Multi-Dimensional Item Response Theory and the Force Concept Inventory

Abstract

Research on the test structure of the Force Concept Inventory (FCI) has largely been performed with exploratory methods such as factor analysis and cluster analysis. Multi-Dimensional Item Response Theory (MIRT) provides an alternative to traditional Exploratory Factor Analysis which allows statistical testing to identify the optimal number of factors. Application of MIRT to a sample of $N=4,716$ FCI post-tests identified a 9-factor solution as optimal. Additional analysis showed that a substantial part of the identified factor structure resulted from the practice of using problem blocks and from pairs of similar questions. Applying MIRT to a reduced set of FCI items removing blocked items and repeated items produced a 6-factor solution; however, the factors had little relation the general structure of Newtonian mechanics. A theoretical model of the FCI was constructed from expert solutions and fit to the FCI by constraining the MIRT parameter matrix to the theoretical model. Variations on the theoretical model were then explored to identify an optimal model. The optimal model supported the differentiation of Newton's 1st and 2nd law; of one-dimensional and three-dimensional kinematics; and of the principle of the addition of forces from Newton's 2nd law. The model suggested by the authors of the FCI was also fit; the optimal MIRT model was statistically superior.

References in corpus (5)

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Cited by in corpus (7)

• Exploring the Structure of Misconceptions in the Force and Motion Conceptual Evaluation with Modified Module Analysis
• Exploring the Structure of Misconceptions in the Force Concept Inventory with Modified Module Analysis
• Extending Modified Module Analysis to Include Correct Responses: An Analysis of the Force Concept Inventory
• Assessing Confidence in AI-Assisted Grading of Physics Exams through Psychometrics: An Exploratory Study
• Multidimensional Item Response Theory in the Style of Collaborative Filtering
• Chained computerized adaptive testing for the Force Concept Inventory
• Replicating analyses of item response curves using data from the Force and Motion Conceptual Evaluation