The Inferential Language Comprehension (iLC) Framework: Supporting Children's Comprehension of Visual Narratives

Abstract

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.