Online Program Home
  My Program

Abstract Details

Activity Number: 344 - Technology in the Classroom
Type: Contributed
Date/Time: Tuesday, August 1, 2017 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Education
Abstract #324564 View Presentation
Title: Improving Statistics Education Through Interactive Learning Tools
Author(s): Philipp Burckhardt* and Alexandra Chouldechova
Companies: Carnegie Mellon University and Carnegie Mellon University
Keywords: education ; e-learning ; machine learning ; teaching ; statistics ; trajectories

We introduce an e-learning platform called ISLE (Interactive Statistics Learning Environment) that provides a framework for building interactive online lessons for statistics that can be used in a blended-learning setting. The platform comes with an accompanying analytics dashboard that enables instructors to easily track the learning trajectories of their students. In this paper, we reflect on an analysis of student engagement with interactive lab sessions that were administered over three sections of a half-semester course on R programming and data analytics. Having collected almost 25, 000 user interactions, we analyze the completion rates of the labs via group-based trajectory modeling. We identify distinct student groups who follow a similar path over time, and investigate the correspondence between learning trajectories and learning outcomes. Taking a closer look at click rates within the R exercises, we find that not all students approach the problems of a lab session in a linear manner. We discuss the implications of these preliminary results and close by laying out future directions for the ISLE platform.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2017 program

Copyright © American Statistical Association