  We overview recent research in Child-Computer Interaction and describe our
framework ChildCI intended for: i) generating a better understanding of the
cognitive and neuromotor development of children while interacting with mobile
devices, and ii) enabling new applications in e-learning and e-health, among
others. Our framework includes a new mobile application, specific data
acquisition protocols, and a first release of the ChildCI dataset (ChildCIdb
v1), which is planned to be extended yearly to enable longitudinal studies. In
our framework children interact with a tablet device, using both a pen stylus
and the finger, performing different tasks that require different levels of
neuromotor and cognitive skills. ChildCIdb comprises more than 400 children
from 18 months to 8 years old, considering therefore the first three
development stages of the Piaget's theory. In addition, and as a demonstration
of the potential of the ChildCI framework, we include experimental results for
one of the many applications enabled by ChildCIdb: children age detection based
on device interaction. Different machine learning approaches are evaluated,
proposing a new set of 34 global features to automatically detect age groups,
achieving accuracy results over 90% and interesting findings in terms of the
type of features more useful for this task.
