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

TitleWrite-Curate-Verify: A Case Study of Leveraging Generative AI for Scenario Writing in Scenario-Based Learning
Authors
KeywordsGenerative artificial intelligence (GenAI)
intrinsic motivation
prompt engineering
scenario-based learning (SBL)
Issue Date18-Mar-2024
PublisherInstitute of Electrical and Electronics Engineers
Citation
IEEE Transactions on Learning Technologies, 2024, v. 17, p. 1313-1324 How to Cite?
AbstractThis 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.
Persistent Identifierhttp://hdl.handle.net/10722/348046

 

DC FieldValueLanguage
dc.contributor.authorBai, Shurui-
dc.contributor.authorGonda, Donn Emmanuel-
dc.contributor.authorHew, Khe Foon-
dc.date.accessioned2024-10-04T00:31:07Z-
dc.date.available2024-10-04T00:31:07Z-
dc.date.issued2024-03-18-
dc.identifier.citationIEEE Transactions on Learning Technologies, 2024, v. 17, p. 1313-1324-
dc.identifier.urihttp://hdl.handle.net/10722/348046-
dc.description.abstractThis 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.-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers-
dc.relation.ispartofIEEE Transactions on Learning Technologies-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectGenerative artificial intelligence (GenAI)-
dc.subjectintrinsic motivation-
dc.subjectprompt engineering-
dc.subjectscenario-based learning (SBL)-
dc.titleWrite-Curate-Verify: A Case Study of Leveraging Generative AI for Scenario Writing in Scenario-Based Learning-
dc.typeArticle-
dc.identifier.doi10.1109/TLT.2024.3378306-
dc.identifier.scopuseid_2-s2.0-85188460123-
dc.identifier.volume17-
dc.identifier.spage1313-
dc.identifier.epage1324-
dc.identifier.eissn1939-1382-
dc.identifier.issnl1939-1382-

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