If you were taking an introductory statistics course, what would you expect from that course? What would make a great course? We in Resource Economics think that you should expect to learn about the different statistical methods commonly used for decision-making in the private and public sectors and be able to interpret statistics found in the press, online or in print. But we also think you really should expect to apply those methods to real data and see how those data lead you to draw conclusions about the world around you. To really learn statistics, you need to apply the methods to real data regularly – practice makes perfect!
Resource Economics has taught large introductory statistics courses (ResEcon 212) for many years, and we’ve always tried to be innovative in our teaching. More than 20 years ago, Richard Rogers and Glenn Caffery pioneered the first wireless hand-held clickers on campus. We invested in clickers numbered 1-500; they were fresh off the production line. Clickers allowed us to engage all our students in those large lectures (300-450 students). Clickers evolved over time to accept numeric responses and we were ecstatic! (And look at those happy faces!) Now we could provide data to students and have them apply methods in class – “Stats Live!” “Stats Live!” became so much fun that we adopted “Stats is fun!” as one of our mottos. (Yeah – we know we’re pretty geeky.)
Those earlier applications of Stats Live were really simple. Real Stats means real data and nobody wants to try and work with large data sets using a hand-held calculator. We needed to engage students with computers and real data. Glenn Caffery, a leading proponent of Team-Based Learning (TBL), and Department Chair Dan Lass proposed a complete redesign of our traditional large lecture Stats courses to take advantage of UMass’ investment in TBL at the new Integrated Learning Center. We received support from the Provost’s office and Dr. Wayne-Roy Gayle joined the Department to lead a dedicated team of grad students (Zach Berman, Tyler Besse, Sam Dauphinais, Eric Koegler, Kelly Miller, Jayash Paudel and Mark Van Orden) to launch our blended online/TBL Stats course fall 2014..
In our new blended format, students develop foundational skills and conceptual understanding before class, and spend the class periods working in teams to solidify and deepen this understanding. In the past, students in this four credit course spent 200 minutes per week in class; this is reduced now to 75 minutes. In the new Integrated Learning Center TBL classrooms, students gather around tables to work with computers to apply statistics to real data using laptop computers! The team-based learning classrooms contain 11 round tables, each seating 9 students. They are equipped with various technologies for students to collaborate in small groups or across the classroom. Outside of class, graduate teaching assistants and undergraduate peer assistants support student learning and complement instructional technologies and media. We have added weekly organized review sessions with graduate students and use computer classroom space to create more than 20 hours of supported work environment each week. Our goal is to improve upon the learning outcomes attainable in our traditional lecture model.
Students gain valuable experience applying statistical techniques. As part of their course requirements, students work in teams to complete a term project applying what they’ve learned to real data. Students might choose a topic related to business and economics. For example, a team interested in economics considered minimum wage legislation across states. Another team considered how minimum wage increases affected the number of full-time and part-time restaurant workers. Projects cover a wide range of topics including sports such as the important factors in determining NCAA Tournament Basketball seeds. Student complete the course and leave with an understanding of statistical concepts, the ability to apply those concepts using computer software, and the experience of working effectively on a team to complete a project. Students leave with a set of valuable tools. We think this is the way Stats should be taught!