Lessons Learned from Creating Course Content using Generative AI.
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| Title: | Lessons Learned from Creating Course Content using Generative AI. |
|---|---|
| Authors: | Hatakka, Mathias1 mathias.hatakka@oru.se, Ask, Andreas1 andreas.ask@oru.se |
| Source: | Proceedings of the European Conference on e-Learning (ECEL). 2025, p146-153. 8p. |
| Subject Terms: | *Course content (Education), *Digital learning, *Generative artificial intelligence, *Instructional systems design, *Curriculum planning, *Learning, ChatGPT |
| Company/Entity: | OpenAI Inc. |
| Abstract: | The release of generative AI tools such as OpenAI's ChatGPT has sparked interest in their implications for education. While early discourse emphasized concerns about plagiarism and academic integrity, recent studies have begun to explore the potential of these tools to support teaching and learning. This paper presents a case study on the use of ChatGPT in the redesign of a first-year systems development project course for informatics students. The course required the integration of various course materials, making it a suitable context for evaluating generative AI's role in course material development. The aim of the study is to present lessons learned from using ChatGPT in the development of course content. Drawing on our practical experience as course designers and instructors, we outline lessons learned from using ChatGPT in the creation of key course elements, including case descriptions, SQL scripts, and requirements specifications. We found that ChatGPT was effective for generating coherent initial drafts of content, but its outputs often required refinement to ensure pedagogical alignment. Challenges included the generation of misleading or irrelevant non-functional requirements and logically flawed code, despite syntactic correctness. Our findings highlight the importance of prompt engineering, critical review, and maintaining a human-in-the-loop approach. We conclude that while ChatGPT can significantly reduce development time for some tasks, it should be used as a complementary tool. This study contributes practical insights to the growing field of AI-assisted education. [ABSTRACT FROM AUTHOR] |
| Copyright of Proceedings of the European Conference on e-Learning (ECEL) is the property of Academic Conferences & Publishing International Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 189744799 AccessLevel: 6 PubType: Conference PubTypeId: conference PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Lessons Learned from Creating Course Content using Generative AI. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hatakka%2C+Mathias%22">Hatakka, Mathias</searchLink><relatesTo>1</relatesTo><i> mathias.hatakka@oru.se</i><br /><searchLink fieldCode="AR" term="%22Ask%2C+Andreas%22">Ask, Andreas</searchLink><relatesTo>1</relatesTo><i> andreas.ask@oru.se</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Proceedings+of+the+European+Conference+on+e-Learning+%28ECEL%29%22">Proceedings of the European Conference on e-Learning (ECEL)</searchLink>. 2025, p146-153. 8p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Course+content+%28Education%29%22">Course content (Education)</searchLink><br />*<searchLink fieldCode="DE" term="%22Digital+learning%22">Digital learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Instructional+systems+design%22">Instructional systems design</searchLink><br />*<searchLink fieldCode="DE" term="%22Curriculum+planning%22">Curriculum planning</searchLink><br />*<searchLink fieldCode="DE" term="%22Learning%22">Learning</searchLink><br /><searchLink fieldCode="DE" term="%22ChatGPT%22">ChatGPT</searchLink> – Name: SubjectCompany Label: Company/Entity Group: Su Data: <searchLink fieldCode="DE" term="%22OpenAI+Inc%2E%22">OpenAI Inc.</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The release of generative AI tools such as OpenAI's ChatGPT has sparked interest in their implications for education. While early discourse emphasized concerns about plagiarism and academic integrity, recent studies have begun to explore the potential of these tools to support teaching and learning. This paper presents a case study on the use of ChatGPT in the redesign of a first-year systems development project course for informatics students. The course required the integration of various course materials, making it a suitable context for evaluating generative AI's role in course material development. The aim of the study is to present lessons learned from using ChatGPT in the development of course content. Drawing on our practical experience as course designers and instructors, we outline lessons learned from using ChatGPT in the creation of key course elements, including case descriptions, SQL scripts, and requirements specifications. We found that ChatGPT was effective for generating coherent initial drafts of content, but its outputs often required refinement to ensure pedagogical alignment. Challenges included the generation of misleading or irrelevant non-functional requirements and logically flawed code, despite syntactic correctness. Our findings highlight the importance of prompt engineering, critical review, and maintaining a human-in-the-loop approach. We conclude that while ChatGPT can significantly reduce development time for some tasks, it should be used as a complementary tool. This study contributes practical insights to the growing field of AI-assisted education. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Proceedings of the European Conference on e-Learning (ECEL) is the property of Academic Conferences & Publishing International Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 8 StartPage: 146 Subjects: – SubjectFull: Course content (Education) Type: general – SubjectFull: Digital learning Type: general – SubjectFull: Generative artificial intelligence Type: general – SubjectFull: Instructional systems design Type: general – SubjectFull: Curriculum planning Type: general – SubjectFull: Learning Type: general – SubjectFull: ChatGPT Type: general – SubjectFull: OpenAI Inc. Type: general Titles: – TitleFull: Lessons Learned from Creating Course Content using Generative AI. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Hatakka, Mathias – PersonEntity: Name: NameFull: Ask, Andreas IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: 2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20488637 Titles: – TitleFull: Proceedings of the European Conference on e-Learning (ECEL) Type: main |
| ResultId | 1 |
