Chapter 12: Self-Regulated Learning Theory to Build Scientific Mindsets For Diversity in Stem

Views about science, technology, engineering, and mathematics (STEM) indicate that there is a general consensus about the importance of science to society and that the development of STEM initiatives should be a national priority (Rainie & Funk, 2015). Indeed, by the numbers only, the K–16 education efforts aimed at the development of a strong STEM work-force have been successful. Since the early 1990s, the STEM workforce has increased by almost 80% (Fayer et al., 2017).

Notwithstanding the nationwide consensus on the importance of STEM and the availability of STEM learning opportunities, those who choose a STEM career are still fewer with respect to the projected needed numbers and their percentages do not reflect the actual diversity of the population (Funk & Parker, 2018). For example, most women employed in STEM are in the health care system, whereas women are underrepresented in computer sciences, by far the fastest-growing STEM field. African Americans (11% of U.S. workforce) constitute only 9% of the STEM workforce, and only 7% of STEM workers are Hispanic (16% of U.S. workforce). The percentages regarding women and Black, Indigenous, and people of color (BIPOC) drop further when considering STEM careers for those with BS or higher degrees (Funk & Parker, 2018). These numbers indicate that STEM careers are not equally accessed by representatives of the population diversity, an unbalance that might reside in the way in which science as a discipline is perceived by the public.