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Research-based assessment instruments (RBAIs) are ubiquitous throughout both physics instruction and physics education research. The vast majority of analyses involving student responses to RBAI questions have focused on whether or not a student selects correct answers and using correctness to measure growth. This approach often undervalues the rich information that may be obtained by examining students particular choices of incorrect answers. In the present study, we aim to reveal some of this valuable information by quantitatively determining the relative correctness of various incorrect responses. To accomplish this, we propose an assumption that allow us to define relative correctness: students who have a high understanding of Newtonian physics are likely to answer more questions correctly and also more likely to choose better incorrect responses, than students who have a low understanding. Analyses using item response theory align with this assumption, and Bocks nominal response model allows us to uniquely rank each incorrect response. We present results from over 7,000 students responses to the Force and Motion Conceptual Evaluation.
Conceptual tests are widely used by physics instructors to assess students conceptual understanding and compare teaching methods. It is common to look at students changes in their answers between a pre-test and a post-test to quantify a transition in
Multiple-choice/multiple-response (MCMR) items (i.e., multiple-choice questions for which there may be more than one correct response) can be a valuable tool for assessment. Like traditional multiple-choice/single-response questions, they are easy to
Motivated by recent failures of polling to estimate populist party support, we propose and analyse two methods for asking sensitive multiple choice questions where the respondent retains some privacy and therefore might answer more truthfully. The fi
Learning physics is a context dependent process. I consider a broader interdisciplinary problem of where differences in understanding and reasoning arise. I suggest the long run effects a multiple choice based learning system as well as society cultu
We present a novel method for obtaining high-quality, domain-targeted multiple choice questions from crowd workers. Generating these questions can be difficult without trading away originality, relevance or diversity in the answer options. Our method