A Data-Driven MCDM Approach-Based Spherical Fuzzy Sets for Evaluating Global Augmented Reality Providers in Education
Amidst the heightened popularity of augmented reality (AR), particularly in education driven by the transformative impact of the COVID-19 pandemic on remote learning, this study addresses the intricacies surrounding the discerning selection of AR providers for educational purposes. It introduces a c...
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IEEE
2025-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10418216/ |
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| author | Phi-Hung Nguyen |
| author_facet | Phi-Hung Nguyen |
| author_sort | Phi-Hung Nguyen |
| collection | DOAJ |
| description | Amidst the heightened popularity of augmented reality (AR), particularly in education driven by the transformative impact of the COVID-19 pandemic on remote learning, this study addresses the intricacies surrounding the discerning selection of AR providers for educational purposes. It introduces a comprehensive decision support model, utilizing Spherical Fuzzy Sets (SFSs) to enhance the decision-making process. The methodology involves the application of SF-Delphi to ascertain the relative significance of eight pivotal criteria shaping AR provider selection. The Spherical Weighted Arithmetic Mean (SWAM) operator ensures an exhaustive and unbiased assessment. Subsequently, the Technique for Order of Preference by Similarity to the Ideal Solution (SF-TOPSIS) is systematically applied to evaluate and rank ten global AR providers. This research yields a dual contribution. Firstly, the proposed decision support model systematically guides AR provider selection, equipping decision-makers to navigate the intricacies of AR technology choices efficiently. Additionally, the impact extends to education, enriching the understanding of AR applications. This knowledge promotes well-informed and innovative AR technology utilization, enhancing the overall learning experience. In conclusion, this study introduces a pioneering decision support model that leverages SFSs to guide the selection of educational AR providers. This structured framework empowers decision-makers and advances the comprehension of AR dynamics, further propelling the strategic integration of AR technology in education. |
| format | Article |
| id | doaj-art-dd8efd76f99c41d48c4ce9fea8a27a72 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| series | IEEE Access |
| spelling | doaj-art-dd8efd76f99c41d48c4ce9fea8a27a722025-01-14T00:02:26ZengIEEEIEEE Access2169-35362025-01-01136102611910.1109/ACCESS.2024.336132010418216A Data-Driven MCDM Approach-Based Spherical Fuzzy Sets for Evaluating Global Augmented Reality Providers in EducationPhi-Hung Nguyen0Research Center of Applied Sciences, Faculty of Business, FPT University, Hanoi, VietnamAmidst the heightened popularity of augmented reality (AR), particularly in education driven by the transformative impact of the COVID-19 pandemic on remote learning, this study addresses the intricacies surrounding the discerning selection of AR providers for educational purposes. It introduces a comprehensive decision support model, utilizing Spherical Fuzzy Sets (SFSs) to enhance the decision-making process. The methodology involves the application of SF-Delphi to ascertain the relative significance of eight pivotal criteria shaping AR provider selection. The Spherical Weighted Arithmetic Mean (SWAM) operator ensures an exhaustive and unbiased assessment. Subsequently, the Technique for Order of Preference by Similarity to the Ideal Solution (SF-TOPSIS) is systematically applied to evaluate and rank ten global AR providers. This research yields a dual contribution. Firstly, the proposed decision support model systematically guides AR provider selection, equipping decision-makers to navigate the intricacies of AR technology choices efficiently. Additionally, the impact extends to education, enriching the understanding of AR applications. This knowledge promotes well-informed and innovative AR technology utilization, enhancing the overall learning experience. In conclusion, this study introduces a pioneering decision support model that leverages SFSs to guide the selection of educational AR providers. This structured framework empowers decision-makers and advances the comprehension of AR dynamics, further propelling the strategic integration of AR technology in education.https://ieeexplore.ieee.org/document/10418216/Augmented realityMCDMspherical fuzzy setsDelphiTOPSISeducation |
| spellingShingle | Phi-Hung Nguyen A Data-Driven MCDM Approach-Based Spherical Fuzzy Sets for Evaluating Global Augmented Reality Providers in Education IEEE Access Augmented reality MCDM spherical fuzzy sets Delphi TOPSIS education |
| title | A Data-Driven MCDM Approach-Based Spherical Fuzzy Sets for Evaluating Global Augmented Reality Providers in Education |
| title_full | A Data-Driven MCDM Approach-Based Spherical Fuzzy Sets for Evaluating Global Augmented Reality Providers in Education |
| title_fullStr | A Data-Driven MCDM Approach-Based Spherical Fuzzy Sets for Evaluating Global Augmented Reality Providers in Education |
| title_full_unstemmed | A Data-Driven MCDM Approach-Based Spherical Fuzzy Sets for Evaluating Global Augmented Reality Providers in Education |
| title_short | A Data-Driven MCDM Approach-Based Spherical Fuzzy Sets for Evaluating Global Augmented Reality Providers in Education |
| title_sort | data driven mcdm approach based spherical fuzzy sets for evaluating global augmented reality providers in education |
| topic | Augmented reality MCDM spherical fuzzy sets Delphi TOPSIS education |
| url | https://ieeexplore.ieee.org/document/10418216/ |
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