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Measuring the perceived multiple intelligence of people with epilepsy via inverse fuzzy algorithms

Awang, Siti Rahmah and Ahmad, Tahir and Raja Mohamad Yusoff, Raja Mohamad Fairuz (2015) Measuring the perceived multiple intelligence of people with epilepsy via inverse fuzzy algorithms. In: 1st International Conference on Theory and Practice, 5-6 Dec, 2015, Australia.

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Official URL: http://apiar.org.au/?conference=1st-international-...


Among the challenging problems faced by People with Epilepsy (PWE) are under-employment and unemployment. Regardless of their qualification and experience, many PWE claim to have been denied the same opportunities given to other people even at present when there are many suitable jobs for them to choose from. Human resource personnel, however, need reliable information about the PWE before they can be hired. Inverse Ability Test of Epilepsy (i-ATIE), a psychometric test was developed to meet their need for this purpose and was constructed by combining Howard Gardner’s Multiple Intelligence theory with statistical procedures. The test development started with Fuzzy Inverse ATIE (FIA) algorithm where this algorithm was incorporated into a crisp Logistic Regression model to obtain the best intelligence parameters that would be garnered to maximize the employment probability of people with epilepsy (PWE). A computer programme using C-Sharp programming language was developed to execute the FIA. Then, the model has been coded to become a software. i-ATIE is able to measure the level of perceived intelligence of the PWE quantitatively and able to identify the skills that they are still lacking and need to be improved. With the advent of this psychometric test, it would now be possible to develop a tangible programme to enhance the employability of PWE that are problem-specific.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:multiple intelligence theory, people with epilepsy
Subjects:H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
ID Code:61664
Deposited By: Fazli Masari
Deposited On:26 Apr 2017 04:21
Last Modified:26 Apr 2017 04:21

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