This paper presents simulation results and network analysis of generative Cascade-Correlation (CC) networks which model the child's learning of English personal pronouns. The network analysis revealed that overheard speech is crucial in learning the correct semantic rules not only for first and second person pronouns but also for third person pronouns. In addition, in order to induce the fully correct semantic rules without error-correcting feedback, the networks need to learn all three personal pronouns. Network analysis techniques used in the present study proved to be a powerful tool for understanding of what the networks are actually learning.