This paper proposes "grounded feedback" as a way to provide implicit verification when students are working with a novel representation. In grounded feedback, students' responses are in the target, to-be-learned representation, and those responses are reflected in a more-accessible linked representation that is intrinsic to the domain. By examining the accessible feedback representation, students can infer if their work with the novel representation is correct. This paper presents the criteria for grounded feedback, provides examples of systems that implement grounded feedback, contrasts grounded feedback with similar feedback types, and discusses the evidence for grounded feedback's effectiveness. Controlled experiments with random assignment that compare grounded feedback to other approaches are limited in number and scope (i.e., comparisons to explicit verification with and without text hints, linked representations, and no feedback). The two experiments we found with full implementation of grounded feedback and a sample size larger than 20 found robust learning benefits of grounded feedback over explicit verification feedback. These results are promising and indicate that grounded feedback warrants further investigation.