This article reviews two aspects of human learning: (1) people draw inferences that appear to rely on hierarchical conceptual representations; (2) some categories are much easier to learn than others given the same number of exemplars, and some categories remain difficult despite extensive training. Both of these results are difficult to reconcile…

Humans are sensitive to the properties of individual items, and exemplar models are useful for capturing this sensitivity. I am a proponent of an extension of exemplar-based architectures that I briefly describe. However, exemplar models are very shallow architectures in which it is necessary to stipulate a set of primitive elements that make up…

Instruction in many STEM domains heavily relies on visual representations, such as graphs, figures, and diagrams. However, students who lack representational competencies do not benefit from these visual representations. Therefore, students must learn not only content knowledge but also representational competencies. Further, as learning…

Ambridge argues that the existence of exemplar models for individual phenomena (words, inflection rules, etc.) suggests the feasibility of a unified, exemplars-everywhere model that eschews abstraction. The argument would be strengthened by a description of such a model. However, none is provided. I show that any attempt to do so would immediately…

A key property of relational representations is their "generativity": From partial descriptions of relations between entities, additional inferences can be drawn about other entities. A major theoretical challenge is to demonstrate how the capacity to make generative inferences could arise as a result of learning relations from…

Learning progressions (LPs) are novel models for the development of assessments in science education, that often use a scale to categorize students' levels of reasoning. Pictorial representations are important in chemistry teaching and learning, and also in LPs, but the differences between pictorial and verbal items in chemistry LPs is unclear. In…

Abstraction is a core principle of Distributional Semantic Models (DSMs) that learn semantic representations for words by applying dimensional reduction to statistical redundancies in language. Although the posited learning mechanisms vary widely, virtually all DSMs are prototype models in that they create a single abstract representation of a…

Ambridge argues that there is widespread agreement among child language researchers that learners store linguistic abstractions. In this commentary the authors first argue that this assumption is incorrect; anti-representationalist/exemplar views are pervasive in theories of child language. Next, the authors outline what has been learned from this…

This article demonstrates the potential of using hierarchical Bayesian methods to relate models and data in the cognitive sciences. This is done using a worked example that considers an existing model of category representation, the Varying Abstraction Model (VAM), which attempts to infer the representations people use from their behavior in…

An intelligence model of processes and content of thought is proposed. Processes include remembering, evaluating, generating, and transforming, while content is self, forms, ideas, and persons, determining levels of complexity for learning. The TETRA model is compared with J.P. Guilford's aptitude structure of intellect. Theory implications for…

Explores the effects of Roundhouse diagram construction on a previously low-performing middle school science student's struggles to understand abstract science concepts and principles. Based on a metacognition-based visual learning model, aims to elucidate the process by which Roundhouse diagramming helps learners bootstrap their current…

Describes ways of projecting stereoscopic images of geologic environments for students with difficulty reasoning in three-dimensions. The photographic procedures needed to produce stereo slides are included. (MA)

The question of whether skills in achieving understanding and retention of information at high levels of abstraction can be taught is addressed by analyzing some of the mental processes involved, and briefly reviewing a number of attempts that have been made to induce these processes. (Author)

Discussion of students' prior knowledge and its effect on analogical reasoning focuses on four case studies of high school and college students that were designed to determine factors important for success in overcoming misconceptions via analogical reasoning. Explanatory models are explained, and abstract transfer versus explanatory model…