Abdul Azziz, Eisy Humaira (2021) Knowledge-based performance measurement model for Malaysia Higher Education Institution. Masters thesis, Universiti Teknikal Malaysia Melaka.
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Abstract
Performance Measurement (PM) is a valuable tool to measure organizational performance. The key factor in measuring the performance is to assess the current position of an organization and to assist managers in creating a better strategy. Some education organizations use ranking instrument system (RIS) in measuring performance for Higher Education Institutions (HEI) such as MyRA and QS Ranking. Hence, almost all HEIs strive to achieve the target performance. More emphasis is put on HEIs' PM plans to ensure that the institutions can perform well in RIS. However, the current Performance Measurement Model (PMM) does not emphasize in measuring individual capabilities in enhancing the overall performance of Higher Education Institutions. Staff may perform works that exceed their limit because the goal is not measured according to their strength. Besides, the current Knowledge-Based Performance Measurement features are not suitable to map with the existing ranking instrument system in which staff performance is one of the main factors. Many aspects are to be considered before measuring the performance because a lot of performance indicators exist in RIS. Therefore, a PM model that can overcome all these problems should be developed. This research develops an enhanced knowledge-based performance measurement model (KBPMM) that caters to the HEIs' needs. The primary aim of this model is to assist institution's top management in managing and monitoring the performance achievement of HEIs based on staff's contribution, hence, contributing to the overall HEI's performance. The proposed model considered some crucial aspects in calculating the performance of individual staff and utilized the Artificial Intelligence (AI) techniques, namely the knowledge-based (KB) and Expert System (ES) to build the model. Besides, non-AI techniques such as Full-time Equivalent (FTE) and Competitor Analysis were also used in the model development to enhance the model's capability. By using ES, the model recommends the possible solutions to enhance the performance. The proposed enhanced KBPMM is validated via expert validation process. Based on the result, the experts conclude that KBPMM could be one of the alternatives for the institution to measure and monitor the performance. KBPMM can also be used to assist the administrators in measuring the institution's performance better than the current existing system. Furthermore, combining AI and non -AI techniques in the model development shows that the use of a variety of approaches/techniques in conducting the process can improve the output. This research will give advantages to the HEI's in Malaysia, especially UTeM, in managing and controlling its institutional performance. In addition, with an in-depth understanding of the flow and process of the model, this model can also be applied in other sectors such as health care.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Expert systems (Computer science), Performance, Measurement Education, Higher, Malaysia, Intelligent tutoring systems |
| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics |
| Divisions: | Library > Tesis > FTMK |
| Depositing User: | F Haslinda Harun |
| Date Deposited: | 29 Sep 2022 12:14 |
| Last Modified: | 29 Sep 2022 12:14 |
| URI: | http://eprints.utem.edu.my/id/eprint/26013 |
| Statistic Details: | View Download Statistic |
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