Optimizing AI-Driven EdTech Solutions for Enhanced English Learning: A TOPSIS Approach

The development of educational technology (EdTech) and artificial intelligence (AI) brings about a revolution in English learning by providing flexible, effective, and customized solutions. The purpose of this study is to assess the impact of AI and EdTec on education. In this article, we defined the multi-criteria decision-making (MCDM) procedure to manage ambiguity and awkward information by integrating the Technique for Order of Preference by Similarity to the Ideal Solution (Topsis) method with Circular q-Rung orthopair fuzzy set (Cq-ROFS), and Bonferroni mean (BM) operators to evaluate and prioritize AI-driven EdTech tools. The methodology incorporates multiple attributes, such as adaptability, learner engagement, cost-effectiveness, and scalability, within an MCDM framework. These results highlight the huge potential of intelligent teaching programs, flexible learning environments, and AI-powered language models to improve English ability. This research demonstrates how AI has advanced in education from simple computer-assisted language learning to complex AI-driven platforms like chatbots and intelligent systems for teaching. These developments, such as automated grading and feedback, have given teachers the ability to improve administrative effectiveness and instructional quality. Furthermore, customized and interactive learning experiences that are adapted to the needs and preferences of each student have been made possible by AI-based EdTech solutions. The study used the TOPSIS technique to rank important criteria for optimizing various solutions, highlighting their contribution to preservation, interaction, and overall efficacy in English language learning.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3561694
Citations
2
Primary Topic
Engineering Education and Technology
Type
article
Field-Weighted Citation Impact
6.49
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article

Optimizing AI-Driven EdTech Solutions for Enhanced English Learning: A TOPSIS Approach

Lu Li, Yang Liu, Li Wang
2 citations
IEEE Access
Engineering Education and Technology
6.49
article

Optimizing AI-Driven EdTech Solutions for Enhanced English Learning: A TOPSIS Approach

Lu Li, Yang Liu, Li Wang
article en
2 citations

Abstract

The development of educational technology (EdTech) and artificial intelligence (AI) brings about a revolution in English learning by providing flexible, effective, and customized solutions. The purpose of this study is to assess the impact of AI and EdTec on education. In this article, we defined the multi-criteria decision-making (MCDM) procedure to manage ambiguity and awkward information by integrating the Technique for Order of Preference by Similarity to the Ideal Solution (Topsis) method with Circular q-Rung orthopair fuzzy set (Cq-ROFS), and Bonferroni mean (BM) operators to evaluate and prioritize AI-driven EdTech tools. The methodology incorporates multiple attributes, such as adaptability, learner engagement, cost-effectiveness, and scalability, within an MCDM framework. These results highlight the huge potential of intelligent teaching programs, flexible learning environments, and AI-powered language models to improve English ability. This research demonstrates how AI has advanced in education from simple computer-assisted language learning to complex AI-driven platforms like chatbots and intelligent systems for teaching. These developments, such as automated grading and feedback, have given teachers the ability to improve administrative effectiveness and instructional quality. Furthermore, customized and interactive learning experiences that are adapted to the needs and preferences of each student have been made possible by AI-based EdTech solutions. The study used the TOPSIS technique to rank important criteria for optimizing various solutions, highlighting their contribution to preservation, interaction, and overall efficacy in English language learning.

IEEE AccessVol. 13
Xi'an International Studies University (CN), Dalian University of Technology (CN), Northwest University (CN), Dalian University (CN)
Openalex Percentile: Top 4%
Engineering Education and Technology
6.49
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Optimizing AI-Driven EdTech Solutions for Enhanced English Learning: A TOPSIS Approach — Lu Li, Yang Liu, et al. · IEEE Access (2025) | TGRS Research Map | TGRS