A concept inventory (CI) is a multiple-choice instrument designed to evaluate whether a person has an accurate, working knowledge of a specific set of concepts. An important role of CI's is to provide instructors with clues about the pre-conceptions their students hold which may be actively interfering with learning. Only a few engineering CI's have been able to be applied successfully in instructional settings, due in part to statistical analysis techniques that are typically applied to the instrument, which measure the item performance data of the CI's. However, these strategies do not measure students' cognitive abilities. To begin filling this gap, a study was conducted to determine the applicability of a new statistical method called the Fusion Model to the Concept Assessment Tool for Statics (CATS) among engineering students from various universities. A four-phase procedure was developed to apply the Fusion Model to CATS. Each phase had a specific objective that was tied to a primary research question. This paper focuses on phase 1 - the generation of a Q-matrix that relates a set of cognitive attributes to specific CATS questions. The process used in this phase of the study consisted of analyzing the items in CATS and determining the cognitive attributes required for students to choose the correct answer. These attributes were identified based on Minstrell's framework - facets of understanding. Results from this study led to the development of a Q-matrix in which 13 attributes were identified among the 27 items. Six of those attributes were identified and expected to be more problematic. Identification of these attributes provide an additional diagnostic information to instructors because instructors will know not only which concepts the students find more difficult, but also what specific attributes contribute to making the concept difficult. With this added information, instruction can be targeted to those specific attributes or concepts.
展开▼
