Early Admission Selection Process Into Sixth Form Science Streams Using Neural Networks Model

The purpose of this study is to investigate and offer a model, based on Neural Networks Theory, capable of selecting successful students for early admission into sixth form science streams. This model would be able to perform the intended selection process even before the results of the Sijil Pelaja...

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Main Author:	Wong, Tuck Sung
Format:	Thesis
Language:	eng eng
Published:	2000
Subjects:	QA76 Computer software
Online Access:	https://etd.uum.edu.my/226/1/WONG_TUCK_SUNG_-_Early_admission_selection_process_into_sixth_form_science_streams_using_neural_networks_model.pdf https://etd.uum.edu.my/226/2/1.WONG_TUCK_SUNG_-_Early_admission_selection_process_into_sixth_form_science_streams_using_neural_networks_model.pdf
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id	my-uum-etd.226
record_format	uketd_dc
spelling	my-uum-etd.2262022-06-07T04:49:29Z Early Admission Selection Process Into Sixth Form Science Streams Using Neural Networks Model 2000 Wong, Tuck Sung Sekolah Siswazah Sekolah Siswazah QA76 Computer software The purpose of this study is to investigate and offer a model, based on Neural Networks Theory, capable of selecting successful students for early admission into sixth form science streams. This model would be able to perform the intended selection process even before the results of the Sijil Pelajaran Malaysia (SPM) are announced. The main benefit of this early admission was to allow students to start their classes early and to complete their demanding syllabus on time. The noble motive was to save time and to prevent time wasting, which would be true if students had to wait until the examination results are announced before they could start their classes. A neural networks solution, using Multi Layer Perceptron (MLP) and Steepest Gradient Descent algorithm, was studied to offer a better model to select students more meticulously. A total of 1488 data samples from ten secondary schools in the silver state of Perak, consisting of past-year Form 4 and Form 5 internal examination results, were collected in order to be trained and tested using the Neural Connection Version 2 software. A correct prediction of 92.18% accuracy was achieved using this Neural Networks model. Analysis of the data showed a reasonably strong correlation between the input variables, which consisted of subjects’ marks, aggregates and grades achieved, with the targeted output variable, which was the offer to continue with Sixth Form. It also showed that the data were only slightly skewed and were normally distributed. The trained Neural Networks model was found to produce a comparable accuracy when applied to other data from either only boys or girls schools, and from either urban or rural schools. 2000 Thesis https://etd.uum.edu.my/226/ https://etd.uum.edu.my/226/1/WONG_TUCK_SUNG_-_Early_admission_selection_process_into_sixth_form_science_streams_using_neural_networks_model.pdf text eng public https://etd.uum.edu.my/226/2/1.WONG_TUCK_SUNG_-_Early_admission_selection_process_into_sixth_form_science_streams_using_neural_networks_model.pdf text eng public masters masters Universiti Utara Malaysia
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
topic	QA76 Computer software
spellingShingle	QA76 Computer software Wong, Tuck Sung Early Admission Selection Process Into Sixth Form Science Streams Using Neural Networks Model
description	The purpose of this study is to investigate and offer a model, based on Neural Networks Theory, capable of selecting successful students for early admission into sixth form science streams. This model would be able to perform the intended selection process even before the results of the Sijil Pelajaran Malaysia (SPM) are announced. The main benefit of this early admission was to allow students to start their classes early and to complete their demanding syllabus on time. The noble motive was to save time and to prevent time wasting, which would be true if students had to wait until the examination results are announced before they could start their classes. A neural networks solution, using Multi Layer Perceptron (MLP) and Steepest Gradient Descent algorithm, was studied to offer a better model to select students more meticulously. A total of 1488 data samples from ten secondary schools in the silver state of Perak, consisting of past-year Form 4 and Form 5 internal examination results, were collected in order to be trained and tested using the Neural Connection Version 2 software. A correct prediction of 92.18% accuracy was achieved using this Neural Networks model. Analysis of the data showed a reasonably strong correlation between the input variables, which consisted of subjects’ marks, aggregates and grades achieved, with the targeted output variable, which was the offer to continue with Sixth Form. It also showed that the data were only slightly skewed and were normally distributed. The trained Neural Networks model was found to produce a comparable accuracy when applied to other data from either only boys or girls schools, and from either urban or rural schools.
format	Thesis
qualification_name	masters
qualification_level	Master's degree
author	Wong, Tuck Sung
author_facet	Wong, Tuck Sung
author_sort	Wong, Tuck Sung
title	Early Admission Selection Process Into Sixth Form Science Streams Using Neural Networks Model
title_short	Early Admission Selection Process Into Sixth Form Science Streams Using Neural Networks Model
title_full	Early Admission Selection Process Into Sixth Form Science Streams Using Neural Networks Model
title_fullStr	Early Admission Selection Process Into Sixth Form Science Streams Using Neural Networks Model
title_full_unstemmed	Early Admission Selection Process Into Sixth Form Science Streams Using Neural Networks Model
title_sort	early admission selection process into sixth form science streams using neural networks model
granting_institution	Universiti Utara Malaysia
granting_department	Sekolah Siswazah
publishDate	2000
url	https://etd.uum.edu.my/226/1/WONG_TUCK_SUNG_-_Early_admission_selection_process_into_sixth_form_science_streams_using_neural_networks_model.pdf https://etd.uum.edu.my/226/2/1.WONG_TUCK_SUNG_-_Early_admission_selection_process_into_sixth_form_science_streams_using_neural_networks_model.pdf
_version_	1747826865164255232

Early Admission Selection Process Into Sixth Form Science Streams Using Neural Networks Model

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