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PERC 2014 Abstract Detail Page

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Abstract Title: A/B Experiments, Machine Learning, and Psychometrics in MOOCs can Accelerate your PER
Abstract: Massive Open Online Courses (MOOCs) present education researchers with a unique opportunity to do PER, develop educational resources, and compare pedagogies. The MOOC environment has several advantages: the opportunity to apply psychometric and machine learning analyses such as IRT, Hidden Markov Models, student habit clustering, etc. with a large sample size? the ability to do perform controlled experiments involving different instructional resources and pedagogies with minimum student pushback? access to detailed records of what resources students study and when, and a wide variation in demographics (e.g. 25% with a high school education or less and 25% who are physics teachers in the same MOOC). We will discuss the A/B experiments and instrument development we are performing in our summer MOOC: 8.MReVx Mechanics Review, on the edX platform, invite discussion, and hopefully recruit some future collaborators who can leverage our data analysis for doing their PER in our next MOOC at the AP-level.
Abstract Type: Symposium Poster
Targeted Session: Getting Involved in Online PER

Author/Organizer Information

Primary Contact: Zhongzhou Chen
Massachusetts Institute of Technology
and Co-Presenter(s)
Neset Demerici, David Pritchard