Resources for Collections-Based  Undergraduate Education

Category: Faculty Mentoring Network

Are you interested in incorporating more real data into your undergraduate courses? Natural History Collections have been digitizing their holdings and making them available online, creating a vast resource for biodiversity data that educators can access! Apply now to join the 2017...

HHMI BioInteractive Faculty Mentoring Network

Category: Faculty Mentoring Network

HHMI BioInteractive and QUBES are pleased to offer a unique networking and professional development opportunity from June 2017-January 2018 for faculty interested in improving student quantitative skills in biology. Faculty participants focus on providing students with a more comprehensive...

Explore Authentic Data with Data Nuggets: An LDC-QUBES Faculty Mentoring Network

Category: Faculty Mentoring Network

The Life Discovery - Doing Science Biology Education Conference (LDC), Data Nuggets, and Quantitative Undergraduate Biology Education and Synthesis project (QUBES) are pleased to offer a unique networking and professional development opportunity from September – November 2017 for faculty...

Math Modeling Faculty Mentoring Network

Category: Faculty Mentoring Network

The Math Modeling Hub (MMHub) aims to develop and grow math modeling in grades K - 16 by connecting educators with mathematical modeling through mentoring, resources, and community. The inaugural Math Modeling Faculty Mentoring Network (MMFMN) will bring together experienced teachers of math...

Beanbag Biology: Teaching Quantitative Biology through Hands-on Activities

Category: Faculty Mentoring Network

This group will share and implement hands-on (i.e. manipulative) activities that teach quantitative biology (e.g., disease modeling) using active-learning exercises. The activities can be adapted to any level from high school through graduate courses. Our approach lends guidance and support as...

The Discrete FMN

Category: Faculty Mentoring Network

Many scenarios in the life sciences can be modeled with discrete difference equation models which simulate how quantities change over evenly spaced intervals. The construction and analysis of models of discrete difference equations do not require knowledge of calculus, and thus make excellent...