Authors' ORCIDs
Nada Mohamed: https://orcid.org/0009-0003-0750-9395
Alshaimaa A. Tantawy: https://orcid.org/0000-0002-6476-9500
Article Type
Research Article
Abstract
Human-computer interaction (HCI) evaluation and optimization of user interfaces (UIs) constitute a complex multi-criteria decision-making challenge, marked by conflicting evaluation dimensions, subjective expert judgments, and inherent uncertainty in user experience assessment. Traditional evaluation approaches, such as heuristic expert reviews and user satisfaction surveys, rely on sharp, binary classifications that fail to capture the gradual and overlapping nature of human cognitive and affective states. This limitation necessitates a more robust uncertainty-aware methodology that can model the true complexity of HCI evaluation. This paper proposes a hybrid mathematical model that integrates various Multi-Criteria Decision Making (MCDM) techniques of Entropy, and Simple Additive Weighting (SAW) for the systematic evaluation and ranking of UI alternatives under the environment of uncertainty theory of Single-Valued Neutrosophic Sets (SVNS). This theory encodes each criterion assessment through truth (T), indeterminacy (I), and falsity (F) membership functions. It provides a principled mechanism for handling the vagueness and contradiction inherent in multi-modal HCI evaluation data. The TrSS component determines the hierarchical structure of evaluation criteria, SVN-Entropy computes objective weights for these criteria by measuring information variability, while SAW aggregates the weighted normalized scores to produce a final ranking of UI alternatives. The proposed model is validated through a case study in which five UI alternatives are evaluated across three HCI criteria by a panel of domain experts. Results demonstrate that the neutrosophic MCDM approach yields more nuanced and reliable UI rankings compared to conventional evaluation methods, effectively resolving conflicts among contradictory evaluation signals. This work contributes a replicable, uncertainty-aware decision support framework for UI optimization, with broader applicability to HCI research and human-centered system design.
Keywords
Human–Computer Interaction (HCI), User interface, SVNSMCDM, Uncertainty, UI optimization
How to Cite
Mohamed, Nada and Tantawy, Alshaimaa A.
(2026)
"Exploiting Uncertainty of Computational Methodology in Optimizing User Interface in Human-Computer Interaction,"
Neutrosophic Systems with Applications: Vol. 26:
Iss.
6, Article 2.
DOI: https://doi.org/10.63689/2993-7159.1346
