Exploring faculty experiences with generative artificial intelligence tools integration in second language curricula in Chinese higher education
Iqbal, Javed; Asgarova, Vafa; Hashmi, Zarqa Farooq; Ngajie, Berty Nsolly; Asghar, Muhammad Zaheer; Järvenoja, Hanna (2025-06-19)
Springer
19.06.2025
Iqbal, J., Asgarova, V., Hashmi, Z.F. et al. Exploring faculty experiences with generative artificial intelligence tools integration in second language curricula in Chinese higher education. Discov Computing 28, 128 (2025). https://doi.org/10.1007/s10791-025-09655-6
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© The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
https://creativecommons.org/licenses/by/4.0/
© The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202506234888
https://urn.fi/URN:NBN:fi:oulu-202506234888
Tiivistelmä
Abstract
The current study investigates how faculty members in Chinese universities are navigating the integration of generative artificial intelligence tools into second language curricula, focusing on specific pedagogical and institutional challenges. Using an exploratory sequential mixed-method approach (N = 776), we examined how faculty perceive and address key areas of concern: curriculum adaptation, assessment transformation, student engagement, ethical concerns, professional development needs, and pedagogical shifts. Unlike prior studies, which often generalize faculty experiences, this study uniquely captures nuanced faculty strategies and gaps in readiness across a large-scale context in Chinese higher education. Results indicated that faculty members exhibited significant usage of generative artificial intelligence tools both for personal and professional purposes. They also used generative artificial intelligence tools for formative assessment practices, with limited application in summative assessments. Results indicated faculty faced Generative AI tool usage challenges like curriculum adaptation, assessment transformation, student engagement with generative artificial intelligence tools, ethical concerns, professional development, and pedagogical shifts. The findings also demonstrated that faculty members were struggling to address these challenges. Furthermore, outcomes indicated that professional development and ethical concerns directly, indirectly, positively and significantly contribute to helping faculty to enhance student engagement and pedagogical shifts in their teaching practices. Additionally, curriculum adaptation and assessment transformation have also mediated these relationships. These findings contribute novel insights into how professional development can support effective GenAI integration. Implications are offered for faculty development programs, curriculum design policies, and institutional governance in the era of AI-enhanced education.
The current study investigates how faculty members in Chinese universities are navigating the integration of generative artificial intelligence tools into second language curricula, focusing on specific pedagogical and institutional challenges. Using an exploratory sequential mixed-method approach (N = 776), we examined how faculty perceive and address key areas of concern: curriculum adaptation, assessment transformation, student engagement, ethical concerns, professional development needs, and pedagogical shifts. Unlike prior studies, which often generalize faculty experiences, this study uniquely captures nuanced faculty strategies and gaps in readiness across a large-scale context in Chinese higher education. Results indicated that faculty members exhibited significant usage of generative artificial intelligence tools both for personal and professional purposes. They also used generative artificial intelligence tools for formative assessment practices, with limited application in summative assessments. Results indicated faculty faced Generative AI tool usage challenges like curriculum adaptation, assessment transformation, student engagement with generative artificial intelligence tools, ethical concerns, professional development, and pedagogical shifts. The findings also demonstrated that faculty members were struggling to address these challenges. Furthermore, outcomes indicated that professional development and ethical concerns directly, indirectly, positively and significantly contribute to helping faculty to enhance student engagement and pedagogical shifts in their teaching practices. Additionally, curriculum adaptation and assessment transformation have also mediated these relationships. These findings contribute novel insights into how professional development can support effective GenAI integration. Implications are offered for faculty development programs, curriculum design policies, and institutional governance in the era of AI-enhanced education.
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