Teaching Hour

Discussion: 2:30 - 3:00 PM

2:30 - 3:00 What We've Learned From Pandemic Teaching

A discussion on the general topic of what we've learned through our various teaching experiences since March 2020. What will you take with you from this past year in your post-pandemic teaching? What won’t you take? Have you become a better teacher? Or can you not wait to ever think about teaching this year again? Let’s reflect together as we move into the summer months.

Moderated by Sarah Wright, Fitchburg State University and Amy Wehe, Fitchburg State University

Teaching Hour Presentations: 4:00-5:15

4:00 - 4:15 Project Based Teaching and Learning of Simple Linear Regression

Hema Gopalakrishnan, Sacred Heart University

In statistics, simple linear regression analysis is used to study relationships between two quantitative variables. In this talk, I will share my experience with implementing a linear regression project in an elementary statistics class in a virtual setting. The project involved collecting bivariate data from the class and analyzing the data for linear correlation between the variables using either R or MS Excel.

4:20 - 4:35 Lessons Learned from teaching Introduction to Data Science

Ann Moskol, Providence College

I will describe how I used the Applied Data Science Materials [developed through an NSF grant and available from Wesleyan University (Middletown Connecticut) ] to teach a data science course at Providence College. The approach requires students to first find an interesting question that can be analyzed using statistical methods and software that they later learn. Several students, for example, used CT motor vehicle data to determine if people of color were arrested more then Caucasian. The Wesleyan website provides resources such a free textbook, videos linked to the textbook, as well as links to available to data bases, The approach provides students the opportunity to work with real data. The materials allow for different statistical software to be used. In my course, I taught the students how to use R to analyze big Data. I will describe the challenges that occurred because the course was online and share what I learned about teaching data science with the Wesleyan materials.

4:40 - 4:55 Translating High School AP Calculus Skills into an Undergraduate Environment

Thomas Y. Chen , Academy for Mathematics, Science, and Engineering

For most high school students, the pinnacle of their mathematics curriculum is AP Calculus. Translating the skills learned in these courses (AB or BC) to undergraduate classes is crucial to a successful education. Criticisms of the AP curriculum include that it simply involves "teaching for the test."

5:00 - 5:15 Less Notetaking in Proof Writing Courses

Jason Molitierno, Sacred Heart University

With the pandemic this year and with half of the students being online at a given time, I decided to type out all of my lecture notes for Graph Theory. It turned out to be a blessing because (1) I covered more material, (2) there was time in class for students to do hands-on work, and (3) it saved on student note taking. This worked so well that I plan to do this with future proof writing courses that I teach.