Abstract
Dorota Styk & Eddy J. Davelaar
School of Psychological Sciences
Birkbeck, University of London
Novel approach in Working Memory Training
Substantial research has been undertaken on the effects of working memory training (WMT) on individuals with learning difficulties, ADHD, and neurological disorders, as well as typically developing children and healthy adults.
The question of the efficacy of WMT has received considerable critical attention as the results of multiple studies are still inconsistent, which may be due to differences in study designs, study samples, training duration, outcome measures, and the training paradigm itself. However, despite a few recommendations, no ‘golden standard’ has yet been proposed to answer the questions about what factors play a critical role in successful transfer to everyday life abilities (far transfer). Until now, no known empirical research has focused on exploring machine learning (ML) models that would create a more optimal working memory training environment to address the role of individual differences in training outcomes. We are developing a web application of gamified working memory tasks using Hidden Markov Models to predict the level of difficulty based on an individual’s performance. We anticipate that this approach will support the identification of which factors are responsible for successful transfer. Moreover, this may also highlight the importance of upgrading current testing methods and creating innovations for behavioural testing.
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