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PIO 201-08 (P. Thayer) - More Than a Head Count : Searching Databases

Resources for researching, writing, and presenting final class paper and presentation

Steps for Effective Database Searching

Step Task
1 Transform your topic as a research question
2 Identify key terms within your research question.  
3 Construct a search statement that consists of your key terms and appropriate Boolean operators.  You may also need to incorporate parentheses as well.
Run your search.
5 Assess your results.  
6 If the results aren't useful, go to Step 7.  Otherwise, you're done.
7 Construct a search statement using variations of your key terms.
8 Run your revised search
9 Assess results of revised search. 
10 If results of revised search are not useful, repeat Steps 7-9 until you get an acceptable set of results.  Otherwise, you're done.  

 

Transforming a topic into a research question

  • Transforming a topic into a research question forces you to focus your research and overall saves you time and effort
  • Even if your topic is one concept, you should develop a research question that is as clear, concise, and complete as possible.  

Examples

Topic Research Question
Medical marijuana How does medical marijuana help people with chronic pain?
Veganism In what ways can veganism help the environment?

What are key terms?

  • Significant words or phrases in a question or sentence
  • Include names, places, events, and concepts
  • Don't usually include functional words like articles, prepositions, conjunctions, etc 

What are Boolean operators?

•Use for searches involving more than one key term
•Commonly-used operators
  • AND - narrows the scope of a search
  • OR - broadens the scope of a search
  • NOT - narrows the scope of a search by excluding results that include specified terms
​​​​More on Boolean operators - •​Concordia University Libraries

More about parentheses

  • Whatever is in parentheses is processed first (remember order of operations from your math classes?)
  • Examples 
    • race OR bias AND algorithms – bias AND algorithms acted on first
    • (race OR bias) AND algorithms – race OR bias acted on first