Volume 12, Number 3

In Search of the Prompt that Produces useful Written Corrective Feedback for L2 Composition Classes

  Authors

James R. Brawn, Hankuk University of Foreign Studies, South Korea

  Abstract

The use of artificial intelligence (AI) in language education may be in its infancy, but technological advances, especially natural language processing, will lead to its widespread adoption far sooner than many may think. For example, large language models (LLMs) like ChatGPT are often used when individuals utilize AI systems. This means that researchers in second language learning must begin evaluating the utility of AI-based tools for second language instruction. This study describes the importance of prompt engineering in designing effective prompts for second-language writing feedback. This action research (AR) study revealed that prompts could constrain the usefulness of AI-generated feedback and suggests that, like LLMs, users are few-shot learners. Adapting the prompts and understanding the limitations and constraints that these prompts produce will allow instructors to design prompts to make ChatGPT and other AI-based applications more helpful to learners in second-language composition classes.

  Keywords

prompt engineering; written corrective feedback; AI; ChatGPT; L2 composition.