EFL Students’ Perceptions of Language Learning and Assessment: Pre and in Generative AI (GenAI) Era

Anecdotal evidence suggests that the use of GenAI has both advantages and disadvantages in students’ learning and assessment processes. However, despite the increasing volume, few studies have been conducted to explore English as a Foreign Language (EFL) students’ perceptions towards language learn...

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Bibliographic Details
Main Author: Huan Zhao
Format: Article
Language:English
Published: Universidad del Valle 2025-06-01
Series:Lenguaje
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Online Access:https://revistaprospectiva.univalle.edu.co/index.php/lenguaje/article/view/14603
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Summary:Anecdotal evidence suggests that the use of GenAI has both advantages and disadvantages in students’ learning and assessment processes. However, despite the increasing volume, few studies have been conducted to explore English as a Foreign Language (EFL) students’ perceptions towards language learning and assessments pre and in GenAI era. Therefore, employing a qualitative research approach, mainly through interviews and thematic analysis, the study aims to discover in-depth information about features and patterns of tertiary EFL students’ perceptions and perception changes, regarding the impact of GenAI on language learning and the fairness of assessments in China. Findings of the study reveal that students do not embrace the idea of banning the use of GenAI in their learning and assessment, while they believe this could lead to not only advantages but also negative outcomes. Their perception towards assessment has shifted after the emergence of GenAI, compared with pre-GenAI era. To mitigate the negative consequences of GenAI in learning and assessment, participants presented some key suggestions. Tertiary education policy makers could draw on the findings of the study to create well-informed guidelines and strategies to effectively and ethically implement the use of GenAI tools, ultimately improving the teaching and learning experiences in Chinese and worldwide tertiary education sectors.
ISSN:0120-3479
2539-3804