These are the best subject databases (meaning they collect articles by subject area) to start looking for articles on education related topics. You can do advanced and basic searches in these databases. You can also see our full list of Electronic Resources.
ERIC Update
The Education Resources Information Center (ERIC) is funded and operated by the Department of Education. As one of the world’s largest databases for educational research, ERIC provides access to a large collection of journal and non-journal literature in the field of education-related research. Editors of certain journals indexed in ERIC have received emails stating that the U.S. Department of Education will no longer include their journal in the ERIC database.
It is expected that the ERIC database will be reducing the collection by approx. 45% starting in April 24, 2025




There will be articles here related to education but also other topics. Use keyword searches here. You can also see our full list of Electronic Resources.

Full-text access to articles from 1,700 Elsevier journals covering the subject areas of science, social sciences, arts, and humanities.

The below video series were created for EDU 517 in 2024.
Where to Search:
The video below (16min) describes some key databases to search for Education related topics, the difference between subject databases, multidisciplinary databases & search engines. It includes a short Google Scholar demonstration at the end.
Search Concepts:
The video below (12min) describes strategies to determine your minimum search concepts and the difference between sensitivity and precision in searching.
Search Concepts:
The video below (4min) describes how to create a basic search strategy using boolean operators.
Search Concepts:
The video below (15min) describes how to execute a basic search in the database ERIC. It includes how to add concepts, use filters, and some database syntax such as quotes, truncation and proximity operators.
There are a lot of new discovery tools and search engines coming up that are enhanced with AI and LLMs. For the tools that are grounded in academic literature sources like Semantic Scholar or PubMed you can think about them as Academic AI Search Engines. Many of these tools are called Retrieval Augmented Generation (RAG), where they will be grounded in a data set and use an LLM to summarize the literature. To learn more about RAG systems, see this blog by Determind.ai
Below are some of these new Academic AI Search Engines you want to explore (if your class allows you to), with a warning that you will still need to critically evaluate the results (aka, does this paper seem legit?), and any guidance or summaries they are providing. Reading the actual paper is still very important, and applying your own critical thinking skills is even with these new research tools.
There are also very real and serious ethical and environmental concerns around the development, use, and sustainability of these tools. See this guide by Rebecca Sweetman for more information.
See this guide by UofT Libraries for some help evaluating these tools.
See this guide by McGill Libraries for help evaluating AI enhanced resources.