An intuitive number conversion system employing gestural recognition for students with special educational needs in Computer Science

Abstract

Duty of a teacher is to effectively engage the different types of students in the classroom into the teaching-learning environment. Each class has a variety of students varying in intelligence, communication, understanding levels, problem solving skills, learning and mathematical abilities. It is the need of the hour to make the differently abled learners with learning or intellectual disabilities to compete with regular students to avoid a social divide in class. Computer science curriculum has many topics/areas that pose learning difficulty for the differently abled. The problems faced by such learners were not taken care of sufficiently, which leaves them behind in the learning process. The paper proposes a hand gesture method, implemented using AI for number conversions, which can be used by teachers and differently abled learners. The efficiency of the hand gesture tool to understand hand gestures is tested for various classifiers and an average accuracy of 96.97 % is obtained across various number systems. The hand gesture based method is evaluated among learners and proved efficient in retention and recovery of concepts. Learners showed greater improvement from pre-test to post-test scores across all categories. This method proved very helpful in engaging students, enhancing understanding, enjoyable learning, notable clarity, effectiveness, and ease of use, making it a valuable educational tool.