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Current Project

A two-year empirical study on GenAI literacy in library and information science education.

Overview

This two-year research project examines how generative artificial intelligence (GenAI) is reshaping learning, instruction, and workforce preparation in library and information science (LIS) education. The project aims to generate empirical knowledge that informs the design of GenAI-related curricular and professional learning experiences that prepare the future library workforce for GenAI-mediated information environments.

Approach

Research Philosophy

  • Empirically grounded: We generate empirical knowledge from real LIS students, instructors, and librarians—not assumptions—to inform curriculum and professional development design.
  • Competency-informed: Guided by established learning frameworks including McClelland's competency model, Bloom's taxonomy, activity-oriented learning, and self-regulated learning theory.
  • Participatory by design: Students, instructors, and librarians are co-designers of GenAI literacy materials—not just research subjects. Participatory design ensures relevance and usability.
Research Vision
Empirical Rigor
Equity & Access
Co-design
Impact

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Deliverables

Project Outputs

The project will produce two primary deliverables: an instructional blueprint mapping LIS learning tasks to GenAI literacy requirements, and a GenAI literacy toolkit offering domain-specific instructional guidance, verification supports, deskilling-risk indicators, and assessment rubrics.

These deliverables are designed as a replicable and adaptable model for responsible integration of GenAI literacy across professional education contexts beyond LIS.

Collaboration

Work With Us

We welcome partnerships with LIS educators, library practitioners, researchers, and institutions interested in GenAI literacy and workforce preparation. If you are interested in collaborating or participating in research, please get in touch.

Contact us
Partners

Affiliations & Partnerships [ to be changed depending on real data]

Lead Institution

University of Wisconsin–Milwaukee

Partner Institution

Florida State University

Partner Institution

University of Texas at Austin

Professional Organization

Association for Information Science & Technology