About

The fall 2016 ASM M(icro)OOCs Course is a four-part webinar series, sponsored by ASM and QUBES focuses on increasing quantitative biology in undergraduate education. Each of the four 60-minute sessions will address common issues around teaching quantitative skills and reasoning, ranging from dilutions to graphing to data analysis. The program will run from September to December, 2016 and will be coupled with a virtual learning community. 

Upon viewing the webinars and participating in a virtual faculty learning community, attendees will be able to:

• Identify challenges to teaching quantitative skills in microbiology.
• Examine their own teaching practices to see how quantitative skills are taught and reinforced in the classroom/laboratory.
• Discover innovative methods faculty are incorporating into classroom and laboratories to improve student quantitative skills.
• Develop or adapt methods and models that involve data collection and analysis as a means of practice and improving quantitative skills.
• Develop a community of practice among colleagues where we can share knowledge and help one another develop and deploy innovative methods in teaching quantitative skills to microbiology students.

Registration for this course is for all four sessions. Registration for individual sessions is not available. Participants may register at any point throughout the course and will have access to past session recordings. Please visit our website to register.

Sessions

1- Connecting Math and Quantitative Skills With Concepts Learned in Class – Why Bother? 
September 28, 2016, 3:00 PM EST 
Presenter: Kären Nelson, Ph. D., Prince George's Community College, Hyattsville MD

Overview: 
There has been a lot of research into math education and why it is important. Frameworks for quantitative reasoning tell us that students’ progress from basic skills such as measuring and quantifying, using fundamental mathematical concepts, data interpretation and finally modeling or creating representations for this data. How can we help microbiology students along this pathway? Perhaps, your students are already using quantitative skills without even knowing it. Where do you find the gaps in student knowledge or resistance from students in using math skills? Learn more about getting your students over well-known barriers to learning in these areas. 

Learning Goals:
• Learn more about education research about math and student learning
• Recognize ways they are already incorporating quantitative skills in their curriculum
• Identify and rank the skills they believe are most important

2- Basic Quantitative Skills: Teaching Math in Lab (#TMIL) – the next #TBT. 
October 12, 2016, 3:00 PM EST 
Presenter: Brian M. Forster, PhD., Saint Joseph's University, Philadelphia, PA

Overview: 
When microbiology students come to lab, we expect them to be competent in basic math skills. These skills can include graphing (interpolation and extrapolation), dilutions, converting measurements, and calculating concentrations. Even though these are concepts discussed in high school and introductory biology, we are seeing more and more of our students lacking in this knowledge. How can teachers create throwback Thursday (#tbt) moments in class to get students to master math in the lab without losing the microbiology concepts we want to cover? 

Learning Goals: 
• Develop a list of the lab math skills we expect all students taking microbiology should be competent in.
• Share best practices in teaching and prompting students to remember these skills.
• Develop a repertoire of sharable labs, lessons, videos and/or assessments we can implement in our teaching laboratories.

3- Data Analysis: My Students Collected Data – Now What?
November 16, 2016, 3:00 PM EST 
Presenter: Theodore R. Muth, PhD., CUNY Brooklyn, Brooklyn, NY

Overview: 
In order to draw out sound conclusions, or to determine the next steps forward, students must be able extract quantifiable properties of their data. Aspects of these quantitative properties include magnitude, relative change, variation, and importantly they should be able to present their analyses in an easy to interpret, graphical manner. Students need to be able to use basic tools, such as spreadsheets, for storing, organizing and analyzing data. This is particularly important in microbiological studies where large datasets are collected and manual calculations and graphing are impractical. While many students are extremely computer literate and not at all technophobic, essential data management, analysis and visualization skills using programs, such as Excel, are very weak. 

Learning Goals: 
• Determine the quantitative properties of their data that can be extracted and used to support conclusions or best describe the data.
• Teach their students basic analysis and visualization using Excel and be familiar with tutorial resources for Excel.
• Use web-based resources and tools for analyzing and visualizing large datasets.
• Create their own training resources, such as screencasts, specifically designed for the quantitative data their students will need to analyze.

4- Applying Mathematical Modeling: Student-Driven Microbiome Research 
December 14, 2016, 3:00 PM EST 
Presenter: Mary E. Allen, Ph.D., Hartwick College, Oneonta, NY

Overview: 
Inquiry based activities are an increasingly common component of microbiology teaching laboratories because they engage students in higher order thinking and the process of conducting scientific research. Microbiology activities that effectively model genuine research incorporate hypothesis development, experimental design, and data analysis. Statistical analysis of data can close the loop on a scientific discovery exercise by asking the students to reflect back on the strength of support for their initial hypothesis. 

Learning Goals: 
• Know how to adapt several common microbiology lab exercises to teach hypothesis development and statistical analysis
• Have heard several ways to incorporate sample replication into microbiological exercises
• Have tools for teaching students to carry out basic statistical analysis and interpretation