Article: Design and development of a tangible machine learning-based object recognition and learning system for Indian kids suffering from visual agnosia Journal: International Journal of Technology Enhanced Learning (IJTEL) 2025 Vol.17 No.4 pp.437 - 457 Abstract: Children with visual agnosia have problems recognising and remembering basic objects. Although they are not visually impaired, they may be disregarded in educational environments. They suffer from the issue of limited identification capacity and are unable to retain what they have seen. A physical device using machine learning has been developed to assist individuals with difficulties in recalling and recognising basic objects like fruits and vegetables. The gadget can recognise objects and provide detailed descriptions within a 100-word limit. The designed equipment aids children in retaining knowledge of several fundamental items and enhances their inquisitiveness towards them. Consequently, they are able to gradually develop their cognitive abilities, including sensorimotor and object permanence capabilities. The object detection is performed via the convolutional neural network (CNN) method implemented in TensorFlow. The equipment effectively conducted tests on more than 20 children, examining a minimum of 30 distinct items. Inderscience Publishers - linking academia, business and industry through research

Title: Design and development of a tangible machine learning-based object recognition and learning system for Indian kids suffering from visual agnosia

Authors: Priyam A. Parikh; Heet Shah; Pinal Vaghela; Smruti Kankrecha

Addresses: Institute of Design, Nirma University, Ahmedabad, Gujarat, India ' Government Engineering College, Gujarat Technological University, Gandhinagar, Gujarat, India ' Chandubhai S. Patel Institute of Technology, Charotar University of Science and Technology, Gujarat, India ' L.D. College of Engineering, Gujarat Technological University, Gujarat, India

Abstract: Children with visual agnosia have problems recognising and remembering basic objects. Although they are not visually impaired, they may be disregarded in educational environments. They suffer from the issue of limited identification capacity and are unable to retain what they have seen. A physical device using machine learning has been developed to assist individuals with difficulties in recalling and recognising basic objects like fruits and vegetables. The gadget can recognise objects and provide detailed descriptions within a 100-word limit. The designed equipment aids children in retaining knowledge of several fundamental items and enhances their inquisitiveness towards them. Consequently, they are able to gradually develop their cognitive abilities, including sensorimotor and object permanence capabilities. The object detection is performed via the convolutional neural network (CNN) method implemented in TensorFlow. The equipment effectively conducted tests on more than 20 children, examining a minimum of 30 distinct items.

Keywords: visual agnosia; TensorFlow; object detection; machine learning; convolutional neural network; CNN.

DOI: 10.1504/IJTEL.2025.149378

International Journal of Technology Enhanced Learning, 2025 Vol.17 No.4, pp.437 - 457

Received: 18 Mar 2024
Accepted: 28 May 2024
Published online: 28 Oct 2025 *

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Title: Design and development of a tangible machine learning-based object recognition and learning system for Indian kids suffering from visual agnosia

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