This article reviews recent progress made by computational studies investigating the emergence, via learning or evolutionary mechanisms, of communication among a collection of agents. This work spans issues related to animal communication and the origins and evolution of language. The studies reviewed show how population size, spatial constraints on agent interactions, and the tasks involved can all influence the nature of the communication systems and the ease with which they are learned and/or evolved. Although progress in this area has been substantial, we are able to identify some important areas for future research in the evolution of language, including the need for further computational investigation of key aspects of language such as open vocabulary and the more complex aspects of syntax.

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Few teachers receive adequate preparation to provide effective individualized instruction for children with intensive early writing needs. In this article, the authors describe an attempt to close this learning gap, by developing Data-Based Instruction-Tools, Learning, and Collaborative Support (DBI-TLC), a comprehensive professional development (PD) system that provides tools, learning opportunities, and ongoing collaborative supports for teachers to implement DBI in early writing. They describe the theoretical framework that has guided this work, the teacher population with whom they worked, their approach to assessing important teacher outcomes, and their development process. They highlight key findings that align with their theory of change, and discuss implications for further research and teacher preparation.

We present an integrated theoretical framework guiding the use of visual narratives in educational settings. We focus specifically on the use of static and dynamic visual narratives to teach and assess inference skills in young children and discuss evidence to support the efficacy of this approach. In doing so, first we review the basis of the integrated framework, which builds on major findings of cognitive, developmental, and language research highlighting that (a) inference skills can be developed in non‐reading contexts using different media, (b) inference skills can transfer across different media, and (c) inference skills can be improved using questioning that includes scaffolding and specific feedback. Second, we review instructional and assessment approaches that align with the proposed framework; these approaches are designed to teach or assess inference making skills using visual narratives and interactive questioning. In this context, we discuss how these approaches leverage the unique affordances of static and dynamic visual narratives with respect to unit of meaning (by increasing opportunities to generate inferences), multimodality (by providing opportunities to generate inferences of higher complexity than text), and vocabulary/knowledge demands (by providing vocabulary/knowledge support), while also reviewing evidence for their usability, feasibility, and efficacy to improve educational outcomes. We conclude with important theoretical and practical questions about future work in this area.