A Study of <scp>AI</scp> ‐Supported Cross‐Cultural Learning and Its Influence on Cross‐Cultural Understanding, Learning Behaviour and Writing Performance of Learners in Authentic Contexts

ABSTRACT Background Cross‐cultural understanding is essential in education as learners increasingly engage with diverse cultural perspectives. Although artificial intelligence ( AI ) tools like contextual recognition and real‐time feedback offer personalised and adaptive support for these tasks, few studies have explored their role in fostering cross‐cultural understanding within authentic learning environments. Objectives This study focused on how AI supported effective learning about traditional foods and clothing from four ethnic groups: Indonesian, Thai, Vietnamese, and Chinese to promote cross‐cultural knowledge and engagement in real‐world contexts. Methods A five‐week quasi‐experimental study was conducted with 25 graduate students (8 females, 17 males, aged 23–35) from four ethnic backgrounds: Indonesian, Thai, Vietnamese, and Chinese. All participants had advanced English proficiency and no prior cross‐cultural learning experience. The AI X‐Cultural App integrated six AI ‐supported features: authentic context recognition, sample sentence generation, scaffolding, inspirational question generation, feedback, and Q&amp;A to support cross‐cultural writing tasks. Data were collected from pre/post essays, system interaction logs, and interviews to assess cross‐cultural understanding, learning behaviours, and user perceptions. Results and Conclusions The study yielded three key findings. First, students showed significant improvements in cross‐cultural understanding after engaging with the X‐Cultural AI app. Second, students' use of AI‐generated questions and Image‐to‐Text Recognition (ITR) features strongly correlated with enhanced writing performance. Finally, interview responses revealed that participants perceived the app as highly supportive in fostering their cross‐cultural learning. These qualitative and quantitative results together indicate the strong potential of AI‐supported tools to help learners connect prior knowledge with new cultural information in real‐world, authentic learning contexts.

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Publication Details

Journal
Journal of Computer Assisted Learning
Published
2026-02-18
DOI
https://doi.org/10.1002/jcal.70208
Citations
1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
52.10
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article

A Study of AI ‐Supported Cross‐Cultural Learning and Its Influence on Cross‐Cultural Understanding, Learning Behaviour and Writing Performance of Learners in Authentic Contexts

Di Ge, Wu‐Yuin Hwang, Tien Minh Nguyen
1 citations
Journal of Computer Assisted Learning
AI in Service Interactions
52.10
article

A Study of AI ‐Supported Cross‐Cultural Learning and Its Influence on Cross‐Cultural Understanding, Learning Behaviour and Writing Performance of Learners in Authentic Contexts

Di Ge, Wu‐Yuin Hwang, Tien Minh Nguyen
article en
1 citations

Abstract

ABSTRACT Background Cross‐cultural understanding is essential in education as learners increasingly engage with diverse cultural perspectives. Although artificial intelligence ( AI ) tools like contextual recognition and real‐time feedback offer personalised and adaptive support for these tasks, few studies have explored their role in fostering cross‐cultural understanding within authentic learning environments. Objectives This study focused on how AI supported effective learning about traditional foods and clothing from four ethnic groups: Indonesian, Thai, Vietnamese, and Chinese to promote cross‐cultural knowledge and engagement in real‐world contexts. Methods A five‐week quasi‐experimental study was conducted with 25 graduate students (8 females, 17 males, aged 23–35) from four ethnic backgrounds: Indonesian, Thai, Vietnamese, and Chinese. All participants had advanced English proficiency and no prior cross‐cultural learning experience. The AI X‐Cultural App integrated six AI ‐supported features: authentic context recognition, sample sentence generation, scaffolding, inspirational question generation, feedback, and Q&amp;A to support cross‐cultural writing tasks. Data were collected from pre/post essays, system interaction logs, and interviews to assess cross‐cultural understanding, learning behaviours, and user perceptions. Results and Conclusions The study yielded three key findings. First, students showed significant improvements in cross‐cultural understanding after engaging with the X‐Cultural AI app. Second, students' use of AI‐generated questions and Image‐to‐Text Recognition (ITR) features strongly correlated with enhanced writing performance. Finally, interview responses revealed that participants perceived the app as highly supportive in fostering their cross‐cultural learning. These qualitative and quantitative results together indicate the strong potential of AI‐supported tools to help learners connect prior knowledge with new cultural information in real‐world, authentic learning contexts.

Journal of Computer Assisted LearningVol. 42(2)
National Central University (TW), Department of Education of Zhejiang Province (CN), Zhejiang University (CN)
Quality Education
Openalex Percentile: Top 0%
AI in Service Interactions
52.10
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