A hybrid model based on learning automata and cuckoo search for optimizing test item selection in computerized adaptive testing

A hybrid model based on learning automata and cuckoo search for optimizing test item selection in computerized adaptive testing

Abstract Computerized adaptive testing (CAT) has become one of the most effective methods of providing a customized approach to assessment. Nevertheless, the identification of student ability and the choice of appropriate test items is still a problem. In this paper, a new design of CAT strategy is...

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Bibliographic Details
Main Authors: Chanjuan Jin, Weiming Pan
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Computerized adaptive testing
Learning automata
Machine learning
Artificial neural network
Test
Online Access:https://doi.org/10.1038/s41598-025-01115-x
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https://doi.org/10.1038/s41598-025-01115-x

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