More intelligent faculty development: Integrating GenAI in curriculum development programs.
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| Title: | More intelligent faculty development: Integrating GenAI in curriculum development programs. |
|---|---|
| Authors: | Khamis, Nehal1,2,3 (AUTHOR) nkhamis1@jhu.edu, Chen, Belinda1,3 (AUTHOR), Egan, Caroline4 (AUTHOR), Gaglani, Shiv3 (AUTHOR), Tackett, Sean1,3 (AUTHOR) |
| Source: | Medical Teacher. Nov2025, Vol. 47 Issue 11, p1739-1741. 3p. |
| Subject Terms: | *Generative artificial intelligence, *Human services programs, *Medical education, *Educational outcomes, *Teacher development, *Curriculum planning, *Role models, Teams in the workplace, Labor productivity, Chatbots |
| Abstract: | Educational challenge: Generative Artificial Intelligence (GenAI) has rapidly emerged as a potentially transformative tool in education. Faculty development (FD) programs, particularly in curriculum development (CD), are ideal settings for incorporating GenAI to benefit faculty and their learners. However, concerns about accuracy, bias, and ethical implications necessitate structured and responsible integration. Solution and implementation: We incorporated GenAI across five CD programs at Johns Hopkins University (JHU) in 2023–2024. We developed structured exercises using customizable prompts aligned with each step of the Six-Step Approach for Curriculum Development in Medical Education and encouraged learners to critically engage with GenAI during required exercises and assignments. Lessons learned and next steps: Structured exercises encouraged experimentation, critical evaluation, and innovation. Participants reported increased efficiency and creativity. Role modeling, balanced messages about GenAI's capabilities and limitations, and multidisciplinary teamwork were key enablers of success. This pilot offers an example of integration of GenAI into existing FD programs without requiring additional time or sacrificing rigor in CD processes. By sharing our findings globally, we hope to democratize FD and contribute to the responsible, scalable adoption of GenAI in diverse educational contexts. [ABSTRACT FROM AUTHOR] |
| Copyright of Medical Teacher is the property of Taylor & Francis 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 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 188804997 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: More intelligent faculty development: Integrating GenAI in curriculum development programs. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Khamis%2C+Nehal%22">Khamis, Nehal</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> nkhamis1@jhu.edu</i><br /><searchLink fieldCode="AR" term="%22Chen%2C+Belinda%22">Chen, Belinda</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Egan%2C+Caroline%22">Egan, Caroline</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gaglani%2C+Shiv%22">Gaglani, Shiv</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Tackett%2C+Sean%22">Tackett, Sean</searchLink><relatesTo>1,3</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Medical+Teacher%22">Medical Teacher</searchLink>. Nov2025, Vol. 47 Issue 11, p1739-1741. 3p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Human+services+programs%22">Human services programs</searchLink><br />*<searchLink fieldCode="DE" term="%22Medical+education%22">Medical education</searchLink><br />*<searchLink fieldCode="DE" term="%22Educational+outcomes%22">Educational outcomes</searchLink><br />*<searchLink fieldCode="DE" term="%22Teacher+development%22">Teacher development</searchLink><br />*<searchLink fieldCode="DE" term="%22Curriculum+planning%22">Curriculum planning</searchLink><br />*<searchLink fieldCode="DE" term="%22Role+models%22">Role models</searchLink><br /><searchLink fieldCode="DE" term="%22Teams+in+the+workplace%22">Teams in the workplace</searchLink><br /><searchLink fieldCode="DE" term="%22Labor+productivity%22">Labor productivity</searchLink><br /><searchLink fieldCode="DE" term="%22Chatbots%22">Chatbots</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Educational challenge: Generative Artificial Intelligence (GenAI) has rapidly emerged as a potentially transformative tool in education. Faculty development (FD) programs, particularly in curriculum development (CD), are ideal settings for incorporating GenAI to benefit faculty and their learners. However, concerns about accuracy, bias, and ethical implications necessitate structured and responsible integration. Solution and implementation: We incorporated GenAI across five CD programs at Johns Hopkins University (JHU) in 2023–2024. We developed structured exercises using customizable prompts aligned with each step of the Six-Step Approach for Curriculum Development in Medical Education and encouraged learners to critically engage with GenAI during required exercises and assignments. Lessons learned and next steps: Structured exercises encouraged experimentation, critical evaluation, and innovation. Participants reported increased efficiency and creativity. Role modeling, balanced messages about GenAI's capabilities and limitations, and multidisciplinary teamwork were key enablers of success. This pilot offers an example of integration of GenAI into existing FD programs without requiring additional time or sacrificing rigor in CD processes. By sharing our findings globally, we hope to democratize FD and contribute to the responsible, scalable adoption of GenAI in diverse educational contexts. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Medical Teacher is the property of Taylor & Francis 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.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=188804997 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/0142159X.2025.2473606 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 3 StartPage: 1739 Subjects: – SubjectFull: Generative artificial intelligence Type: general – SubjectFull: Human services programs Type: general – SubjectFull: Medical education Type: general – SubjectFull: Educational outcomes Type: general – SubjectFull: Teacher development Type: general – SubjectFull: Curriculum planning Type: general – SubjectFull: Role models Type: general – SubjectFull: Teams in the workplace Type: general – SubjectFull: Labor productivity Type: general – SubjectFull: Chatbots Type: general Titles: – TitleFull: More intelligent faculty development: Integrating GenAI in curriculum development programs. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Khamis, Nehal – PersonEntity: Name: NameFull: Chen, Belinda – PersonEntity: Name: NameFull: Egan, Caroline – PersonEntity: Name: NameFull: Gaglani, Shiv – PersonEntity: Name: NameFull: Tackett, Sean IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 0142159X Numbering: – Type: volume Value: 47 – Type: issue Value: 11 Titles: – TitleFull: Medical Teacher Type: main |
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