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Retrospective analysis of a STEM outreach event reveals positive influences on student attitudes toward STEM careers but not scientific methodology.

A J CrawfordCassandra L HaysSarah L SchlichteSydney E GreerHalle J MallardRyan M SinghMartina A ClarkeAlicia M Schiller
Published in: Advances in physiology education (2021)
Substantial, involved, and expensive efforts to promote the dissemination of scientific knowledge and career interest in Science, Technology, Engineering, and Mathematics (STEM) are enthusiastically supported by many scientific, federal, and local organizations. The articulated underlying goals for these efforts include an enhanced public understanding of science and science-related policy, an increased diversity in STEM careers, and an increase in the future STEM workforce. This effort is primarily driven by an underperformance of the United States that includes poor test performance and limited number of students pursuing STEM degrees. Despite this investment, attitudes toward STEM have not notably changed. The goal of this project was to determine students' attitudes toward STEM in response to a previously established scientific outreach event. This event was used to address three common goals in STEM outreach: STEM literacy, diversity and inclusion, and career preparedness. We found there was a notable difference in the attitudes toward scientific activities and interest in pursuing a "Science Career" after participation in this event. Strikingly, interest in hypothesis development, the keystone of all STEM disciplines, was the least liked of all the activities offered during the event. Our data suggest that events designed to enhance interest in pursuing a STEM career may benefit from different elements compared with events designed to increase understanding of STEM literacy concepts, such as hypothesis development.
Keyphrases
  • public health
  • healthcare
  • mental health
  • emergency department
  • medical students
  • machine learning
  • artificial intelligence
  • social media
  • big data
  • infectious diseases