E. Deploy short-format training to counter inequity


Develop a well-funded SFT strategy to counter systemic inequities faced by historically excluded researchers and STEM educators.

This recommendation shifts SFT from a passively available resource to an actively deployed tool for supporting scientists and STEM educators to achieve their research, teaching, and career goals. Targeted SFTs have the potential to be transformative in giving researchers and educators an opportunity to reskill, upskill, and redefine themselves to meet their scientific and career goals. Attention has been paid to improving undergraduate curriculum and graduate training to support students that have been historically excluded from the sciences. This effort should be extended to career-spanning SFT.

The disparities and obstacles these historically-excluded scientists and educators face do not end after achieving high levels of professional accreditation (e.g., PhD degree). For example, in the United States, graduates receiving PhDs from minority-serving institutions (which are generally under-resourced) are less likely to have academic positions than those who received their PhD from a majority-serving institution 1. SFT can be used to empower researchers whose formal training did not include skills that have become critical to current research and teaching aims.

All scientists and educators could benefit when SFT is deployed as part of a long-term disciplinary strategy (i.e., STEM disciplines support continued professional development as a norm, such as in medicine), rather than only for the support of β€œjust-in-time” skills (i.e., workshops are developed for one-off specific needs without long-term planning for career-spanning needs).

How might this work:🚲

Professional societies, funders, and other interested stakeholders would have to assess the needs that must be met within a community. This includes assessment of instructional needs (e.g., which skills are most unmet for a stakeholder group), technical/infrastructural requirements to complete the training, and equity deficiencies (e.g., which stakeholders are currently excluded from full participation and why) for the community of learners. An example was a 2019 assessment in the field of bioinformatics and data science 2. Based on the assessed needs, SFT opportunities would need to be deployed to specifically address the needs of learners. Evaluation would have to assess if the deployment is adequate in meeting learner needs and promoting equity.

Benefits to the learners:🚲

  1. Learners whose formal training lacked critical skills because of systemic or other inequities can be enabled to participate at the same professional level as learners who were prepared at more well-resourced institutions.
  2. An equitable SFT strategy could address the needs of learners with a high level of professional skill who need additional training to reach new career milestones (e.g., promotion, retaining for a career transition, pursuit of a new research funding opportunity).

Incentives to implementers:🚲

For Instructors and Instructional Designers

  1. Increased equity benefits the discipline and is rewarding.
  2. Instructional designers/support can meet goals to broaden participation in their training programs.

For All Implementers

  1. More scientists could perform more high-impact science 3.
  2. Deploying SFT without an intention of countering inequity may exacerbate existing issues of access and resource availability.

Barriers to implementation:🚲

  1. Funders and organizations may need to see the value of deploying SFT to counter inequity and evidence that SFT can be effective in achieving this.
  2. Understanding and meeting learning needs, as well as assessing if they are met, will take significant effort. This needs to be done with the direction and guidance of those who have been historically excluded, not built for them without their input.

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  1. Martinez, L. R., Boucaud, D. W., Casadevall, A., & August, A. (2018). Factors contributing to the success of NIH-designated underrepresented minorities in academic and nonacademic research positions. CBE Life Sciences Education, 17(2). https://doi.org/10.1187/cbe.16-09-0287

  2. Teresa K Attwood, Sarah Blackford, Michelle D Brazas, Angela Davies, Maria Victoria Schneider, A global perspective on evolving bioinformatics and data science training needs, Briefings in Bioinformatics, Volume 20, Issue 2, March 2019, Pages 398–404, https://doi.org/10.1093/bib/bbx100

  3. Szostkowski, A., Upadhyay, B. Looking forward by looking back: equity in science education as socially just and morally healing action. Cult Stud of Sci Educ 14, 335–353 (2019). https://doi.org/10.1007/s11422-019-09916-z