Statistical classification for cognitive diagnostic assessment: an artificial neural network approach
- 2 July 2015
- journal article
- research article
- Published by Taylor & Francis Ltd in Educational Psychology
- Vol. 36 (6), 1065-1082
- https://doi.org/10.1080/01443410.2015.1062078
Abstract
The purpose of the current investigation was to describe how the artificial neural networks (ANNs) can be used to interpret student performance on cognitive diagnostic assessments (CDAs) and evaluate the performances of ANNs using simulation results. CDAs are designed to measure student performance on problem-solving tasks and provide useful diagnostic information about cognitive skill acquisition. But for CDA to realise its potential as a formative testing method, substantial progress must be made in the development of cognitive models that characterise students’ knowledge structures and processes skills, the construction of high-quality test items that precisely measure the nature of the knowledge and skills as specified in the cognitive models, as well as the advancement of psychometric techniques that allow us to accurately interpret student performance. The current investigation focuses on the third component as we examine the use of ANNs as a powerful nonparametric statistical method for diagnostic classification.Keywords
Funding Information
- SSHRC Insight Development grant (430-2011-0101)
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