핵심 개념
Generative AI tools like ChatGPT are reshaping second language learning and teaching, requiring a critical understanding of their capabilities, limitations, and implications for learner and teacher agency.
초록
The article examines the impact of generative AI, particularly ChatGPT, on second language learning and teaching. It highlights the transformative potential of AI in areas such as language practice, writing assistance, and personalized learning, while also discussing the challenges posed by AI's limitations in understanding language pragmatics and sociocultural nuances.
The author argues that the appropriate initial response to AI in instructed second language acquisition (SLA) settings should be the development of critical AI literacy in both learners and teachers. This involves understanding the nature of generative AI, its power dynamics, and the ethical concerns surrounding its use.
The article explores the concept of distributed agency, where agency is seen as a relational and emergent property shared between human users and AI systems. It examines how AI can enhance or constrain learner and teacher agency, and how ecological frameworks can help illuminate the dynamic relationship between humans and AI in language learning.
The article also discusses the varied reach and power of AI, from narrow AI tools targeting specific language tasks to general-purpose systems like ChatGPT. It explores the potential for customized or hybrid AI systems to address language-specific needs, as well as the integration of AI into immersive learning environments.
The author emphasizes the importance of understanding AI's limitations in areas such as pragmatics, sociocultural awareness, and multimodal communication, and how these limitations can be addressed through instructional strategies that promote critical reflection, collaborative learning, and the maintenance of individual voice and creativity in writing.
The article concludes by framing the human-AI relationship in language learning through the lens of sociomaterialism and relational pedagogy, highlighting the need for a holistic understanding of the complex, ever-changing dynamics between learners, teachers, and AI tools.
통계
"AI asserts control: "I'm sorry, Dave, I'm afraid I can't do that.""
"Machine learning and enhanced media abilities in AI systems will move them to ever higher levels of ability in language output (Patil et al., 2024), reasoning capabilities (Anderson, 2024), and multimodal integration (Metz, 2024)."
"Advances in machine learning technology such as reinforcement learning and genetic algorithms point to the potential of AI to reconfigure itself for improved performance without human intervention (Dattathrani & De', 2023)."
"Through AI, the changes in the relationship of learner–tool–environment are likely to be profound, representing dynamically shifted ecosystems for language education."
"Generative AI relies on a mathematical rather than a linguistic model of language. LLMs work so well at generating language because their training is based not on fixed rules but on actual language use (namely, its training corpus)."
"Generative AI systems use a quite different approach to developing language abilities, one that has proven to be phenomenally successful."
"Paradoxically, the highly sophisticated system that creates these extraordinary texts has no real understanding of what they mean."
인용구
"Through their semiotic symbol processing capability, they [information systems] are also digital actors capable of performing social action on behalf of humans and organisations" (Ågerfalk, 2020, p.2).
"Humans make meaning by assembling linguistic signs but also by pooling language (and all their languages) together with whatever other bits of semiotic repertoire they have, to the point that meaning making is always multisensory, multimodal, and always involving much more than language" (Ortega, 2019, pp. 290-291).
"Through teaching students how they can tangibly use these tools in their own learning, educators can create strong foundations for their students' immediate learning and long-term use of AI-based tools in educational and professional contexts" (Tseng & Warschauer, 2023, p. 260).