The Use of Artificial Intelligence with d/Deaf and Hard of Hearing Students: A Systematic Review

The major purpose of the present systematic review is to critically evaluate the literature on the use of artificial intelligence (AI) with d/Deaf and hard of hearing (d/Dhh) students. It is also of interest to analyze any existing studies on the use of AI to improve the reading skills of these students. In light of limited available investigations, it is important to describe the development of a funded AI reading project to be proffered as a model for future research. The studies reviewed provide various examples of the use of deep learning, machine learning, and AI applications for d/Dhh individuals. These studies are not directly related to reading comprehension. One of the studies examined indicated that an AI-based sign language recognition technique can be used for word and sentence recognition in the future. In addition, it was hypothesized that this technique will help students improve their vocabulary. It was also emphasized that the system not only facilitates alphabet recognition, but also can be extended to the teaching of more complex reading units that form the basis of literacy. In the funded AI reading project model, reading texts were developed for d/Dhh students. The Flesch-Kincaid Grade Level (Turkish version) readability formula was used to determine whether the texts were suitable for the first- and second-grade levels. The model has the potential to serve larger groups of students through more comprehensive databases with its scalable structure.