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Title: Exploring Common Trends in Online Educational Experiments
As online learning platforms become more ubiquitous throughout various curricula, there is a growing need to evaluate the effectiveness of these platforms and the different methods used to structure online education and tutoring. Towards this endeavor, some platforms have performed randomized controlled experiments to compare different user experiences, curriculum structures, and tutoring strategies in order to ensure the effectiveness of their platform and personalize the education of the students using it. These experiments are typically analyzed on an individual basis in order to reveal insights on a specific aspect of students' online educational experience. In this work, the data from 50,752 instances of 30,408 students participating in 50 different experiments conducted at scale within the online learning platform ASSISTments were aggregated and analyzed for consistent trends across experiments. By combining common experimental conditions and normalizing the dependent measures between experiments, this work has identified multiple statistically significant insights on the impact of various skill mastery requirements, strategies for personalization, and methods for tutoring in an online setting. This work can help direct further experimentation and inform the design and improvement of new and existing online learning platforms. The anonymized data compiled for this work are hosted by the Open Science Foundation and can be found at https://osf.io/59shv/.  more » « less
Award ID(s):
1931419
NSF-PAR ID:
10354096
Author(s) / Creator(s):
; ; ; ; ;
Editor(s):
Mitrovic, Antonija; Bosch, Nigel
Date Published:
Journal Name:
Proceedings of the 15th International Conference on Educational Data Mining
Page Range / eLocation ID:
27-38
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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