Consensus on Criteria for Selection of Sign Language Mobile Apps: A Delphi Study

Abstract

In the rapidly evolving digital learning landscape, sign language mobile apps are vital in advancing sign language teaching. However, ensuring the quality of these apps remains a critical challenge. To address this gap, this study employs the fuzzy Delphi technique to establish a robust set of criteria for evaluating the quality of sign language mobile apps. By leveraging the collective wisdom and expertise of a panel of experts, the fuzzy Delphi technique facilitates a structured process for achieving consensus on the essential factors contributing to evaluating sign language mobile apps. Through rigorous rounds of iterative feedback and analysis, the study identifies a comprehensive list of reliable criteria encompassing various dimensions, including functionality, usability, accessibility, and pedagogical effectiveness. The criteria established through this method serve as a valuable resource for developers, educators, and clients in selecting and developing top-notch sign language mobile apps. Developers can use the criteria as a guide during the design and development stages, ensuring that their apps meet the highest quality and user experience standards. Educators can rely on the criteria as a checklist for evaluating and selecting appropriate apps that align with their teaching objectives and cater to the diverse learning needs of their students. Clients, such as educational institutions or individuals seeking sign language learning resources, can make informed decisions by referring to the established criteria, promoting the adoption of clear and impactful sign language mobile apps. This study emphasizes the significance of applying the fuzzy Delphi method in the context of sign language mobile app assessment. Involving experts from relevant fields ensures that the established criteria capture the multifaceted nature of compelling sign language learning experiences. Developing a comprehensive and reliable set of criteria contributes to improving existing apps and encourages innovation in creating new apps that better serve the needs of sign language learners. Overall, this research extends the knowledge base of sign language teaching in the digital age by providing a robust framework for assessing the quality of sign language mobile apps. The findings of this study empower stakeholders in the education and technology sectors to make informed decisions, fostering the advancement of sign language teaching and promoting inclusivity in digital learning environments.