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Research Content

Research Title and Theme


A comparative study on the implementation path of generative AI-enabled language teaching in higher education in United Kingdom and China

Research Context


The rapid development of generative AI (Generative AI) has profoundly changed the way information is obtained and knowledge is transferred, and it has also brought major challenges to higher education and teaching, digital governance, and talent training. At present, many international organizations and world-class universities have explored the application specifications of generative AI. In Europe, the Russell Group of 24 top United Kingdom universities, including the University of Oxford, the University of Cambridge and the University of Birmingham, has jointly released new principles for the use of generative AI tools on campus, emphasizing the leadership of teachers and students in the AI era(The Russell Group，2024)。 In July 2023, the National Development and Reform Commission (NDRC) and the Ministry of Education (MOE) jointly issued the Interim Measures for the Management of Generative AI Services to support educational and scientific research institutions in generative AITechnological innovation in the field, and at the same time standardize the healthy development of technology. The use of generative AI technology to promote classroom teaching reform has become the consensus of various institutions around the world (Wang Wen and Li Yongzhi, 2024). Among them, language teaching is an important subject scenario for the application of AI technology in education. In the era of human-machine symbiosis, language teaching needs to keep pace with the times and construct a new teaching framework supported by a variety of intelligent technologies (Kong Lei, 2). 024）。 However, at present, there is still a need to expand the research on the development of language teachers in the process of integrating AI into language teaching. The relationship between language teaching and AI output is still being explored, and the guidelines for the use of generative AI in specific scenarios of language teaching need to be deeply analyzed and refined.

Literature Review


In 2023, the United Nations Educational, Scientific and Cultural Organization (UNESCO), as a promoter of global education development, released the Guidance for the Application of Generative AI in Education and Research Generative AI in Education and Research argues that when teachers use the technology to assist in teaching, they need to take into account the need to provide personalized support to students and help learners verify the credibility of their answers in a variety of ways (UNESCO, 2023). Help students solve problems and make up for shortcomings, so as to effectively improve the quality and efficiency of students' learning (Bauer et al.). ，2023）。 Kohnke et al.(2023) Language teachers are encouraged to explore the teaching possibilities of ChatGPT and make reasonable use of its rich teaching methods. Xu Jiajin and Zhao Chong (2024) believe that the core content is the idea of compiling prompts in the teaching process. In addition, the use of model language partners for speaking practice can give students a sense of accomplishment and fun similar to completing real communication (Dizon & Tang 2020). Five types of application scenarios have become the frontier of AI-supported language teaching, including automatic Q&A and chatbots, machine translation, corpora, intelligent guidance and intelligent assessment, etc. Yu Miao, Guo Zhiyan, 2024). However, when students use AI technology in their coursework, they need to ensure and verify the correctness of the sources of information generated, clearly show students how they can use the technology in their coursework, and distinguish which parts of the coursework are completed by the students themselves ( Joint Council for Qualifications，2023）。 Therefore, it is crucial to help teachers and students build the necessary AI literacy. At the same time, a survey study by the University of Hong Kong shows that over-reliance is currently the top concern of learners regarding the application of generative AI in higher education (Chan C K Y, Hu W, 2023). ）。In its guide to generative AI students, the University of Edinburgh specifically cautions that an over-reliance on smart technology will compromise learners' valuable opportunities to practice and develop higher-order thinking skills (The University of Edinburgh, 2024). Some scholars have proposed that the flipped classroom learning of language teaching by integrating generative AI to construct virtual tutors can significantly improve the mastery of memorable knowledge and transferable knowledge of learners at the higher education stage, and play a positive role in promoting the cultivation of learners' higher-order thinking such as complex problem solving (Zhai Xuesong, Chu Xiaoyan, et al., 2024）。 In addition, in view of the lack of generative AI content detection tools, teachers urgently need to change the way of teaching evaluation to grasp the real learning situation of students and provide corresponding guidance (Weber-Wulff D et al．，2023）。 Teachers should pay attention to software upgrades and interdisciplinary applications to enhance their role in language pedagogy and research (Feng Qinghua, Zhang Kaiyi,2024）。 In addition, the use of generative AI in the teaching process of language education will also bring about the digital divide of technological access fairness (Chu Xiaoyan, Shen Shusheng et al., 2024).

Aims and Objectives


United Kingdom's generative AI technology is among the highest in the world (Haiyan Gao, Youyou, Zhang, 2024). This paper compares the application status and implementation of generative AI technology in language teaching in higher education in the UK and Chinapathway, explore the potential of generative AI in language teaching and its impact on learning outcomes, and analyze the application of technology in language teaching in the two countries. Differences in teaching strategies and student learning experience, suggestions for optimizing the application of generative AI in the teaching of Chinese languages, and promoting communication and learning in the field of language education technology between the two countries, To provide language educators in the United Kingdom and China with a reference for the use of cross-cultural educational technologies.

Research Ideas and Methodology


(1) Sort out the educational products released by United Kingdom and China on the application of generative AI in language teaching, compare their main functions and models used, and analyze and compare their diversified development trends.


(2) review the academic literature on the application of generative AI in language teaching, and use meta-analysis methods to analyze it;


(3) In-depth communication with teachers, relevant language education researchers and students in United Kingdom universities. Through observation and conversation, the following data were obtained for quantitative and qualitative analysis:


1) teachers' and students' perceptions and attitudes towards generative AI;


2) the current situation and improvement plan of teachers and students' intelligent literacy, as well as the participation in relevant intelligent training;


3) Sort out the core AI technologies and application scenarios of teachers in language teaching;


4) Analyze how teachers in United Kingdom universities design human-computer collaboration tasks in language teaching, how to build deep dialogue learning models, and how to enable students to learn language-related problemsCritical reflection on technology-generated content during Q&A;


5) How to construct an intelligent teaching evaluation system for students in language teaching, including authentic evaluation, formative evaluation, reflective evaluation and diversified evaluation;


6) How to evaluate and monitor the academic integrity of students and researchers, and ensure information security and personal privacy.


(4) Participate in academic seminars on language teaching to understand the latest developments and achievements of generative AI in language teaching in United Kingdom universitiesto broaden their academic horizons and promote cooperation and exchanges between the UK and China in language teaching.