The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method

The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method

Entry qualifications are very important for the educational institution or educational providers to ensure quality graduate been produced. This paper presents the influence of gender, entry qualification and entry results towards the student performance in university. Total of 65 students were...

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Main Authors: M. M., Noor, K., Kadirgama, M. M., Rahman, M. R. M., Rejab, M. S. M., Sani, M. Y., Taib
Format: Conference or Workshop Item
Language:English
Published: 2009
Subjects:
LB2300 Higher Education
Online Access:http://umpir.ump.edu.my/id/eprint/1428/
http://umpir.ump.edu.my/id/eprint/1428/1/2009_P_MUCEET09_Gender_M.M.Noor_K.Kadirgama-Conference-.pdf
id ump-1428
recordtype eprints
spelling ump-14282018-01-23T02:00:09Z http://umpir.ump.edu.my/id/eprint/1428/ The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method M. M., Noor K., Kadirgama M. M., Rahman M. R. M., Rejab M. S. M., Sani M. Y., Taib LB2300 Higher Education Entry qualifications are very important for the educational institution or educational providers to ensure quality graduate been produced. This paper presents the influence of gender, entry qualification and entry results towards the student performance in university. Total of 65 students were randomly selected in faculty of mechanical engineering, University Malaysia Pahang. Entries qualifications are from Foundation Program, Higher Certificate of Malaysian Education (STPM) and Diploma Certificate. STPM is form six examinations in secondary school level. Multilayer Perceptron Neural Network (MPNN) method was used to measure and predict the student’s performance. Result from the study shows that gender not significant role but entry results plays important role. Good entry results student normally maintain their performance throughout the study and become excellent graduates. MPNN is an important tool to study the different type of variables for student performance. 2009 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/1428/1/2009_P_MUCEET09_Gender_M.M.Noor_K.Kadirgama-Conference-.pdf M. M., Noor and K., Kadirgama and M. M., Rahman and M. R. M., Rejab and M. S. M., Sani and M. Y., Taib (2009) The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method. In: Malaysian Technical Universities Conference on Engineering and Technology, 20-22 June 2009 , MS Garden Hotel, Kuantan, Pahang, Malaysia. . (Unpublished)
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic LB2300 Higher Education
spellingShingle LB2300 Higher Education
M. M., Noor
K., Kadirgama
M. M., Rahman
M. R. M., Rejab
M. S. M., Sani
M. Y., Taib
The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method
description Entry qualifications are very important for the educational institution or educational providers to ensure quality graduate been produced. This paper presents the influence of gender, entry qualification and entry results towards the student performance in university. Total of 65 students were randomly selected in faculty of mechanical engineering, University Malaysia Pahang. Entries qualifications are from Foundation Program, Higher Certificate of Malaysian Education (STPM) and Diploma Certificate. STPM is form six examinations in secondary school level. Multilayer Perceptron Neural Network (MPNN) method was used to measure and predict the student’s performance. Result from the study shows that gender not significant role but entry results plays important role. Good entry results student normally maintain their performance throughout the study and become excellent graduates. MPNN is an important tool to study the different type of variables for student performance.
format Conference or Workshop Item
author M. M., Noor
K., Kadirgama
M. M., Rahman
M. R. M., Rejab
M. S. M., Sani
M. Y., Taib
author_facet M. M., Noor
K., Kadirgama
M. M., Rahman
M. R. M., Rejab
M. S. M., Sani
M. Y., Taib
author_sort M. M., Noor
title The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method
title_short The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method
title_full The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method
title_fullStr The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method
title_full_unstemmed The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method
title_sort entry qualifications and gender analysis of student performance by using artificial intelligent method
publishDate 2009
url http://umpir.ump.edu.my/id/eprint/1428/
http://umpir.ump.edu.my/id/eprint/1428/1/2009_P_MUCEET09_Gender_M.M.Noor_K.Kadirgama-Conference-.pdf
first_indexed 2023-09-18T21:54:33Z
last_indexed 2023-09-18T21:54:33Z
_version_ 1777413992100134912

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