The computational modeling of language development has enabled researchers to make impressive strides toward achieving a comprehensive psychological account of the processes and mechanisms whereby children acquire their mother tongues. Nevertheless, the field's primary focus on distributional information has lead to little progress in elucidating the processes by which children learn to compute meanings beyond the level of single words. This lack of psychologically motivated computational work on semantics poses an important challenge for usage‐based computational accounts of acquisition in particular, which hold that grammatical development is closely tied to meaning. In the present review, we trace some initial steps toward answering this challenge through a survey of existing computational models of grammatical development that incorporate semantic information to learn to assign thematic roles and acquire argument structure. We argue that the time is ripe for usage‐based computational accounts of grammatical development to move beyond purely distributional features of the input, and to incorporate information about the objects and actions observable in the learning environment. To conclude, we sketch possible avenues for extending previous approaches to modeling the role of semantics in grammatical development. For further resources related to this article, please visit the WIREs website. Conflict of interest: The authors have declared no conflicts of interest for this article.