RETRACTED: Unboxing the intersections between self‐esteem and academic mindfulness with test emotions, psychological wellness and academic achievement in artificial intelligence‐supported learning environments: Evidence from English as a foreign language learners
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| Title: | RETRACTED: Unboxing the intersections between self‐esteem and academic mindfulness with test emotions, psychological wellness and academic achievement in artificial intelligence‐supported learning environments: Evidence from English as a foreign language learners |
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| Authors: | Hou, Lin (AUTHOR) |
| Source: | British Educational Research Journal. Jun2026, Vol. 52 Issue 3, pe163-e190. 28p. |
| Subjects: | Self-esteem, Artificial intelligence, Academic achievement, Classroom environment, Mental health, Test anxiety, Metacognition |
| Geographic Terms: | China |
| Abstract: | The integration of artificial intelligence (AI) into language education is rapidly transforming English as a foreign language (EFL) learning environments, presenting both opportunities and challenges. While AI‐supported tools offer potential benefits, they can also trigger complex test‐related emotions that may impact learners' psychological and academic well‐being. Therefore, understanding the interplay between internal resources like self‐esteem and academic mindfulness, alongside these emotions, becomes crucial. This study investigated the correlations between self‐esteem and academic mindfulness with test emotions, psychological well‐being and academic achievement among EFL learners in AI‐supported contexts in China. To meet this purpose, a quantitative approach was employed, using data collected from a sample of 305 EFL university students (155 males and 150 females) in China selected through stratified random sampling. The analysis was conducted via confirmatory factor analysis and structural equation modelling using SMART PLS software. The results indicated that self‐esteem and academic mindfulness were strong predictors of test emotions, psychological wellness and academic achievement. Higher levels of academic self‐esteem and academic mindfulness were linked to higher test emotions, psychological well‐being and academic achievement. These findings stress the necessity of incorporating socio‐emotional skills into AI‐enhanced EFL learning, considering students' psychological well‐being when deploying AI tools and designing interventions to address emotional challenges within AI‐supported environments. [ABSTRACT FROM AUTHOR] |
| Copyright of British Educational Research Journal is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | The integration of artificial intelligence (AI) into language education is rapidly transforming English as a foreign language (EFL) learning environments, presenting both opportunities and challenges. While AI‐supported tools offer potential benefits, they can also trigger complex test‐related emotions that may impact learners' psychological and academic well‐being. Therefore, understanding the interplay between internal resources like self‐esteem and academic mindfulness, alongside these emotions, becomes crucial. This study investigated the correlations between self‐esteem and academic mindfulness with test emotions, psychological well‐being and academic achievement among EFL learners in AI‐supported contexts in China. To meet this purpose, a quantitative approach was employed, using data collected from a sample of 305 EFL university students (155 males and 150 females) in China selected through stratified random sampling. The analysis was conducted via confirmatory factor analysis and structural equation modelling using SMART PLS software. The results indicated that self‐esteem and academic mindfulness were strong predictors of test emotions, psychological wellness and academic achievement. Higher levels of academic self‐esteem and academic mindfulness were linked to higher test emotions, psychological well‐being and academic achievement. These findings stress the necessity of incorporating socio‐emotional skills into AI‐enhanced EFL learning, considering students' psychological well‐being when deploying AI tools and designing interventions to address emotional challenges within AI‐supported environments. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 01411926 |
| DOI: | 10.1002/berj.4146 |
