The multiple intelligence classification of management graduates using two step cluster analysis
In this study, graduates multiple intelligences profile are the main interest in order to enhance the opportunities of the management graduates for employability. In order to measure and classify the multiple intelligences of graduate, Two Step Cluster Analysis is applied. The cluster is based on th...
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my.utm.604772021-12-08T08:15:35Z http://eprints.utm.my/id/eprint/60477/ The multiple intelligence classification of management graduates using two step cluster analysis Mohamed, Noorazilah Awang, Siti Rahmah HD28 Management. Industrial Management In this study, graduates multiple intelligences profile are the main interest in order to enhance the opportunities of the management graduates for employability. In order to measure and classify the multiple intelligences of graduate, Two Step Cluster Analysis is applied. The cluster is based on their demographic background and Gardner’s nine intelligences namely musical, spatial/visual, verbal/linguistic, mathematics/logical, bodily-kinaesthetic, interpersonal, intrapersonal, naturalist and spiritual. The framework and findings of this study are conducted at Faculty of Technology Management and Technopreneurship (FPTT), Universiti Teknikal Malaysia Melaka (UTeM). The nine intelligence types of the 137 management graduates had been successfully clustered into four more meaningful clusters based on their intelligence scores and characteristics that agree with the Gardner’s Multiple Intelligence theory. Penerbit UTM Press 2015 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/60477/1/NoorazilahMohamed2015_TheMultipleIntelligenceClassificationOfManagement.pdf Mohamed, Noorazilah and Awang, Siti Rahmah (2015) The multiple intelligence classification of management graduates using two step cluster analysis. Malaysian Journal of Fundamental and Applied Sciences, 11 (1). pp. 48-51. ISSN 2289-5981 http://dx.doi.org/10.11113/mjfas.v11n1.351 |
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HD28 Management. Industrial Management Mohamed, Noorazilah Awang, Siti Rahmah The multiple intelligence classification of management graduates using two step cluster analysis |
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In this study, graduates multiple intelligences profile are the main interest in order to enhance the opportunities of the management graduates for employability. In order to measure and classify the multiple intelligences of graduate, Two Step Cluster Analysis is applied. The cluster is based on their demographic background and Gardner’s nine intelligences namely musical, spatial/visual, verbal/linguistic, mathematics/logical, bodily-kinaesthetic, interpersonal, intrapersonal, naturalist and spiritual. The framework and findings of this study are conducted at Faculty of Technology Management and Technopreneurship (FPTT), Universiti Teknikal Malaysia Melaka (UTeM). The nine intelligence types of the 137 management graduates had been successfully clustered into four more meaningful clusters based on their intelligence scores and characteristics that agree with the Gardner’s Multiple Intelligence theory. |
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Article |
author |
Mohamed, Noorazilah Awang, Siti Rahmah |
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Mohamed, Noorazilah Awang, Siti Rahmah |
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Mohamed, Noorazilah |
title |
The multiple intelligence classification of management graduates using two step cluster analysis |
title_short |
The multiple intelligence classification of management graduates using two step cluster analysis |
title_full |
The multiple intelligence classification of management graduates using two step cluster analysis |
title_fullStr |
The multiple intelligence classification of management graduates using two step cluster analysis |
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The multiple intelligence classification of management graduates using two step cluster analysis |
title_sort |
multiple intelligence classification of management graduates using two step cluster analysis |
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Penerbit UTM Press |
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2015 |
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http://eprints.utm.my/id/eprint/60477/1/NoorazilahMohamed2015_TheMultipleIntelligenceClassificationOfManagement.pdf http://eprints.utm.my/id/eprint/60477/ http://dx.doi.org/10.11113/mjfas.v11n1.351 |
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