Skip to Main Content

AI: Artificial Intelligence Resources

Information and resources for Artificial Intelligence applied to academic environments

AI and Database Searching

As generative AI becomes more popular, several of the article databases UND subscribes to are adding AI-assisted features.  This page has videos explaining how they work, as well as some advice on how to use AI to help you with keyword searching on any database.

EBSCO Natural Language Search

JSTOR Semantic Scholar

This video will show you how to access Semantic Scholar in JSTOR, and possible ways to use it.

Primo Research Assistant

This is a tool within the CFL Library catalog to use AI to find and summarize articles, books, and more.

This first video shows how to access the tool from the library homepage:

This second video shows how to use it and how to understand its results:

AI and Keyword Searching

You can use commercial AIs like ChatGPT, Gemini, and Claude to help you with your search strategy for any database.

Let's say you're researching whether giving elementary school students tablets has on literacy scores, but you need help turning that into a keyword search.  You can use a prompt like this:

I am an undergrad education major at the University of North Dakota.

I am researching what effect giving elementary school students tablets has on literacy scores.

Can you suggest some databases to try, and some keywords and search strategies?

The AI can, if web searching is on, check what databases are available at Chester Fritz Library, recommend some plausible options, and make suggestions for some keyword combinations.  When I tried it just now, it had these, meant to work with Ebsco Advanced Search:

(tablets OR "digital devices" OR iPads OR "educational technology")
AND
("elementary students" OR "primary school" OR "early grades")
AND
("literacy scores" OR "reading achievement" OR "reading comprehension")

It will also suggest ways to limit the search, provide search tips, and you can ask it to explain concepts further.  For example, I asked it to explain why it chose the keyword combinations it did.  It explained how "Boolean searching" works, why it grouped the keywords like it did, and closed with this summary:

Think of it as looking for the overlap between three circles:

  • One for articles about technology
  • One for those about elementary students
  • One for those measuring literacy outcomes

Only the articles in the middle—the intersection of all three—are what you’re interested in.