AI and metadata in the classroom: A work-integrated learning project

Students in two undergraduate courses explored textual data and scholarly communication through a work-integrated learning project focused on journal metadata migration. They participated in workshops on manual metadata entry, AI prompt generation, and web scraping and scripting. Taking multiple approaches allowed students with diverse levels of digital literacy skills to critically engage with a real-world problem.In Team-GPT, students experimented with two artificial intelligence models, Claude Sonnet and GPT-4o, to convert HTML from a journal website into XML matching the Open Journal Systems schema. They broke the problem into smaller, manageable tasks, testing and refining reusable AI prompts. Along the way, they asked questions about journal practices and metadata challenges, gaining deeper insights into scholarly publishing. For a final assignment, each student created 18 metadata records using the AI-assisted workflow. These records will be evaluated alongside human-created metadata and outputs from a scripted approach to determine accuracy.This work-integrated learning project had substantial benefits for the journal, the library, and students. The journal editorial board will be able to make an informed decision about the migration to Open Journal Systems. Librarians, also the instructors for these courses, blended professional practice into pedagogy and made advances on a library publishing project. Students made meaningful contributions to the Open Access movement. We all practiced divergent problem-solving and continued to build informed opinions on the benefits and challenges of working with artificial intelligence.In this presentation, librarians and students will share our insights into how AI tools and metadata projects can be integrated into educational contexts. We will also discuss how work-integrated learning projects can effectively bridge pedagogy and practice, equipping students with critical skills in digital literacy, problem-solving, and scholarly communication.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-19
DOI
https://doi.org/10.5281/zenodo.17161812
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
0.00
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article

AI and metadata in the classroom: A work-integrated learning project

Elizabeth Stregger, Stephen J. Geier, Duc Tri Dang, Sabrina Sandy
Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

AI and metadata in the classroom: A work-integrated learning project

Elizabeth Stregger, Stephen J. Geier, Duc Tri Dang, Sabrina Sandy
article en

Abstract

Students in two undergraduate courses explored textual data and scholarly communication through a work-integrated learning project focused on journal metadata migration. They participated in workshops on manual metadata entry, AI prompt generation, and web scraping and scripting. Taking multiple approaches allowed students with diverse levels of digital literacy skills to critically engage with a real-world problem.In Team-GPT, students experimented with two artificial intelligence models, Claude Sonnet and GPT-4o, to convert HTML from a journal website into XML matching the Open Journal Systems schema. They broke the problem into smaller, manageable tasks, testing and refining reusable AI prompts. Along the way, they asked questions about journal practices and metadata challenges, gaining deeper insights into scholarly publishing. For a final assignment, each student created 18 metadata records using the AI-assisted workflow. These records will be evaluated alongside human-created metadata and outputs from a scripted approach to determine accuracy.This work-integrated learning project had substantial benefits for the journal, the library, and students. The journal editorial board will be able to make an informed decision about the migration to Open Journal Systems. Librarians, also the instructors for these courses, blended professional practice into pedagogy and made advances on a library publishing project. Students made meaningful contributions to the Open Access movement. We all practiced divergent problem-solving and continued to build informed opinions on the benefits and challenges of working with artificial intelligence.In this presentation, librarians and students will share our insights into how AI tools and metadata projects can be integrated into educational contexts. We will also discuss how work-integrated learning projects can effectively bridge pedagogy and practice, equipping students with critical skills in digital literacy, problem-solving, and scholarly communication.

Zenodo (CERN European Organization for Nuclear Research)
Mount Allison University (CA)
Quality Education
Openalex Percentile: Top 13%
Research Data Management Practices
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