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Artificial Intelligence + ACRL Frameworks

This libguide explores the integration of generative AI with the Framework for Information Literacy. It examines authority, information creation, value, research inquiry, and scholarship as conversation in relation to generative AI.

Searching as Strategic Exploration

Searching for information is often nonlinear and iterative, requiring the evaluation of a range of information sources and the mental flexibility to pursue alternate avenues as new understanding develops.

—Framework for Information Literacy for Higher Education, Page 22

Scholarship as conversation: Comparison

How does each system help researchers explore a research question?​

How does each system help researchers explore a research question?​

Scholarly

Subject headings, author-supplied topics, and abstract keywords link several articles together when indexed by a database.​

Generative AI

The breadth of the LLM's corpus allows Generative AI to present information that appears complete.​

How does the operation of each system impact barriers to adoption?​

How does the operation of each system impact barriers to adoption?​

Scholarly

Structured search strategies increase barriers to using this tool.​

Generative AI

Natural Language Processing reduces barriers to using this tool. Although effective deployment of prompt engineering improves the chances of successful outcomes.​

How does feedback from the system help generate new avenues of exploration?​

How does feedback from the system help generate new avenues of exploration?​

Scholarly

Similar articles are provided in the same search. Metadata serves as a bridge between similar materials. Users can engage with the material to ask new questions.​

Generative AI

Users are actively encouraged to iterate on the previous question & answer set.​