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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

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Title: 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
Language: English
Authors: Wu-Yuin Hwang (ORCID 0000-0001-5684-3590), Thi-Rin-Gan Nguyen (ORCID 0009-0007-1159-1845), Rustam Shadiev (ORCID 0000-0001-5571-1158)
Source: Journal of Computer Assisted Learning. 2026 42(2).
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 23
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Technology Uses in Education, Multicultural Education, Cultural Awareness, Cross Cultural Training, Authentic Learning, Ethnic Groups, Foreign Countries, Graduate Students, Computer Oriented Programs, Prior Learning, Educational Technology, Instructional Effectiveness, Student Improvement, Learning Activities, Learning Experience
Geographic Terms: Indonesia, Thailand, Vietnam, China
DOI: 10.1002/jcal.70208
ISSN: 0266-4909
1365-2729
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&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.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1500462
Database: ERIC
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  Data: 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
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  Data: <searchLink fieldCode="AR" term="%22Wu-Yuin+Hwang%22">Wu-Yuin Hwang</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5684-3590">0000-0001-5684-3590</externalLink>)<br /><searchLink fieldCode="AR" term="%22Thi-Rin-Gan+Nguyen%22">Thi-Rin-Gan Nguyen</searchLink> (ORCID <externalLink term="https://orcid.org/0009-0007-1159-1845">0009-0007-1159-1845</externalLink>)<br /><searchLink fieldCode="AR" term="%22Rustam+Shadiev%22">Rustam Shadiev</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5571-1158">0000-0001-5571-1158</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Computer+Assisted+Learning%22"><i>Journal of Computer Assisted Learning</i></searchLink>. 2026 42(2).
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  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Data: Y
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  Data: 23
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Multicultural+Education%22">Multicultural Education</searchLink><br /><searchLink fieldCode="DE" term="%22Cultural+Awareness%22">Cultural Awareness</searchLink><br /><searchLink fieldCode="DE" term="%22Cross+Cultural+Training%22">Cross Cultural Training</searchLink><br /><searchLink fieldCode="DE" term="%22Authentic+Learning%22">Authentic Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Ethnic+Groups%22">Ethnic Groups</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Graduate+Students%22">Graduate Students</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Oriented+Programs%22">Computer Oriented Programs</searchLink><br /><searchLink fieldCode="DE" term="%22Prior+Learning%22">Prior Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Technology%22">Educational Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Instructional+Effectiveness%22">Instructional Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Improvement%22">Student Improvement</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Activities%22">Learning Activities</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Experience%22">Learning Experience</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Indonesia%22">Indonesia</searchLink><br /><searchLink fieldCode="DE" term="%22Thailand%22">Thailand</searchLink><br /><searchLink fieldCode="DE" term="%22Vietnam%22">Vietnam</searchLink><br /><searchLink fieldCode="DE" term="%22China%22">China</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1002/jcal.70208
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0266-4909<br />1365-2729
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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&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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        Value: 10.1002/jcal.70208
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      – Text: English
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        PageCount: 23
    Subjects:
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Technology Uses in Education
        Type: general
      – SubjectFull: Multicultural Education
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      – SubjectFull: Foreign Countries
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      – SubjectFull: Computer Oriented Programs
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      – SubjectFull: Prior Learning
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      – SubjectFull: Indonesia
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      – SubjectFull: China
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      – TitleFull: 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
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