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  • Join Policy Restricted
  • Created 07 Nov 2022

Frequently Asked Questions

1. What are faculty mentoring networks?

Faculty Mentoring Networks (FMNs) are a method for building supportive communities of faculty interested in addressing similar challenges around teaching quantitative biology. FMNs usually consist of anywhere from ten to twenty faculty participants working with content and pedagogical mentors from the community. The groups share a private space on the QUBESHub where they can have discussions, share resources, and manage group projects. The larger group is subdivided into smaller groups to facilitate discussions. Faculty work together to brainstorm, plan, troubleshoot and generally support one another in their efforts to implement new materials or approaches in the classroom. Mentors facilitate the discussion and provide some guidance and resources.

As faculty grapple with the many details and new challenges of implementing fundamental changes in their classrooms, ongoing community interaction is vital. The virtual nature of FMNs makes this long-term interaction possible by reducing both time and financial barriers to participation.


2. Is this opportunity only available to full-time faculty or can a long-term adjunct faculty member apply?

This opportunity is only available to full-time faculty.


3. Do I have to work at a Primarily Undergraduate Institution?

Yes, you need to work at a Primarily Undergraduate Institution (PUI), as defined by the National Science Foundation:

(PUIs) are defined by the nature of the institution and not solely on the basis of highest degree offered. Eligible PUIs are accredited colleges and universities (including two-year community colleges) that award Associate's degrees, Bachelor's degrees, and/or Master's degrees in NSF-supported fields, but have awarded 20 or fewer Ph.D./D.Sci. degrees in all NSF-supported fields during the combined previous two academic years. (Source)


4. Do I need to be proficient with R to participate?

Some exposure to R, the tidyverse, and associated packages is helpful. More importantly, a willingness to learn these (with provided materials) is even better.