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Training away over-exhaustive errors with distributive quantifiers in children with a single training session

Roest, Christian (2018) Training away over-exhaustive errors with distributive quantifiers in children with a single training session. Bachelor's Thesis, Artificial Intelligence.

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Abstract

Children between the ages of 5 to 9 years often make language errors called ”overex haustive errors”. If we show them an image with 3 boys each playing with a cat, they reject a statement like ”Every boy plays with a cat”, if there is an extra cat in the image which no boy is playing with. There is a clear polarization between the responses that children at this age give; they will either always make the mistake, or never make the mistake. This suggests that a full understanding of distributive quantifiers is not learned gradually, rather that there is a trigger effect after which they learn the correct understanding quickly. We wanted to find out whether exposing children to informative examples, in a single training session, will trigger children to learn the correct understanding of distributive quantifiers. We designed a study to test this using the Dutch quantifier ”elke”. Results of picture verification tasks before training, after training, and 5 weeks after training, show that 10 out of 24 children improved to correctly use the quantifier most of the time. This suggests that a single session of informative examples is not enough for most children to trigger a correct understanding.

Item Type: Thesis (Bachelor's Thesis)
Supervisor:
Supervisor nameSupervisor E mail
Spenader, J.K.J.K.Spenader@rug.nl
Degree programme: Artificial Intelligence
Thesis type: Bachelor's Thesis
Language: English
Date Deposited: 14 Aug 2018
Last Modified: 15 Aug 2018 08:44
URI: http://fse.studenttheses.ub.rug.nl/id/eprint/18299

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