NIMBioS Interactive Event

NIMBioS Discussions with Students on Quantitative Education in the Life Sciences

Topic: NIMBioS Discussions with Students on Quantitative Education in the Life Sciences

Meeting dates: Two sessions – January 19 at 1 p.m. and January 22 at 1 p.m.

Objective. With support from the Burroughs Wellcome Fund, NIMBioS recently hosted a Workshop on Quantitative Education in Life Science Graduate Programs. One suggestion from this Workshop was to foster a discussion with current and recent students (advanced undergraduate, graduate students and postdocs) involved in the life sciences about their quantitative education experiences. The objective is to gather information and opinions regarding the current means by which students are obtaining quantitative training and comments about the benefits of alternative modes of learning. NIMBioS invites recent and current students to assist in the process of providing input on this by joining in on one or more conversations to be held in January 2021 several times using the Sococo platform in NIMBioS Interactive. The exact dates and times will be chosen in early January based on polls of the participants. These discussions will provide students an opportunity to share suggestions and to learn from the experiences of others about options to enhance their quantitative skills.

Questions for discussion sessions

Describe briefly the quantitative education you received as a undergraduate or graduate student, both formally (courses, workshops, tutorials) and informally (lag groups, peer-learning, mentor learning, on-line learning, etc.)
Describe which of your educational experiences you have found to be most helpful in your career and which have not been helpful.
What quantitative education do you now wish you had more of and how would you suggest having it best delivered to meet your needs?
What suggestions do you have for a report on quantitative education for graduate students?

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From 2008 until early 2021, NIMBioS was supported by the National Science Foundation through NSF Award #DBI-1300426, with additional support from The University of Tennessee, Knoxville. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.