Google Scholar is the search company Google's engine for searching scholarly or academic materials. Google Scholar searches many publisher's journals, academic websites, institutional repositories, and other similar sources, including the ScienceDirect and JSTOR databases. In Google Scholar you can find:
Google Scholar is strongest in science, technology, and medicine.
Like regular Google, Google Scholar using a "relevance" algorithm to determine the ranking of the results. This takes into account the position of your search words in the titles, abstracts, and other descriptive material about the document.
The "Scholar" in Google Scholar is not the equivalent of the "Scholarly Journals" or "Peer-Reviewed Journals" check boxes in the databases. Scholarly in this case refers to non-commercial sites, like universities, and to publisher websites. Google Scholar does have scholarly and peer-reviewed articles, but also has non-reviewed articles and presentations, pre-prints (pre-publication versions of articles), reports, and a wide variety of other materials that exist on scholarly websites or have been cited in other scholarly works.
You can set Google Scholar to recognize which school you are from.
Be sure to check the main title link, which leads to the "official version", any other links, which often lead to freely accessible versions of the articles, AND the SCSU Journal Finder/ViewIt link, which will check if the article is accessible in our databases.
Microsoft Academic Search is Microsoft's version of a library database. It contains records for nearly 200 million articles (as of 2/2018). However, it's the way that MA treats those articles that is different from a traditional database. The articles have been analyzed for semantic content, not just indexed for keywords, so related concepts will automatically be searched together. This means the user is not as vulnerable to quirks in the authors' phrasing. MA also looks at the relationships between articles, based on references, citations, and authors, as well as "semantic similarity."
These videos will give you some ideas on how MA can be used. But the best way to explore this is to try it out. It's not quite like searching a regular database.
Transcript coming soon