Integrating Computing and Analysis in the Development of Interactive Quizzes for Sign Language Learning
Arifa Ashrafi, Victor Sergeevich Mokhnachev, Mohammed H. Uvaysov, Evgenii P. Medvedev · 2025
This paper outlines the innovative use of integrating computing and data analysis in developing the interactive quiz platform for sign language learning. With an increasing demand for effective educational strategies, the aim is to enhance the traditional learning methods by using modern technologies to create engaging, adaptive experiences for hearing impaired students. The interactive quizzes incorporate multimedia elements, including video demonstrations and real-time feedback, to foster a deeper understanding of sign language. By utilizing data analytics, it is possible to monitor learner progress, adaptation in real-time, and provide personalized learning pathways that address individual needs. Usability tests and pilot studies evaluate the efficacy of these quizzes in enhancing memory, comprehension, and practical usage of sign language among diverse learners. The primary findings suggest that the integration of computing and analysis significantly improves learner engagement and outcomes, showing the scientific novelty of this study. This research highlights the transformative potential of interactive educational technologies in making sign language learning more accessible and effective for a varied demographic as a multilingual sign language platform is aimed to develop. Through these innovations, it is supposed to significantly impact the improvement of language education.