Examination of Delphi and Quasi-experimental Research Designs

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Research plays a vital role in more deeply understanding library science. Thoughtful consideration of how evidence-based research is conducted is essential to its effective use. Research helps professionals identify and explore areas of concern or interest in addition to providing possible solutions for known problems. The Delphi and quasi-experimental studies provide examples of research performed in library science.
The Delphi Study The Delphi study was developed by The RAND Corporation in the 1950s for the Air Force and was primarily used to forecast future events based on expert opinions (Wildemuth, 2009). Delphi studies provide an alternative to the traditional round-table type discussion (Cypher & Gant, 1971). The Delphi design
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These numbers were identical for round three. In total, 268 books and 34 journals were ranked with the top 100 representing items recommended for a core CME library.
This study focused on gathering information on books from its expert panel and does exemplify several areas of a Delphi study. First, the researchers nominated a panel to recruit experts and make sure the instruments used were clear. To reduce bias, any book or journal affiliated with a panel member was eliminated. Demographics were noted by sub-groups, and each panel member was asked to rate his expertise. A minimum number of votes (10) was used as a cutoff for books indicated as most helpful to novice learners. In addition, each panel member was asked to waive anonymity with names published in the report. Forty-three members agreed.

The Quasi-experimental Study A quasi-experimental study is a subcategory of experimental design where randomization of participants is not possible or not needed (Wildemuth, 2009). These studies occur in natural settings when limited control over the variables is possible. The independent variable (treatment) is manipulated to see if a causal relationship exists (Haas & Kraft, 1984). Naturally occurring groups such as classes are generally used. The goal is “to produce reliable causal knowledge” (Haas & Kraft, p. 229). Internal and external validity are important to this design. Internal validity is determined when
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