Title: Convolution Forgetting Curve Model for Repeated Learning,
Abstract: Most of mathematic forgetting curve models fit well with the forgetting data
under the learning condition of one time rather than repeated. In the paper, a
convolution model of forgetting curve is proposed to simulate the memory
process during learning. In this model, the memory ability (i.e. the central
procedure in the working memory model) and learning material (i.e. the input in
the working memory model) is regarded as the system function and the input
function, respectively. The status of forgetting (i.e. the output in the
working memory model) is regarded as output function or the convolution result
of the memory ability and learning material. The model is applied to simulate
the forgetting curves in different situations. The results show that the model
is able to simulate the forgetting curves not only in one time learning
condition but also in multi-times condition. The model is further verified in
the experiments of Mandarin tone learning for Japanese learners. And the
predicted curve fits well on the test points.