BrainHood: Designing a cognitive training system that supports self-regulated learning skills in children

Konstantinos Tsiakas (Corresponding author), Emilia Barakova, Javed Vassilis Khan, Panos Markopoulos

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)


BACKGROUND: There is strong evidence that cognitive skills and executive functions are skills that children need in order to successfully learn in school. Although executive function disorders are not considered a learning disability, weaknesses in executive functioning are often observed in students with learning disabilities or ADHD. Cognitive games are a type of educational games which focus on enhancing cognitive functioning in children with different profiles of cognitive development, including students with neurocognitive and/or learning disabilities. Self-regulation and metacognitive skills also play an important role in academic performance. OBJECTIVE: In this work, we highlight the need of monitoring and supporting metacognitive skills (self-regulation) in the context of a cognitive training game. We propose a system for self-regulated cognitive training for children which supports metacognitive strategies allowing the child to reflect on their own progress, weaknesses and strengths, self-arrange the training content, and thus to promote their self-regulated learning skills. METHODS: We provide a narrative review of research in cognitive training, self-regulated learning and explainable recommendation systems for children in educational settings. RESULTS AND CONCLUSIONS: Based on the review, an experimental testbed is proposed to explore how transparency, explainability and persuasive strategies can be used to promote self-regulated learning skills in children, considering individual differences on learning abilities, preferences, and needs.

Original languageEnglish
Pages (from-to)219-228
Number of pages10
JournalTechnology and Disability
Issue number4
Publication statusPublished - 2020


  • Cognitive training
  • executive functions
  • Explainable AI
  • persuasive technology
  • self-regulated learning


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