Generative Artificial Intelligence for Language Learning and Teaching: Opportunities, Challenges, and Ethical Considerations
摘要截稿:
全文截稿: 2025-01-31
影响因子: 1.979
期刊难度:
CCF分类: 无
Overview
This special issue delves into the impact of generative artificial intelligence (GenAI) on foreign/second language (L2) learning and teaching, including its effectiveness, potential limitations, and ethical considerations.
Guest editors:
Prof. Peijian Paul Sun, Zhejiang University, Hangzhou, China. luapnus@zju.edu.cn
Prof. Lin Sophie Teng, Zhejiang University, Hangzhou, China. lin.teng@zju.edu.cn
Dr. Max Wolpert, Zhejiang University, Hangzhou, China; McGill University, Montreal, Canada. max.a.wolpert@mail.mcgill.ca
Special issue information:
This special issue (SI) aims to explore the opportunities, challenges, and ethical considerations arising from the integration of generative artificial intelligence (GenAI) in foreign/second language (L2) learning and teaching. Specifically, this SI seeks to examine the effects of GenAI on L2 learning and teaching, delve into potential obstacles and limitations of using GenAI in L2 learning and teaching, and address the ethical concerns associated with the use of GenAI in L2 learning and teaching.
The advent of GenAI, such as ChatGPT, Copilot, and Bard, has sparked considerable interest in its potential applications in language education. Unlike traditional AI technology, GenAI utilizes deep learning models to produce human-like content across various modalities, including text, image, audio, and video. As such, GenAI has the potential to revolutionize the way language learning and teaching are approached. In particular, it introduces a new pedagogical paradigm for teachers, wherein learners can engage in interactive and personalized language learning experiences. However, our understanding of the influence of GenAI on L2 learning and teaching is limited. There is an urgent need to investigate the role of GenAI in L2 learning and teaching to better prepare students and teachers for the GenAI-supported education in the future.
Therefore, this special issue attempts to provide insights into the opportunities, challenges, and ethical considerations associated with the implementation of GenAI in L2 learning and teaching. The scope of this special issue will include but not be limited to the following aspects.
Opportunities:
The SI will examine the potential opportunities offered by GenAI in L2 learning and teaching. This includes exploring 1) how GenAI can enhance language acquisition by providing personalized and adaptive learning experiences; 2) the potential of GenAI to facilitate language production and performance; and 3) the role of GenAI in empowering L2 learning and teaching, such as through enhanced positive psychology and refined interactive and immersive learning environments.
Challenges:
The SI will delve into the challenges and limitations of integrating GenAI in L2 learning and teaching. This includes investigating 1) the technical challenges associated with the development and implementation of GenAI tools, such as ensuring accuracy, reliability, and adaptability; 2) the pedagogical challenges of incorporating GenAI in instructional practices from engagement, technology acceptance, and technology adoption lenses; and 3) the potential issues related to equity and access to ensure that GenAI is inclusive and beneficial for all stakeholders.
Ethical Considerations:
The SI will critically examine the ethical considerations stemming from the use of GenAI in L2 learning and teaching. This includes 1) how to seek a balance between GenAI-driven instruction and the essential role of human educators; 2) how to use GenAI tools responsibly, with a focus on the well-being and educational benefit of L2 learners; and 3) how to ensure fairness in language education in the era of GenAI.
Apart from the scope mentioned above, this SI also encourages investigations into the intersection of GenAI and L2 learning and teaching from interdisciplinary perspectives. For instance, incorporating machine learning or neuroscientific approaches may provide valuable insights into how the mechanisms of machine or brain learning can inform GenAI-supported L2 learning and teaching.
To sum up, this collection of papers will not only shed light on the role of GenAI in L2 learning and teaching but also contribute to the broader field of language education and provide valuable insights for educators, researchers, and policymakers involved in language education.
Manuscript submission information:
Abstract submission deadline: 31st March, 2024
Short-listed abstracts announced: 15th April, 2024
Submission open date: 1st September, 2024
Final manuscript submission deadline: 31st January, 2025