A sequential cognitive diagnosis model for polytomous responses.
This paper proposes a general polytomous cognitive diagnosis model for a special type of graded responses, where item categories are attained in a sequential manner, and associated with some attributes explicitly. To relate categories to attributes, a category-level Q-matrix is used. When the attribute and category association is specified a priori, the proposed model has the flexibility to allow different cognitive processes (e.g., conjunctive, disjunctive) to be modelled at different categories within a single item. This model can be extended for items where categories cannot be explicitly linked to attributes, and for items with unordered categories. The feasibility of the proposed model is examined using simulated data. The proposed model is illustrated using the data from the Trends in International Mathematics and Science Study 2007 assessment.
Rutgers, The State University of New Jersey, New Brunswick, New Jersey, USA. wenchao.ma@rutgers.edu.
Wenchao
http://orcid.org/0000-0002-6763-0707
W
Ma
Rutgers, The State University of New Jersey, New Brunswick, New Jersey, USA.
Jimmy
J
de la Torre
D000465:Algorithms; D003072:Cognition Disorders / Q000175:diagnosis*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004521:Educational Measurement / Q000379:methods*; D006801:Humans; D015233:Models, Statistical; D011594:Psychometrics / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D011795:Surveys and Questionnaires
Q-matrix; cognitive diagnosis; generalized DINA; polytomous response; processing function; sequential G-DINA model; sequential process model