Data to evaluate the usability of an interactive system based on a judgment-based model

Area of Science:

• Computer Science
• Human-Computer Interaction
• Information Systems

Background:

• Usability evaluation of interactive systems is crucial for user satisfaction and system effectiveness.
• Existing methods may not fully capture the subjective nature of usability.
• Fuzzy logic offers a robust framework for handling imprecise and subjective data.

Purpose of the Study:

• To develop and present a judgment-based fuzzy multifactorial evaluation (MFE) model for assessing the usability of interactive systems.
• To integrate expert knowledge from Information Systems, Human-Computer Interaction, and Adaptive Learning Management Systems domains.
• To validate the model using empirical data and expert opinions.

Main Methods:

• Data collection involved literature review (180 articles from WoS, 2018-2019) and expert surveys.
• Component factor analysis using IBM SPSS Statistics was employed to classify interactive system objectives.
• A Mamdani-type fuzzy inference system (FIS) was designed in MATLAB for usability evaluation.

Main Results:

• The fuzzy multifactorial evaluation (MFE) model successfully integrated expert judgments and empirical data.
• The FIS model effectively evaluated usability based on four classes of interactive systems and five usability criteria.
• Expert opinions were crucial in defining fuzzy variables and system objectives.

Conclusions:

• The proposed fuzzy multifactorial evaluation (MFE) model provides a reliable and adaptable approach for usability assessment.
• Fuzzy logic enhances the evaluation of complex interactive systems by incorporating subjective expert insights.
• This research contributes a novel methodology for enhancing the understanding and evaluation of interactive system usability.