Index of Instructional Sensitivity of Holistic Approach Training Module for Malaysian TVET Instructors in Prison
The current correctional system under Malaysia Prison Department (Pride) has implemented technical vocational education and training (TVET) as part of their rehabilitation programme. However, training by vocational instructors for inmates requires a holistic approach, as they need to bring the inm...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
UTeM
2018
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/21220/ http://umpir.ump.edu.my/id/eprint/21220/ http://umpir.ump.edu.my/id/eprint/21220/1/3804-10223-1-SM.pdf |
| Summary: | The current correctional system under Malaysia Prison Department (Pride) has implemented technical vocational education and training (TVET) as part of their rehabilitation programme. However, training by vocational instructors for inmates requires a holistic approach, as they need to bring the inmates to go beyond employability. As part of correctional programme components, the significant role of vocational instructor is not only about delivering skills, but also to improve inmates’ attitude and perspective about life. Therefore, the Holistic Approach Training Module has been developed. This module focused on the integration of God Consciousness element as a compass of life; internally and externally without disturbing the classic objective in vocational training. The module
consists of five variables or qualities which are believing in God, subjective, objective, social and cultural quality. A study was conducted on a group of 91 prisons’ vocational instructors from the East Zone of Malaysian Peninsular and Borneo under Pride. The collected data was analysed using Statistical Package for Social Science (SPSS for Windows) version 19.0 and Rasch Measurement
Modelling with Bond & Fox Steps Software. 42 participants, manage to go through both pre-test and post-test. It was concluded that the result shows module effectiveness by identifying the index of sensitivity by both analysis. |
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