Large-Scale Parallel Cognitive Diagnostic Test Assembly Using A Dual-Stage Differential Evolution-Based Approach
- Authors
- Cao, Xi; Lin, Ying; Liu, Dong; Duh, Henry Been-Lirn; Zhang. Jun
- Issue Date
- Dec-2023
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Automatic assessment tools; cognitive diagnosis model (CDM); Context modeling; differential evolution (DE); Mathematical models; Optimization; psychometric testing; Search problems; Sociology; Testing; Urban areas
- Citation
- IEEE Transactions on Artificial Intelligence, pp 1 - 14
- Pages
- 14
- Indexed
- SCOPUS
- Journal Title
- IEEE Transactions on Artificial Intelligence
- Start Page
- 1
- End Page
- 14
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/118519
- DOI
- 10.1109/TAI.2023.3341916
- ISSN
- 2691-4581
- Abstract
- Parallel testing, which uses different test forms to assess examinees, is a necessary and important technique in both educational and psychometric assessments. A key but challenging problem for successful parallel testing lies in generating a high-quality parallel test set. Most existing parallel test assembly methods were developed for classic test theory and item response theory. In the context of cognitive diagnosis models, which is a new instrument featuring the ability to assess the examinee’s status on fine-grained attributes, the investigation of parallel test assembly is limited, particularly for large parallel scale. This study aims to provide an efficient dual-stage solution for the large-scale parallel cognitive diagnostic test (CDT) assembly problem. In the first stage, the assembly of individual CDTs is treated as a multimodal optimization problem and a niching differential evolution algorithm is developed to find an elite set of CDTs with near-optimal diagnostic performance. By redesigning evolutionary operators, the efficient search mechanism in differential evolution is transferred to the binary context and suits the purpose of optimizing item assignment to a CDT. In the second stage, a graph representation is defined to capture the set of elite CDTs and their overlapping relationships. A deterministic algorithm is applied to the graph to find specific nodal maximum cliques and provide two types of parallel test sets that satisfy different examiner preferences. Simulation studies under a variety of conditions and real-data demonstration show that the proposed method outperforms the existing approaches on large-scale instances while remaining competitive on small-scale cases. IEEE
- Files in This Item
-
Go to Link
- Appears in
Collections - COLLEGE OF ENGINEERING SCIENCES > SCHOOL OF ELECTRICAL ENGINEERING > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/118519)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.