User:Statisfactions/New Directions

New directions
Teachers of statistics have been encouraged to explore new directions in curriculum content, pedagogy and assessment. In an influential talk at USCOTS, researcher George Cobb presented a new approach to teaching statistics that put simulation,  randomization, and  bootstrapping techniques at the core of the college-level introductory course, in place of traditional content such as probability theory and the t-test. Several teachers and curriculum developers have been exploring ways to introduce simulation, randomization, and bootstrapping as teaching tools for the secondary and postsecondary levels. New courses such as the University of Minnesota's CATALST, Nathan Tintle and collaborators' Introduction to Statistical Investigations, and the Lock team's Unlocking the Power of Data, are curriculum projects based on Cobb's ideas. Other researchers have been exploring the development of informal inferential reasoning as a way to use these new methods to build a better understanding of statistical inference.

Another new direction is addressing the big data sets that are increasingly affecting or being contributed to in our daily lives. Statistician Rob Gould outlines many of these types of data and encourages teachers to find ways to use the data and address issues around big data. According to Gould, new curriculum focused on big data will address issues of data visualization, data cleaning, the underlying processes that generate data, sampling, and prediction, rather than traditionally emphasized methods of making statistical inferences such as hypothesis testing.

Driving both of these changes is the increased role of computing in teaching and learning statistics. Some researchers argue that as the use of modeling and simulation increase, and as data sets become larger and more complex, students will need better and more technical computing skills. New projects such as MOSAIC have been creating courses that blend computer science, modeling, and statistics.