BACKGROUND: In recent years, medical and physician assistant (PA) education has moved towards a competency based model. This model encourages teaching students to “know how” to use what they learn in practice rather than simply gain a large knowledge base. This allows students to garner a deeper understanding of the material. Active learning strategies such as flipped classroom and interactive learning, have gained great support in recent years. These models have helped further the ability of universities to move towards these competency based education models. At the core of these newer teaching and learning modalities are the instructors themselves. They play a vital role in not only what a student learns, but how well they learn it.
LITERATURE REVIEW: A literature review highlights both the importance of hiring quality instructors as well as the importance of their ability to fulfill these new teaching models. There have been numerous studies on how effective teaching influences a student’s performance in the classroom. To date, there has not been any research on how to increase the probability of hiring an effective instructor from day one.
PROPOSED PROJECT: The objective of this study is to develop a tool that would help employers screen for potentially less qualified candidates. The proposed tool is a questionnaire that would be filled out by potential employees and would raise a red flag if a potentially concerning answer choice was selected. The validity of this questionnaire will be tested by comparing current physician assistant didactic and clinical instructors’ scores on the questionnaire, to their respective student evaluations.
CONCLUSION: It is predicted that a “red flag” score on/this questionnaire will correlate with poor instructor scores on student evaluations. Successful validation and deployment of this tool would allow students to be instructed by the best possible instructors, bettering their education.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/26934 |
| Date | 02 November 2017 |
| Creators | Verbruggen, Connor |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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