Ph.D. Dissertation Proposal Defense: Olasumbo O. Oluwalana

Monday, July 16, 2018 10:00am - 12:00pm

GSE 314

Dissertation Proposal Defense

New Approaches to Q-Matrix Validation and Estimation for Cognitive Diagnosis Models

Olasumbo is a doctoral student in the Learning, Cognition, Instruction, and Development concentration of the Doctor of Philosophy program.  

Committee: Dr. Chia-Yi Chiu (chair), Dr. Greg Camilli, Dr. Dake Zhang, Dr. Jiawen Zhou

 

ABSTRACT

A primary purpose of cognitive diagnostic models (CDMs) is to classify examinees based on their attribute patterns. The Q-matrix (Tatsuoka, 1985), a common component of all CDMs, specifies the relationship between the set of required dichotomous attributes and the test items. Since a Q-matrix is often developed by content-knowledge experts and can be influenced by their judgment (de la Torre & Chiu, 2016), this can lead to misspecifications in the Q-matrix that can have unintended consequences on examinees’ classifications. Incorrect classification of examinees can have tremendous impact since some assessments are high-stake and are used to make important decisions about students, such as selection and placement. It is therefore vital to develop new methods of validating and estimating a Q-matrix that can be used with a variety of CDMs. This study proposes one Q-matrix validation method and one Q-matrix estimation method. The proposed methods both integrate the Q-matrix validation procedure (Chiu, 2013) that is based on a nonparametric classification method. The first method, the integrated Q-matrix validation (IQV) method, uses a joint maximum likelihood estimation (JMLE) procedure for DCM (Chiu et al, 2016) to determine examinees’ attribute profiles that are then integrated into the algorithm of Chiu’s Q-matrix validation method to validate the Q-matrix. In the second method, the two-step Q-matrix estimation (TSQE) method, factor analysis is first applied to the correlation matrix to obtain a provisional Q-matrix. The provisional Q-matrix is then incorporated into the algorithm of Chiu’s Q-matrix validation method, to obtain the true Q-matrix. The viability of both methods was investigated using simulation studies with various conditions. As a practical application, both methods are used for a complete analysis of a subset of the TIMMS 2011 fourth-grade mathematics data.

     

Who to contact:

Ericka Diaz

ericka.diaz@gse.rutgers.edu