mlsanityData to 7 Oct 2026

Exploring EFL students' prompt engineering in human-AI story writing: an Activity Theory perspective

arXiv 2306.01798 ↗First posted 1 Jun 2023cs.CY cs.AIcited by 3

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Abstract (arXiv)

This study applies Activity Theory to investigate how English as a foreign language (EFL) students prompt generative artificial intelligence (AI) tools during short story writing. Sixty-seven Hong Kong secondary school students created generative-AI tools using open-source language models and wrote short stories with them. The study collected and analyzed the students' generative-AI tools, short stories, and written reflections on their conditions or purposes for prompting. The research identified three main themes regarding the purposes for which students prompt generative-AI tools during short story writing: a lack of awareness of purposes, overcoming writer's block, and developing, expanding, and improving the story. The study also identified common characteristics of students' activity systems, including the sophistication of their generative-AI tools, the quality of their stories, and their school's overall academic achievement level, for their prompting of generative-AI tools for the three purposes during short story writing. The study's findings suggest that teachers should be aware of students' purposes for prompting generative-AI tools to provide tailored instructions and scaffolded guidance. The findings may also help designers provide differentiated instructions for users at various levels of story development when using a generative-AI tool.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 11 of its 43 references that are in the map. First posted on arXiv 1 Jun 2023.

Builds on

11 of 43 references.

References · 11

  1. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,222
  2. 2022Large Language Models Are Human-Level Prompt Engineerscited by 1,020
  3. 2023A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPTcited by 612
  4. 2021Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigmcited by 599
  5. 2022CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilitiescited by 245
  6. 2021Sparks: Inspiration for Science Writing using Language Modelscited by 80
  7. 2022Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation with Large Language Modelscited by 70
  8. 2022Creative Writing with an AI-Powered Writing Assistant: Perspectives from Professional Writerscited by 69
  9. 2022How to Prompt? Opportunities and Challenges of Zero- and Few-Shot Learning for Human-AI Interaction in Creative Applications of Generative Modelscited by 43
  10. 2023Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineeringcited by 40
  11. 2022Understanding EFL Student Idea Generation Strategies for Creative Writing with NLG Toolscited by 3

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Citing papers per year: 2024: 1; 2025: 2.

3 papers.