PERC 2016 Abstract Detail Page
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| Abstract Title: | Analysis of student performance on the Mechanics Reasoning Inventory |
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| Abstract: | Our Mechanics Reasoning Inventory (MRI) is a 21-item instrument specifically designed to assess reasoning skills involving these core topics: Newton's Laws, momentum, mechanical energy, and circular motion. The instrument consists of three classes of problems: whether momentum or energy is conserved in a given situation and why is it conserved, (inspired by Lawson's Classroom Test of Scientific Reasoning), application of Newton's 2nd and 3rd law, and decomposing problems into parts (inspired by Van Domelen's Problem Decomposition Diagnostic). It has been administered in two MIT courses since 2009. Exploratory factor analysis (EFA) identified four factors among the 21 problems which correspond one-to-one with the four physics topics, but not with the question types. Latent class analysis (LCA) based on those four factors identified three latent classes among students students: high, medium and low ability students. These results suggest that topical knowledge is a better predictor of student performance than skill on question type, and points to future directions for improving the instrument. |
| Abstract Type: | Contributed Poster Presentation |
Author/Organizer Information | |
| Primary Contact: |
Zhongzhou Chen Massachusetts Institute of Technology 77 Massachusetts Institute of Technology 26-321 Cambridge, MA 02139 Phone: 217-721-8411 |
| Co-Author(s) and Co-Presenter(s) |
Sunbok Lee, Alex Kimn, Andrew Paul, David Pritchard |
