JOURNAL ARTICLE
Prompting Change: ChatGPT's Impact on Digital Humanities Pedagogy – A Case Study in Art History.
Published In: International Journal of Humanities & Arts Computing: A Journal of Digital Humanities, 2024, v. 18, n. 1. P. 58 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Guo, Qiuzi 3 of 3
Abstract
This article explores the transformative impact of ChatGPT, a Generative Pre-trained Transformers model, on humanities methodologies and its integration into a digital humanities (DH) course. The advent of ChatGPT enhances the capacity of people without coding experience to acquire, process, analyse and interpret art historical data, fostering a unique blend of generative AI development and humanistic inquiries. The article presents pedagogical experiences in incorporating ChatGPT, into a digital humanities course, with a focus on learning prompt engineering, a vital skill in handling art historical data. The iterative process of crafting prompts, receiving responses and refining prompts again enables the model to generate custom solutions tailored to individual inquiries. The practices of processing and analysing data are no longer arcane, exclusive to certain fields; they open up new avenues for research hypotheses that go beyond traditional qualitative and quantitative methods. The article underscores the immense significance of the prompts we input for the tasks at hand and the continuous nature of refinement and improvement in AI. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Humanities & Arts Computing: A Journal of Digital Humanities. 2024/03, Vol. 18, Issue 1, p58
- Document Type:Article
- Subject Area:Social Sciences and Humanities
- Publication Date:2024
- ISSN:1753-8548
- DOI:10.3366/ijhac.2024.0321
- Accession Number:176431503
- Copyright Statement:Copyright of International Journal of Humanities & Arts Computing: A Journal of Digital Humanities is the property of Edinburgh University Press 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.)
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