The learning model with experimenter-controlled events defined by Bush and Mosteller is generalized to a model with time-dependent learning parameters and with time-dependent probabilities for the underlying events. The main result is a limiting theorem which in part belongs to the laws of large numbers and to the theory of stochastic approximation.