Critical Analysis of User Experience Evaluation Methods Focused on Deaf Users: A Systematic Literature Review

Context. User experience (UX) evaluation has played an important role in the software development lifecycle, as it helps determine whether a product effectively meets the needs of specific users. However, in the case of Deaf individuals, existing UX evaluation methods often fail to take into account the specific characteristics and needs of this community. Objective. This study focuses on analyzing the state of the art regarding the application of UX evaluation methods adapted to the specific characteristics of Deaf users, collecting each of these methods, evaluating their advantages and disadvantages, identifying the adaptations implemented, and discussing the results of each solution. Method. A systematic literature review (SLR) was conducted, consisting of three phases: (a) planning, (b) execution, and (c) reporting. The SLR was focused in finding relevant studies about UX evaluation for Deaf population. Also, a quality assessment process was conducted to ensure the reliability and validity of the collected data. The final reporting phase included both qualitative and quantitative analyses. Results. As a result, ten relevant studies were considered in this SLR. Five UX evaluation methods were identified, which were classified based on the collection of qualitative and quantitative data. Additionally, an analysis of the advantages and disadvantages of each method was conducted by reviewing the results of each proposal. Some of the most notable adaptations include the involvement of a sign language interpreter, the use of simple measurement scales, the independence from verbal information, the incorporation of graphic resources. Conclusion. The results highlight the need to develop UX evaluation methods that are more inclusive and accessible for Deaf individuals. Despite adaptations made to existing tools, they still show shortcomings in terms of communication and accessibility, which limits their effectiveness in software testing with Deaf users.