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Abstract Title: Can some wrong answers be more right than others?
Abstract: The Force Concept Inventory (FCI) has been efficiently used to assess conceptual learning in mechanics. Each FCI question has one Newtonian answer and four wrong answers (distracters). Researchers and practitioners most frequently use measures of total score to assess learning. Yet, are all wrong answers equivalent? We conducted Latent Markov Chain Modeling (LMCM) analyses of all choices (right and wrong) on a subset of four FCI questions. LMCM assesses whether there are groups of students sharing similar patterns of responses. We infer that students sharing similar patterns also share similar reasoning. Our results show seven reasoning-groups. LMCM also computes probabilities of transition from one reasoning-group to another following instruction. When examining transitions between groups, we note a clear hierarchy. Groups at the top of the hierarchy are comprised of students that use Newtonian thinking more consistently. Furthermore, proficient students choose some wrong answers more frequently.
Abstract Type: Contributed Poster

Contributed Poster

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Author/Organizer Information

Primary Contact: Helena Dedic
Vanier College
Co-Author(s)
and Co-Presenter(s)
Steven Rosenfield, Vanier College
Nathaniel Lasry, John Abbott College