PERC 2011 Abstract Detail Page
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| Abstract Title: | Quantitative Modeling of Changes in Student Understanding |
|---|---|
| Abstract: | We employ four distinct statistical methods to model day-to-day changes in student responses to simple conceptual questions. These questions were administered several times per week to separate, randomly selected groups of introductory physics students. The four methods applied to parameter estimation were least-squares estimation, maximum-likelihood estimation, autoregressive integrated moving average series modeling (ARIMA), and Bayesian estimation. Each method is able to estimate the impacts of specific learning interventions such as lectures, homework assignments, and exams. We present brief introductions to each of these four methods, as well as a comparison of their results to demonstrate the advantages and disadvantages for each. |
| Abstract Type: | Contributed Poster |
Author/Organizer Information | |
| Primary Contact: |
Aaron R. Warren Purdue University - North Central Department of Mathematics, Physics, and Statistics 1401 S. US-421 Westville, IN 46391 Phone: 219-785-5659 |
| Co-Author(s) and Co-Presenter(s) |
Thomas M. Scaife Department of Chemistry and Engineering Physics University of Wisconsin - Platteville Andrew F. Heckler Department of Physics The Ohio State University |
