JOURNAL ARTICLE

Guest Editors' Introduction: Humanities Going Digital: Teaching, Training and Research Experiences.

  • Published In: International Journal of Humanities & Arts Computing: A Journal of Digital Humanities, 2024, v. 18, n. 1. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Amaro, Raquel; Costa, Rute 3 of 3

Abstract

This article is a guest editors' introduction to a special issue of the International Journal of Humanities & Arts Computing. The issue focuses on the outcomes of the Erasmus+ Humanities Going Digital project, which aimed to develop innovative teaching methodologies and research activities in the field of digital humanities. The articles in this issue cover a range of topics, including integrating digital humanities courses into university-level language studies, integrating digital editions and methods for text editing and analysis in undergraduate literary studies, and using digital resources and research methods in the classroom. The articles also explore the potential of ChatGPT in art history pedagogy, the creation of digital archive-based activities for remembrance, and the use of quantitative network analysis to map archival bias. Additionally, the articles discuss enriching historical textual data through named entity recognition and transforming printed dictionaries into digitally exploitable lexical resources. Overall, this collection of articles provides insights into how the humanities are embracing digital technologies and the potential future directions of the field. [Extracted from the article]

Additional Information

  • Source:International Journal of Humanities & Arts Computing: A Journal of Digital Humanities. 2024/03, Vol. 18, Issue 1, p1
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2024
  • ISSN:1753-8548
  • DOI:10.3366/ijhac.2024.0317
  • Accession Number:176431499
  • 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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