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Abstract

It is essential for teachers to effectively address the diverse needs of students within the classroom environment, encompassing variations in IQ, communication skills, problem-solving abilities, and mathematical proficiency. Ensuring the inclusion of CwSN (Children with Special Needs) is imperative to prevent social division in the classroom. While the department offers accommodations such as scribes, interpreters, or extra time for examinations, these measures may not fully address the specific needs of CwSN. This study explores the efficacy of employing hand gestures as a teaching tool for CwSN in computer science, particularly in the realm of number conversions. A machine learning-based tool has been developed and implemented to provide an inclusive and accessible approach, addressing the specific needs of students with learning and intellectual disabilities. Through a mixed-methods approach, the research aims to evaluate the impact of integrating hand gestures into the instruction of number conversions. This methodology offers a simplified and interactive approach, potentially enhancing comprehension, retention, and engagement among CwSN. By focusing on the mathematical aspects of the computer science syllabus, specifically number conversion, this method aims to streamline the learning process, requiring minimal arithmetic to perform conversions without the use of pen and paper. The hand gestures method significantly improved the effectiveness of teaching number conversions to Children with Special Needs (CwSN) in comparison to traditional approaches. This approach not only boosted their participation but also facilitated easier retention of the concepts.

First Page

254

Last Page

274

Ethics Approval

Yes

Declaration Statement

This research work is funded by Academic Special Cell, Department of General Education – Higher Secondary, Government of Kerala, India, as per order no HSE/6904/2023-Acd Spl2 dated 03-11-2023.

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