Artificial intelligence in educational technology and transformative approaches to English language using fuzzy framework with CRITIC-TOPSIS method

Abstract Artificial intelligence (AI) is transforming educational technology by enabling personalized, adaptive, and data-driven learning experiences. Machine learning algorithms analyze student performance to tailor content delivery, while natural language processing facilitates interactive learnin...

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Main Authors: Jingdan Liu, Xujie Bao, Liji Chen
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-09844-9
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author Jingdan Liu
Xujie Bao
Liji Chen
author_facet Jingdan Liu
Xujie Bao
Liji Chen
author_sort Jingdan Liu
collection DOAJ
description Abstract Artificial intelligence (AI) is transforming educational technology by enabling personalized, adaptive, and data-driven learning experiences. Machine learning algorithms analyze student performance to tailor content delivery, while natural language processing facilitates interactive learning through voice assistants and essay evaluation. This article presents the potential of criteria importance through the inter-criteria correlation (ICCR) method, which is used to determine objective weights under theoretical concepts of standard deviation and coefficient correlation techniques. Furthermore, another approach using the tool for order preference by similarity to the ideal solution (TOPSIS) method is discussed to investigate the ranking of preferences under various criteria and experts’ opinions within the system of the q-rung orthopair fuzzy framework. To reveal the validation and superiority, a numerical example is discussed to evaluate an effective AI approach to improve English language and psychology pedagogy under different criteria. Furthermore, a comprehensive comparative study is conducted to assess the compatibility of the proposed optimization techniques in the CRITIC-TOPSIS method with existing optimization approaches. Finally, the findings and contributions, along with future directions, are discussed in the conclusion. Additionally, we can apply the discussed decision-making methodologies to resolve complex real-life applications, such as renewable energy, medical diagnosis, multi-robotic systems, social selections, and computational and environmental sciences.
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spelling doaj-art-7550c45f022d492080b63d376559ea462025-08-20T03:46:07ZengNature PortfolioScientific Reports2045-23222025-07-0115111610.1038/s41598-025-09844-9Artificial intelligence in educational technology and transformative approaches to English language using fuzzy framework with CRITIC-TOPSIS methodJingdan Liu0Xujie Bao1Liji Chen2School of General Education, Hunan University of Information TechnologySchool of General Education, Hunan University of Information TechnologySchool of General Education, Hunan University of Information TechnologyAbstract Artificial intelligence (AI) is transforming educational technology by enabling personalized, adaptive, and data-driven learning experiences. Machine learning algorithms analyze student performance to tailor content delivery, while natural language processing facilitates interactive learning through voice assistants and essay evaluation. This article presents the potential of criteria importance through the inter-criteria correlation (ICCR) method, which is used to determine objective weights under theoretical concepts of standard deviation and coefficient correlation techniques. Furthermore, another approach using the tool for order preference by similarity to the ideal solution (TOPSIS) method is discussed to investigate the ranking of preferences under various criteria and experts’ opinions within the system of the q-rung orthopair fuzzy framework. To reveal the validation and superiority, a numerical example is discussed to evaluate an effective AI approach to improve English language and psychology pedagogy under different criteria. Furthermore, a comprehensive comparative study is conducted to assess the compatibility of the proposed optimization techniques in the CRITIC-TOPSIS method with existing optimization approaches. Finally, the findings and contributions, along with future directions, are discussed in the conclusion. Additionally, we can apply the discussed decision-making methodologies to resolve complex real-life applications, such as renewable energy, medical diagnosis, multi-robotic systems, social selections, and computational and environmental sciences.https://doi.org/10.1038/s41598-025-09844-9q-rung orthopair fuzzy informationAggregation operatorsAdvanced educational technologiesCRITIC-TOPSIS for decision-making problems
spellingShingle Jingdan Liu
Xujie Bao
Liji Chen
Artificial intelligence in educational technology and transformative approaches to English language using fuzzy framework with CRITIC-TOPSIS method
Scientific Reports
q-rung orthopair fuzzy information
Aggregation operators
Advanced educational technologies
CRITIC-TOPSIS for decision-making problems
title Artificial intelligence in educational technology and transformative approaches to English language using fuzzy framework with CRITIC-TOPSIS method
title_full Artificial intelligence in educational technology and transformative approaches to English language using fuzzy framework with CRITIC-TOPSIS method
title_fullStr Artificial intelligence in educational technology and transformative approaches to English language using fuzzy framework with CRITIC-TOPSIS method
title_full_unstemmed Artificial intelligence in educational technology and transformative approaches to English language using fuzzy framework with CRITIC-TOPSIS method
title_short Artificial intelligence in educational technology and transformative approaches to English language using fuzzy framework with CRITIC-TOPSIS method
title_sort artificial intelligence in educational technology and transformative approaches to english language using fuzzy framework with critic topsis method
topic q-rung orthopair fuzzy information
Aggregation operators
Advanced educational technologies
CRITIC-TOPSIS for decision-making problems
url https://doi.org/10.1038/s41598-025-09844-9
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