The Q-BEx project comprises three phases:
A snapshot of each is presented below.
How should children’s bilingual experience be measured? What common measures of language experience should be used to allow comparability between studies? To what extent can/should researchers and practitioners (teachers, speech and language therapists) use the same measures to profile the children they work with?
To inform our project, we carried out a Delphi Consensus Survey to seek an answer to these (and many other) questions. The Delphi survey method is used across disciplines to reach a consensus on topics where there is little or no full agreement between stakeholders. This survey was completed by 132 participants (including researchers, speech and language therapists, and teachers) from 29 countries. Details about the methodology and the outcomes can be found in De Cat et al (2022).
Our project is also informed by a comprehensive review of existing questionnaires from the research literature. This revealed high variability across questionnaires and low comparability of the measures they yield. For further detail, see Kašćelan et al (2021).
Based on the results of the Delphi Consensus Survey, and informed by best practice from psychometrics, we designed a new, online questionnaire. The questionnaire is modular and customisable to suit the needs of professionals. It can be completed by children (of at least 8 years of age) or their caregiver, and is available for free in a growing number of languages. A back-end calculator derives a number of measures that are straightforward to interpret by professionals. The online interface was created by web developers (Castlegate IT).
To evaluate the fitness-for-purpose of the tool, we interviewed 25 adult and 5 child respondents (from across 14 countries) while they were filling in the questionnaire. This helped us enhance the clarity of the questionnaire.
The validation phase is currently taking place. We are collecting new data from at least 300 children in 3 different countries (including questionnaire data, language proficiency data, and cognitive measures). Based on this assessment, we will provide evidence-based guidance to inform users’ choice on the level of questionnaire detail most appropriate to their needs.
Exploiting cutting-edge statistical techniques, we will also develop an objective method to identify early those bilingual children in need of support with their school language, helping practitioners estimate when a child who speaks a different language at home can be expected to have “caught up” with their monolingual peers.
