Child selection of learning methods: a corpus based on real-world data

• Authors: Heikki Ruuska;Shinya Kiriyama;Yoichi Takebayashi
• Venue: Proceedings of the 2nd Workshop on Child, Computer and Interaction
• Year: 2009

We are running a parent-child learning project for constructing a multimodal child behavioral corpus. It is based on a learning environment where children and their parents regularly attend both guided lessons and have chances for free play. Among other purposes, we use the gathered data for analyzing how children construct evaluation schemas of learning processes. One important kind of learning is learning which learning methods are useful and which harmful in different situations. We have examined how learning methods, which are different from skills, develop from simple to complex physical and social manipulation. Our research shows hints on how negative knowledge on unsuccessful learning methods is used to encourage cognitive constructs more advanced than binary repetition, resulting in developing complex methods such as learning to reason by analogies and use them to construct new complex hypotheses about the world, and using adults and other children as sources of knowledge. We are also researching how right kind of support and example from adults close to children are essential in endowing and encouraging children with using these abilities.