Impact of AI-Powered Adaptive Learning Platforms on English Reading Proficiency: Evidence From Structural Equation Modeling
This study examines the impact and mediating mechanisms of AI-powered adaptive learning platforms on enhancing English reading proficiency. Using structural equation modeling (SEM) on data collected from 118 undergraduate students, this study validates a chained mediation model in which learner enga...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/11006699/ |
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| author | Jin Wu Yiyun Wang Fang Chen Xueqi Yin Yun He |
| author_facet | Jin Wu Yiyun Wang Fang Chen Xueqi Yin Yun He |
| author_sort | Jin Wu |
| collection | DOAJ |
| description | This study examines the impact and mediating mechanisms of AI-powered adaptive learning platforms on enhancing English reading proficiency. Using structural equation modeling (SEM) on data collected from 118 undergraduate students, this study validates a chained mediation model in which learner engagement mediates the relationship between satisfaction with platform functionalities and perceived learning outcomes. The results show that: (1) satisfaction with key functionalities, such as dynamic content adaptation and real-time feedback, significantly enhances learner engagement; (2) learner engagement strongly predicts perceived improvements in reading skills; and (3) the platform facilitates reading comprehension through a dual intervention mechanism integrating bottom-up decoding and top-down schema activation strategies. These findings address an empirical gap in the application of AI for receptive language development and provide theoretical, methodological, and practical implications for the design of intelligent educational systems and foster pedagogical innovation. |
| format | Article |
| id | doaj-art-0bab314aba234e6180f7f45bf5ef4f93 |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-0bab314aba234e6180f7f45bf5ef4f932025-08-20T01:53:03ZengIEEEIEEE Access2169-35362025-01-0113882308824210.1109/ACCESS.2025.357105511006699Impact of AI-Powered Adaptive Learning Platforms on English Reading Proficiency: Evidence From Structural Equation ModelingJin Wu0https://orcid.org/0009-0004-8308-2765Yiyun Wang1https://orcid.org/0000-0003-1061-640XFang Chen2Xueqi Yin3https://orcid.org/0009-0001-9800-9630Yun He4School of Foreign Languages, Tianjin University of Commerce, Tianjin, ChinaSchool of Foreign Languages, Tianjin University of Commerce, Tianjin, ChinaSchool of Foreign Languages, Tianjin University of Commerce, Tianjin, ChinaSchool of Foreign Languages, Tianjin University of Commerce, Tianjin, ChinaSchool of Foreign Languages, Tianjin University of Commerce, Tianjin, ChinaThis study examines the impact and mediating mechanisms of AI-powered adaptive learning platforms on enhancing English reading proficiency. Using structural equation modeling (SEM) on data collected from 118 undergraduate students, this study validates a chained mediation model in which learner engagement mediates the relationship between satisfaction with platform functionalities and perceived learning outcomes. The results show that: (1) satisfaction with key functionalities, such as dynamic content adaptation and real-time feedback, significantly enhances learner engagement; (2) learner engagement strongly predicts perceived improvements in reading skills; and (3) the platform facilitates reading comprehension through a dual intervention mechanism integrating bottom-up decoding and top-down schema activation strategies. These findings address an empirical gap in the application of AI for receptive language development and provide theoretical, methodological, and practical implications for the design of intelligent educational systems and foster pedagogical innovation.https://ieeexplore.ieee.org/document/11006699/Artificial intelligence in educationadaptive learning systemspersonalized learningEnglish reading comprehensionstructural equation modeling |
| spellingShingle | Jin Wu Yiyun Wang Fang Chen Xueqi Yin Yun He Impact of AI-Powered Adaptive Learning Platforms on English Reading Proficiency: Evidence From Structural Equation Modeling IEEE Access Artificial intelligence in education adaptive learning systems personalized learning English reading comprehension structural equation modeling |
| title | Impact of AI-Powered Adaptive Learning Platforms on English Reading Proficiency: Evidence From Structural Equation Modeling |
| title_full | Impact of AI-Powered Adaptive Learning Platforms on English Reading Proficiency: Evidence From Structural Equation Modeling |
| title_fullStr | Impact of AI-Powered Adaptive Learning Platforms on English Reading Proficiency: Evidence From Structural Equation Modeling |
| title_full_unstemmed | Impact of AI-Powered Adaptive Learning Platforms on English Reading Proficiency: Evidence From Structural Equation Modeling |
| title_short | Impact of AI-Powered Adaptive Learning Platforms on English Reading Proficiency: Evidence From Structural Equation Modeling |
| title_sort | impact of ai powered adaptive learning platforms on english reading proficiency evidence from structural equation modeling |
| topic | Artificial intelligence in education adaptive learning systems personalized learning English reading comprehension structural equation modeling |
| url | https://ieeexplore.ieee.org/document/11006699/ |
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