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Abstract Details

Activity Number: 344
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 ; computing ; teaching ; tools

Online courses are becoming more and more popular and allow - through monitoring of student behavior - an enhanced and personalized learning experience. In the university context, e-learning modules can be used to provide hands-on laboratory activities. While common in the physical and natural sciences, these are still rare in statistics education. We have created an interactive statistics learning environment to augment and extend statistics courses with interactive learning modules. We report on the results of using this system to teach the statistical programming language R. Since all user interactions (mouse clicks, text inputs etc.) are collected along with their time stamps, we can scrutinize user behavior in detail and track student performance. Our results show that student engagement varies widely across various social contexts (e.g., taking exercises in-class or at home), but besides that is heavily influenced by the software interface and the used educational design. Since user engagement is positively correlated with student performance, we close by summarizing our findings on how to maximize student's motivation.

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

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