MAGDM for Evaluating the Role of Computer Science in Education with PLq-ROF Heronian Mean Operators and Maximizing Deviation-MOORA Methodology
Abstract Computer science (CS) has changed educational processes in a wide range of academic fields and is now considered to be an essential part of modern education. This manuscript presents a novel methodology in which CS can be used to solve judgment concerns in education. The conventional educat...
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| Format: | Article |
| Language: | English |
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Springer
2025-08-01
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| Series: | International Journal of Computational Intelligence Systems |
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| Online Access: | https://doi.org/10.1007/s44196-025-00925-1 |
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| author | Aqsa Shafiq Muhammad Waheed Rasheed Marwah Shaker Habeeb Rabia Tasneem Nimra Shabbir Abdu Alameri |
| author_facet | Aqsa Shafiq Muhammad Waheed Rasheed Marwah Shaker Habeeb Rabia Tasneem Nimra Shabbir Abdu Alameri |
| author_sort | Aqsa Shafiq |
| collection | DOAJ |
| description | Abstract Computer science (CS) has changed educational processes in a wide range of academic fields and is now considered to be an essential part of modern education. This manuscript presents a novel methodology in which CS can be used to solve judgment concerns in education. The conventional education system frequently finds it difficult to deal with the ambiguities and linguistic expressions that are an integral component of human judgment and choice-making processes. By combining probabilistic uncertainty with linguistic concepts, a probabilistic linguistic q-rung orthopair fuzzy set (PLq-ROFS) presents an efficient mathematical methodology for describing inaccurate and unclear facts to handle these concerns. For aggregating the assessment data, we first propose the PLq-ROF Heronian mean operators. The maximizing deviation methodology is a helpful tool when dealing with situations where the knowledge about the attribute weights is either partially or fully unknown. To find attribute weights, this study presents the PLq-ROF-maximizing deviation methodology. We also propose the multi-objective optimization by ratio analysis (MOORA) methodology with PLq-ROFNs to evaluate the options and identify an optimal choice. Furthermore, a case study related to the judgment process on CS applications in education is provided from the PLq-ROFS perspective to illustrate the effectiveness and use of the developed technique. The numerical results show that $${\mathbb {A}}_{4}$$ A 4 (namely: skill development) is the best CS application in education. |
| format | Article |
| id | doaj-art-86d7dbf5c1124b88b1a5c4b4082df9e5 |
| institution | Kabale University |
| issn | 1875-6883 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Springer |
| record_format | Article |
| series | International Journal of Computational Intelligence Systems |
| spelling | doaj-art-86d7dbf5c1124b88b1a5c4b4082df9e52025-08-20T03:41:56ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832025-08-0118113310.1007/s44196-025-00925-1MAGDM for Evaluating the Role of Computer Science in Education with PLq-ROF Heronian Mean Operators and Maximizing Deviation-MOORA MethodologyAqsa Shafiq0Muhammad Waheed Rasheed1Marwah Shaker Habeeb2Rabia Tasneem3Nimra Shabbir4Abdu Alameri5Department of Mathematics, COMSATS University IslamabadDepartment of Mathematics, COMSATS University IslamabadCollege of Dentistry, Alnoor UniversityDivision of Science and Technology, Department of Mathematics, University of EducationDivision of Science and Technology, Department of Mathematics, University of EducationDepartment of Biomedical Engineering, University of Science and TechnologyAbstract Computer science (CS) has changed educational processes in a wide range of academic fields and is now considered to be an essential part of modern education. This manuscript presents a novel methodology in which CS can be used to solve judgment concerns in education. The conventional education system frequently finds it difficult to deal with the ambiguities and linguistic expressions that are an integral component of human judgment and choice-making processes. By combining probabilistic uncertainty with linguistic concepts, a probabilistic linguistic q-rung orthopair fuzzy set (PLq-ROFS) presents an efficient mathematical methodology for describing inaccurate and unclear facts to handle these concerns. For aggregating the assessment data, we first propose the PLq-ROF Heronian mean operators. The maximizing deviation methodology is a helpful tool when dealing with situations where the knowledge about the attribute weights is either partially or fully unknown. To find attribute weights, this study presents the PLq-ROF-maximizing deviation methodology. We also propose the multi-objective optimization by ratio analysis (MOORA) methodology with PLq-ROFNs to evaluate the options and identify an optimal choice. Furthermore, a case study related to the judgment process on CS applications in education is provided from the PLq-ROFS perspective to illustrate the effectiveness and use of the developed technique. The numerical results show that $${\mathbb {A}}_{4}$$ A 4 (namely: skill development) is the best CS application in education.https://doi.org/10.1007/s44196-025-00925-1PLq-ROFSHeronian mean operatorsMaximizing deviation methodologyMOORA methodologyCS applications in an educational sector |
| spellingShingle | Aqsa Shafiq Muhammad Waheed Rasheed Marwah Shaker Habeeb Rabia Tasneem Nimra Shabbir Abdu Alameri MAGDM for Evaluating the Role of Computer Science in Education with PLq-ROF Heronian Mean Operators and Maximizing Deviation-MOORA Methodology International Journal of Computational Intelligence Systems PLq-ROFS Heronian mean operators Maximizing deviation methodology MOORA methodology CS applications in an educational sector |
| title | MAGDM for Evaluating the Role of Computer Science in Education with PLq-ROF Heronian Mean Operators and Maximizing Deviation-MOORA Methodology |
| title_full | MAGDM for Evaluating the Role of Computer Science in Education with PLq-ROF Heronian Mean Operators and Maximizing Deviation-MOORA Methodology |
| title_fullStr | MAGDM for Evaluating the Role of Computer Science in Education with PLq-ROF Heronian Mean Operators and Maximizing Deviation-MOORA Methodology |
| title_full_unstemmed | MAGDM for Evaluating the Role of Computer Science in Education with PLq-ROF Heronian Mean Operators and Maximizing Deviation-MOORA Methodology |
| title_short | MAGDM for Evaluating the Role of Computer Science in Education with PLq-ROF Heronian Mean Operators and Maximizing Deviation-MOORA Methodology |
| title_sort | magdm for evaluating the role of computer science in education with plq rof heronian mean operators and maximizing deviation moora methodology |
| topic | PLq-ROFS Heronian mean operators Maximizing deviation methodology MOORA methodology CS applications in an educational sector |
| url | https://doi.org/10.1007/s44196-025-00925-1 |
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