Teaching Quantitative Biology Online

An editable Google Doc with community resources for teaching online.

List of sections:

• Teaching writing in a time of quick transition

• General shifting-quickly-online resources 

• Affective issues, for faculty and students

• Accessibility  (including surveys you can copy to learn about your students’ tech/materials access)

• General online teaching resources

• Disciplinary resources

• Transitioning Service-Learning Courses

• Resources aimed at students

From the description on Kaggle

"Johns Hopkins University has made an excellent dashboard using the affected cases data. Data is extracted from the google sheets associated and made available here.

Edited:
Now data is available as csv files in the Johns Hopkins Github repository. Please refer to the github repository for the Terms of Use details. Uploading it here for using it in Kaggle kernels and getting insights from the broader DS community."

This is a relatively quick activity. A few lines of code utilizing the EpiDynamics R package gives students access to simulations of SEIR curves and can explore how lowering transmission rate helps flatten the curve. OER activity - fork it to add your own twist!

This is a Washington Post spatially-explicit simulation showing how social distancing helps flatten the curve and reduce overall infections.

General audience

A colleague recommended this. He said it is easy to use, students can use it in a breakout session, and you can save the whiteboard when you are done.

A fantastic tool for exploring public health, data, and data visualization.  The link will take you to teaching materials, but consider using the videos to prompt question exploration in the tools section.

A very good blog by Rebecca Barrett-Fox to help keep this exercise in perspective.

Data, figures and materials to explore.  No educational materials included.

A collection of basic information about teaching online.

The Floe Inclusive Learning Design Handbook is a free Open Educational Resource (OER) designed to assist teachers, content creators, Web developers, and others in creating adaptable and personalizable educational resources that can accommodate a diversity of learning preferences and individual needs. 

At this link is a version of the guidelines with clickable headers and checkpoints. More information is provided for each guideline.

The goal of the Accessibility Toolkit – 2nd Edition is to provide resources for each content creator, instructional designer, educational technologist, librarian, administrator, and teaching assistant to create a truly open textbook—one that is free and accessible for all students.

A three-minute video on how to use Zoom and Google Slides captioning to live captioning a lecture and record it to share.

Article from Aimi Hamraie on the Mapping Access blog on ways to improve accessibility when transferring your typically in-person teaching to an online-environment.  I found this short article to have great ideas about how to incorporate students into the redesign of the course if needed and other ways to help from everyone feeling disconnected when now in an online environment.   

"Each day during the summer of 2019 we intend to add a new entry to this blog on a given topic of interest to educators teaching data science and statistics courses. Each entry is intended to provide a short overview of why it is interesting and how it can be applied to teaching. We anticipate that these introductory pieces can be digested daily in 20 or 30 minute chunks that will leave you in a position to decide whether to explore more or integrate the material into your own classes. By following along for the summer, we hope that you will develop a clearer sense for the fast moving landscape of data science."

This group is back at it with ideas for teaching online.

Avida-ED is an award-winning educational application developed at Michigan State University for undergraduate biology courses to help students learn about evolution and scientific method by allowing them to design and perform experiments to test hypotheses about evolutionary mechanisms using evolving digital organisms.

Check out the blog posts by Jim Smith (posted 3/13/20) and Rob Pennock (posted 4/1/20).