Attribute hierarchy method

The attribute hierarchy method (AHM), is a cognitively based psychometric procedure developed by Jacqueline Leighton, Mark Gierl, and Steve Hunka at the Centre for Research in Applied Measurement and Evaluation (CRAME) at the University of Alberta. The AHM is one form of cognitive diagnostic assessment that aims to integrate cognitive psychology with educational measurement for the purposes of enhancing instruction and student learning. A cognitive diagnostic assessment (CDA), is designed to measure specific knowledge states and cognitive processing skills in a given domain. The results of a CDA yield a profile of scores with detailed information about a student’s cognitive strengths and weaknesses. This cognitive diagnostic feedback has the potential to guide instructors, parents and students in their teaching and learning processes.

To generate a diagnostic skill profile, examinees’ test item responses are classified into a set of structured attribute patterns that are derived from components of a cognitive model of task performance. The cognitive model contains attributes, which are defined as a description of the procedural or declarative knowledge needed by an examinee to answer a given test item correctly. The inter-relationships among the attributes are represented using a hierarchical structure so the ordering of the cognitive skills is specified. This model provides a framework for designing diagnostic items based on attributes, which links examinees' test performance to specific inferences about examinees' knowledge and skills.

The AHM differs from Tatsuoka's Rule Space Method (RSM) with the assumption of dependencies among the attributes within the cognitive model. In other words, the AHM was derived from RSM by assuming that some or all skills may be represented in hierarchical order. Modeling cognitive attributes using the AHM necessitates the specification of a hierarchy outlining the dependencies among the attributes. As such, the attribute hierarchy serves as a cognitive model of task performance designed to represent the inter-related cognitive processes required by examinees to solve test items. This assumption better reflects the characteristics of human cognition because cognitive processes usually do not work in isolation but function within a network of interrelated competencies and skills. In contrast, the RSM makes no assumptions regarding the dependencies among the attributes. This difference has led to the development of both IRT and non-IRT based psychometric procedures for analyzing test item responses using the AHM. The AHM also differs from the RSM with respect to the identification of the cognitive attributes and the logic underlying the diagnostic inferences made from the statistical analysis.

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