Durrani Aimi, Abdul Malik (2022) Hybrid fuzzy analytical hierarchy process with fuzzy inference system on ranking stem approach towards blended learning in mathematics. Masters thesis, Universiti Malaysia Pahang (Contributors, Thesis advisor: Yuhani, Yusof).
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Hybrid fuzzy analytical hierarchy process with fuzzy inference system on ranking stem approach towards blended learning in mathematics.ir.pdf - Accepted Version Download (505kB) | Preview |
Abstract
In the era of Education 4.0, blended learning has been selected as one of the transformational pedagogies for the teaching and learning process that integrate Science, Technology, Engineering, and Mathematics (STEM), a new norm that needs to be adopted by Malaysia. Since the COVID-19 pandemic, the issue has been highlighted at most levels of study in the education field. However, limited knowledge of the implementation of 21st Century learning skills with Web 2.0 among teachers has made the students demotivated for their mathematics classroom. Moreover, dynamic changes in the standard curriculum have made the situation more challenging for teachers in selecting the appropriate STEM approach to ensure students are fully engaged. Inspired by the problem, this research used fuzzy multi-criteria decision-making (MCDM) concepts. A hybrid fuzzy MCDM model proposes a four stages process to rank and find the best implementation STEM approach in the mathematics classroom. The model is constructed by integrating the Fuzzy Analytical Hierarchy Process (FAHP) to determine the weights of STEM criteria and sub-criteria and the Fuzzy Inference System (FIS) to compute the best STEM approach in the mathematics classroom. The procedure involves exploring the issue associated with the selection problems, deriving decision criteria important weights, and ranking various alternatives with applied intuitive multiple centroids as a defuzzification method. The results showed hands-on activities as the best STEM approach while requisite knowledge is the important criterion with the greatest value of weights. Thus, the proposed model helps provide a clear picture for teachers in the implementation of STEM approach in Mathematics based on a comprehensive view and also lay a new foundation knowledge in fuzzy MCDM view, particularly in STEM education. Also, it helps the Ministry of Education (MoE) to achieve one of the initiatives in Wave 3 of the Malaysia Education Blueprint (2021-2025), which is to share the best practice in the classroom to cultivate a peer-led culture of professional excellence among teachers as the basis for improving the implementation and achievement of STEM at the national level.
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | Thesis (Master of Science) -- Universiti Malaysia Pahang – 2022, SV: Assoc. Prof. Dr. Yuhani Binti Yusof, NO.CD: 13298 |
| Uncontrolled Keywords: | Hybrid fuzzy analytical hierarchy process, fuzzy inference system |
| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics |
| Faculty/Division: | Institute of Postgraduate Studies Center for Mathematical Science |
| Depositing User: | Mr. Nik Ahmad Nasyrun Nik Abd Malik |
| Date Deposited: | 25 Aug 2023 02:13 |
| Last Modified: | 25 Aug 2023 02:13 |
| URI: | http://umpir.ump.edu.my/id/eprint/38451 |
| Download Statistic: | View Download Statistics |
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