Teaching critical thinking and AI literacy through the library
As generative AI reshapes the landscape of higher education, libraries are uniquely positioned to respond, not only by supporting the ethical use of AI, but also by fostering student-centred, critically engaged learning experiences that go beyond algorithmic shortcuts.
This webinar explores innovative approaches to AI and student research, with a focus on the value of primary sources. In a world where technology can automate information retrieval, primary sources offer the transparency, context, and critical inquiry that build the very skills employers value most: curiosity, analytical thinking, and the ability to question and interpret data.
This session examines:
- Utilising digitised primary sources and special collections to design assignments that prioritise critical thinking and information literacy
- Leveraging the library as a hub for teaching AI literacy
- Implementing research practices that humanise technology’s role through collaborative curriculum design
Presenters highlight how inquiry-based learning, rooted in primary source engagement and cross-disciplinary partnerships, can reduce overreliance on AI tools and empower students to navigate them with agency, care, and creativity.
Featured speakers:
- Ben Lacey, Head of Engagement, AM
- Karen Jackson, Research and Academic Support Manager, University of Warwick
- Anne Kingsley, Dean of Educational Technology, Library, and Learning Resources, Diablo Valley College
- Emily Moss, Teaching and Learning Librarian, Diablo Valley College
Recent posts

Tuesday 30 September | 8am PDT | 11am EDT | 4pm BST
In this webinar, you'll learn about the AM Quartex difference as we highlight examples of seamless migrations, improved performance, and future-ready digital collections that deliver lasting impact for archives and their communities.

Tuesday 21 October | 8am PDT | 11am EDT | 4pm BST
From MARC records to AI-assisted indexing, this webinar in partnership with CHOICE offers an end-to-end look at how AM creates and enhances metadata for its primary source collections to connect diverse resources and content types with scholars.