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Multilayer Perceptron Artificial Neural Network Model on assessing early mathematical knowledge behaviours and Todd-Acts mobile application development

In modern culture, mathematics is the primary tool for comprehending science, engineering, and economics. Mathematics has historically been viewed as the primary measure of human intellect. Since the early stages, certain industrialised countries have been carefully considering the subject of foster...

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Main Authors: Mustafa, Zaida, Ahmad Kamaruddin, Saadi, Md Ghani, Nor Azura, Mohamad, Hamidah, Abdul Aziz, Muhammad Noor
Format: Article
Language:English
Published: UUM Press 2022
Subjects:
QA75 Electronic computers. Computer science
Online Access:https://repo.uum.edu.my/id/eprint/29082/1/JCIA%2001%2001%202022%2019-41.pdf
https://e-journal.uum.edu.my/index.php/jcia/article/view/14496
https://repo.uum.edu.my/id/eprint/29082/
https://e-journal.uum.edu.my/index.php/jcia/article/view/14496
https://e-journal.uum.edu.my/index.php/jcia/article/view/14496
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spelling my.uum.repo.290822023-02-12T08:22:34Z https://repo.uum.edu.my/id/eprint/29082/ Multilayer Perceptron Artificial Neural Network Model on assessing early mathematical knowledge behaviours and Todd-Acts mobile application development Mustafa, Zaida Ahmad Kamaruddin, Saadi Md Ghani, Nor Azura Mohamad, Hamidah Abdul Aziz, Muhammad Noor QA75 Electronic computers. Computer science In modern culture, mathematics is the primary tool for comprehending science, engineering, and economics. Mathematics has historically been viewed as the primary measure of human intellect. Since the early stages, certain industrialised countries have been carefully considering the subject of fostering and generating geniuses among their people. This is because they recognise that individuals learn or remember knowledge the fastest throughout their first four years due to the prefrontal cortex’s resiliency. This vital period of human existence needs careful consideration. Previous study has revealed that a person’s mathematical skills develop from the day he or she is born. According to science, a person’s capacity to acquire math abilities allows them to develop many other talents faster, and infants are no exception. In this study, we looked at the behaviours or modules that contribute to the development of arithmetic skills or capacities in newborns from birth (0 months) to 4 years old (48 months). In this study, a two-layer neural network with tansig transfer function in the first layer and purelin transfer function in the second layer was used. Because many parents and instructors are focused on the programmes offered at childcare facilities, or the so-called nursery, Montessori, or kindergarten, an innovative mobile application called ‘Todd- Acts’ was created. This mobile application aims to assist parents and teachers with standardised modules that they can practise at home or on their premises, primarily to improve the arithmetic skills of babies in the five critical stages of human life: 0 to 6 months, 6 to 12 months, 12 to 24 months, 24 to 36 months, and 36 to 48 months. UUM Press 2022 Article PeerReviewed application/pdf en cc4_by https://repo.uum.edu.my/id/eprint/29082/1/JCIA%2001%2001%202022%2019-41.pdf Mustafa, Zaida and Ahmad Kamaruddin, Saadi and Md Ghani, Nor Azura and Mohamad, Hamidah and Abdul Aziz, Muhammad Noor (2022) Multilayer Perceptron Artificial Neural Network Model on assessing early mathematical knowledge behaviours and Todd-Acts mobile application development. Journal of Computational Innovation and Analytics (JCIA), 01 (01). pp. 19-41. ISSN 2821-3408 https://e-journal.uum.edu.my/index.php/jcia/article/view/14496 https://e-journal.uum.edu.my/index.php/jcia/article/view/14496 https://e-journal.uum.edu.my/index.php/jcia/article/view/14496
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutional Repository
url_provider http://repo.uum.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Mustafa, Zaida
Ahmad Kamaruddin, Saadi
Md Ghani, Nor Azura
Mohamad, Hamidah
Abdul Aziz, Muhammad Noor
Multilayer Perceptron Artificial Neural Network Model on assessing early mathematical knowledge behaviours and Todd-Acts mobile application development
description In modern culture, mathematics is the primary tool for comprehending science, engineering, and economics. Mathematics has historically been viewed as the primary measure of human intellect. Since the early stages, certain industrialised countries have been carefully considering the subject of fostering and generating geniuses among their people. This is because they recognise that individuals learn or remember knowledge the fastest throughout their first four years due to the prefrontal cortex’s resiliency. This vital period of human existence needs careful consideration. Previous study has revealed that a person’s mathematical skills develop from the day he or she is born. According to science, a person’s capacity to acquire math abilities allows them to develop many other talents faster, and infants are no exception. In this study, we looked at the behaviours or modules that contribute to the development of arithmetic skills or capacities in newborns from birth (0 months) to 4 years old (48 months). In this study, a two-layer neural network with tansig transfer function in the first layer and purelin transfer function in the second layer was used. Because many parents and instructors are focused on the programmes offered at childcare facilities, or the so-called nursery, Montessori, or kindergarten, an innovative mobile application called ‘Todd- Acts’ was created. This mobile application aims to assist parents and teachers with standardised modules that they can practise at home or on their premises, primarily to improve the arithmetic skills of babies in the five critical stages of human life: 0 to 6 months, 6 to 12 months, 12 to 24 months, 24 to 36 months, and 36 to 48 months.
format Article
author Mustafa, Zaida
Ahmad Kamaruddin, Saadi
Md Ghani, Nor Azura
Mohamad, Hamidah
Abdul Aziz, Muhammad Noor
author_facet Mustafa, Zaida
Ahmad Kamaruddin, Saadi
Md Ghani, Nor Azura
Mohamad, Hamidah
Abdul Aziz, Muhammad Noor
author_sort Mustafa, Zaida
title Multilayer Perceptron Artificial Neural Network Model on assessing early mathematical knowledge behaviours and Todd-Acts mobile application development
title_short Multilayer Perceptron Artificial Neural Network Model on assessing early mathematical knowledge behaviours and Todd-Acts mobile application development
title_full Multilayer Perceptron Artificial Neural Network Model on assessing early mathematical knowledge behaviours and Todd-Acts mobile application development
title_fullStr Multilayer Perceptron Artificial Neural Network Model on assessing early mathematical knowledge behaviours and Todd-Acts mobile application development
title_full_unstemmed Multilayer Perceptron Artificial Neural Network Model on assessing early mathematical knowledge behaviours and Todd-Acts mobile application development
title_sort multilayer perceptron artificial neural network model on assessing early mathematical knowledge behaviours and todd-acts mobile application development
publisher UUM Press
publishDate 2022
url https://repo.uum.edu.my/id/eprint/29082/1/JCIA%2001%2001%202022%2019-41.pdf
https://e-journal.uum.edu.my/index.php/jcia/article/view/14496
https://repo.uum.edu.my/id/eprint/29082/
https://e-journal.uum.edu.my/index.php/jcia/article/view/14496
https://e-journal.uum.edu.my/index.php/jcia/article/view/14496
_version_ 1758580952794136576
score 13.211869

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