologies developed, the results are compared to the actual opinion of the users. Results indicated that actual user opinions are in line with the calculated "intelligence" value of the smartphones. This study shows that there is a way to develop a "yardstick" to measure user satisfaction by using purely objective parameters. Search Terms: Machine Intelligence Quotient (MIQ), User Intelligence Quotient (UIQ), Mobile, User Interface, Smartphones, Usability, Fuzzy Logic, Sugeno, Mamdani, FIS.
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