Improving EFL students’ cultural awareness: Reframing moral dilemmatic stories with ChatGPT

Abstract

Classroom teachers are usually responsible for creating materials to meet students' needs and course requirements. The arrival of generative AI, such as ChatGPT, offers EFL teachers an opportunity to regularly collaborate with AI chatbots to create new source materials. The writing experiments in this study considered how to effectively and ethically work with generative AI to produce culturally appropriate EFL teaching materials. The experiments involved co-producing moral dilemmatic stories with ChatGPT to support a new Chinese EFL curriculum unit on “Morals and Virtues”. We draw on Lo's (2023a, 2023b) CLEAR framework for prompt engineering to generate appropriate stimulus materials. We refer to Durkheim's (1961) sociological theory on morality and Bernstein's (1971, 1981, 2003) concept of framing to unpack how moral decisions might be framed as dilemmas in particular sociocultural contexts. We then mobilize Martin and White's (2005) appraisal framework to uncover the patterns of cultural biases embedded in the AI-generated text. We propose a two-step “Navigation and Generation” method for effective prompt engineering with generative AI: first navigating the AI chatbot to a clear and consistent positioning around a concept, and then requesting the AI chatbot to generate text based on the clarifications generated in the first step. Our appraisal analysis indicates that WEIRD (western, educated, industrial, rich, and democratic) cultural values are embedded in moral dilemmatic stories generated by ChatGPT. EFL Teachers need to be aware of how these values are presented to encourage critical cultural awareness in their students.

Keywords

• Prompt engineering
• ChatGPT
• Morality
• Cultural awareness
• Cultural biases
• Appraisal theory