Write-Curate-Verify: A Case Study of Leveraging Generative AI for Scenario Writing in Scenario-Based Learning

Abstract

This case study explored the use of generative artificial intelligence (GenAI), specifically chat generative pretraining transformer (ChatGPT), in writing scenarios for scenario-based learning (SBL). Our research addressed three key questions: 1) how do teachers leverage GenAI to write scenarios for SBL purposes? 2) what is the quality of GenAI-generated SBL scenarios and tasks? and 3) how does GenAI-supported SBL affect students’ motivation, learning performance, and learning perceptions? A three-step prompting engineering process (write the prompts, curate the output, and verify the output, WCV) was established during the teacher interaction with GenAI in the scenario writing. Findings revealed that by using the WCV approach, ChatGPT enabled the efficient creation of quality scenarios for SBL purposes in a short timeframe. Moreover, students exhibited increased intrinsic motivation, learning performance, and positive attitudes toward GenAI-supported scenarios. We also suggest guidelines for using the WCV prompt engineering process in scenario writing.