Understanding EFL Student Idea Generation Strategies for Creative Writing with NLG Tools
Not on the map. Why?
Abstract (arXiv)
Natural language generation (NLG) is a process within artificial intelligence where computer systems produce human-comprehensible language texts from information. English as a foreign language (EFL) students' use of NLG tools might facilitate their idea generation, which is fundamental to creative writing. However, little is known about how EFL students interact with NLG tools to generate ideas. This study explores strategies adopted by EFL students when searching for ideas using NLG tools, evaluating ideas generated by NLG tools and selecting NLG tools for ideas generation. Four Hong Kong secondary school students attended workshops where they learned to write stories comprising their own words and words generated by NLG tools. After the workshops, they answered questions to reflect on their writing experience with NLG tools. In a thematic analysis of the written reflections, we found students may have existing ideas when searching for ideas and evaluating ideas with NLG tools. Students showed some aversion to ideas generated by NLG tools and selected NLG tools that generated a greater quantity of ideas. The findings inform our understanding of EFL students' concerns when using NLG tools for idea generation and can inform educators' instruction to implement NLG tools for classroom creative writing.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 7 of its 58 references that are in the map. First posted on arXiv 4 Jun 2022.
Builds on
7 of 58 references.
References · 7
- 2017Attention Is All You Needcited by 60,361
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2020Language Models are Few-Shot Learnerscited by 32,419
- 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,234
- 2022CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilitiescited by 249
- 2017Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluationcited by 206
- 2019Do Massively Pretrained Language Models Make Better Storytellers?cited by 90
Built on by
Citing papers per year: 2023: 2; 2024: 0; 2025: 1.
3 papers.
- 2023Exploring EFL students' prompt engineering in human-AI story writing: an Activity Theory perspectivecited by 3
- 2023Cases of EFL Secondary Students' Prompt Engineering Pathways to Complete a Writing Task with ChatGPTcited by 2
- 2025Exploring EFL Secondary Students' AI-generated Text Editing While Composition Writingcited by 0
- 2025Exploring EFL Secondary Students' AI-generated Text Editing While Composition Writing13 May 2025
- 2023Cases of EFL Secondary Students' Prompt Engineering Pathways to Complete a Writing Task with ChatGPT19 Jun 2023
- 2023Exploring EFL students' prompt engineering in human-AI story writing: an Activity Theory perspective1 Jun 2023