The current available receptive vocabulary test for the Hong Kong Cantonese-speaking population was published 26 years ago. Considering language change over time and the rapid socio-economic development, the validity of the test is questionable, thus the need of new vocabulary test is pressing. Traditional vocabulary tests require an average of 30 minutes of completion time. The relatively long administration time is associated with the nature of the linear test design implemented in the paper-and-pen format. Each examinee is presented with the same set of items in the same predetermined order.  Every child is obliged to respond to all questions despite some items are too easy while the others are way too difficult for their ability.  These test items increase the test load and reduce their motivation.  The manual scoring method requires post-test score interpretation also unavoidably reduce test efficiency, not to mention about the higher risk of human errors.

This project proposes to promote a new vocabulary test using the Computerized Adaptive Test approach. CAT consists of three stages – item bank development, setting up algorithm and publish on a CAT platform. Item bank development is the most important part that requires vigorous psychometric analyses. A large item pool consisting of 216 items has been validated on 1245 children aged 2;06 to 6;05 in a 5-year research project. With this large item bank as the foundation, this project will proceed with the second and third stages of test production. ReV-CAT will reduce the testing length and measurement errors for each subject, improving test efficiency and expanding the qualifications of testers to more relevant individuals.

Currently, Hong Kong lacks computerized adaptive tests in speech therapy. This pioneering project aims to develop and launch the first computerized adaptive vocabulary test for the industry, benefiting community end users. CAT enables economical and rapid identification of children with vocabulary difficulties. Placing children indicated for further full language assessment and proper education remediation is made possible.

• Speech-language pathologists and SLP students


• Professionals other than SLPs, e.g. psychologists, childcare workers, paediatrians

2023

Education, Healthcare, Speech therapy, Well-being