20 Oct
2021
20 Oct
'21
1:05 p.m.
The next webinar in the CAUSE (the Consortium for the Advancement of Undergraduate
Statistics Education) / Journal of Statistics and Data Science Education webinar series
will be taking place on Tuesday, November 16, 2021 at 5:00pm ET (note the later time).
The webinar is free but registration is required.
Do data competitions improve learning: A study on student performance, engagement, and
experience with Kaggle InClass data challenges.
In the November CAUSE/Journal of Statistics and Data Science Education webinar series, we
have invited the authors of this recently published paper to share their experiences in
running data competitions as part of classes on statistical learning. Kaggle is a data
modeling competition service, where participants compete to build a model with lower
predictive error than other participants. Several years ago Kaggle released a simplified
service that is ideal for instructors to run competitions in a classroom setting. This
webinar describes the results of an experiment to determine if participating in a
predictive modeling competition enhances learning. The evidence suggests it does. In
addition, students were surveyed to examine if the competition improved engagement and
interest in the class. The authors will also discuss the main issues to consider when
setting up a data competition in a class, including the technical aspects of using the
Kaggle InClass platform.
Julia Polak is a lecturer in Statistics at the University of Melbourne. She has a broad
range of research interests including nonparametric methods, forecasting and data
visualisation. In addition, Julia has many years of experience in teaching statistics and
data science for different audience.
Di Cook is a Professor in Econometrics and Business Statistics at Monash University in
Melbourne. Her research is in the area of data visualisation, especially the visualisation
of high-dimensional data using tours with low-dimensional projections, and projection
pursuit. A current focus is on bridging the gap between exploratory graphics and
statistical inference.
Sign up for the webinar at:
https://www.causeweb.org/cause/webinar/jsdse/2021-11<https://nam10.safel…