Collecting experimental cognitive data with young children usually requires undertaking one-on-one assessments, which can be both expensive and time-consuming. In addition, there is increasing acknowledgement of the importance of collecting larger samples for improving statistical power Button et al. (Nature Reviews Neuroscience 14(5), 365-376, 2013), and reproducing exploratory findings Open Science Collaboration (Science, 349(6251), aac4716-aac4716 2015). One way both of these goals can be achieved more easily, even with a small team of researchers, is to utilize group testing. In this paper, we evaluate the results from a novel tablet application developed for the Resilience in Education and Development (RED) Study. The RED-app includes 12 cognitive tasks designed for groups of children aged 7 to 13 to independently complete during a 1-h school lesson. The quality of the data collected was high despite the lack of one-on-one engagement with participants. Most outcomes from the tablet showed moderate or high reliability, estimated using internal consistency metrics. Tablet-measured cognitive abilities also explained more than 50% of variance in teacher-rated academic achievement. Overall, the results suggest that tablet-based, group cognitive assessments of children are an efficient, reliable, and valid method of collecting the large datasets that modern psychology requires. We have open-sourced the scripts and materials used to make the application, so that they can be adapted and used by others.
Bibliographical noteFunding Information:
The Resilience in Education and Development (RED) Study is supported by grant TWCF0159 from the Templeton World Charity Foundation, and by the UK Medical Research Council.
The Resilience in Education and Development (RED) Study is supported by grant TWCF0159 from the Templeton World Charity Foundation, and by the UK Medical Research Council. An earlier version of this article has been shared on OSF Preprints ( https://osf.io/aw6c5/ ), and portions of the findings have been presented as posters at the 2019 British Neuroscience Association (BNA) and 2019 British Association for Cognitive Neuroscience (BACN) conference. We have no conflicts of interest to disclose. Acknowledgements
© 2020, The Author(s).
- Big Data
- Child, Preschool
- Educational Status
- Reproducibility of Results