What is ‘counterintuitive’? There is general agreement that it refers to a violation of previously held knowledge, but the precise definition seems to vary with every author and study. The aim of this paper is to deconstruct the notion of ‘counterintuitive’ and provide a more philosophically rigorous definition congruent with the history of psychology, recent experimental work in ‘minimally counterintuitive’ concepts, the science vs. religion debate, and the developmental and evolutionary background of human beings. We conclude that previous definitions of (...) counterintuitiveness have been flawed and did not resolve the conflict between a believer’s conception of the supernatural entity (an atypical “real kind”) and the non-believer’s conception (empty name/fictional). Furthermore, too much emphasis has been placed on the universality and (presumed) innateness of intuitive concepts (and hence the criteria for what is counterintuitive)—and far too little attention paid to learning and expertise. We argue that many putatively universal concepts are not innate, but mostly learned and defeasible—part of a religious believer’s repertoire of expert knowledge. Nonetheless, the results from empirical studies about the memorability of counterintuitive concepts have been convincing and it is difficult to improve on existing designs and methodologies. However, future studies in counterintuitive concepts need to embed their work in research about context effects, typicality, the psychology of learning and expertise (for example, the formation of expert templates and range defaults), with more attention to the sources of knowledge (direct and indirect knowledge) and a better idea of what ‘default’ knowledge really is. (shrink)

The informativity of a computational model of language acquisition is directly related to how closely it approximates the actual acquisition task, sometimes referred to as the model's cognitive plausibility. We suggest that though every computational model necessarily idealizes the modeled task, an informative language acquisition model can aim to be cognitively plausible in multiple ways. We discuss these cognitive plausibility checkpoints generally and then apply them to a case study in word segmentation, investigating a promising Bayesian segmentation strategy. We incorporate (...) cognitive plausibility by using an age-appropriate unit of perceptual representation, evaluating the model output in terms of its utility, and incorporating cognitive constraints into the inference process. Our more cognitively plausible model shows a beneficial effect of cognitive constraints on segmentation performance. One interpretation of this effect is as a synergy between the naive theories of language structure that infants may have and the cognitive constraints that limit the fidelity of their inference processes, where less accurate inference approximations are better when the underlying assumptions about how words are generated are less accurate. More generally, these results highlight the utility of incorporating cognitive plausibility more fully into computational models of language acquisition. (shrink)

Children with specific language impairment (SLI) show a protracted period of inconsistent use of tense/agreement morphemes. The purpose of this investigation was to determine whether this inconsistent use could be attributed to the children's misinterpretations of particular syntactic structures in the input. In Study 1, preschool-aged children with SLI and typically developing peers heard sentences containing novel verbs preceded by auxiliary was or sentences in which the novel verb formed part of a nonfinite subject-verb sequence within a larger syntactic structure (...) (e.g. We saw the dog relling). The children were then tested on their use of the novel verbs in contexts that obligated use of auxiliary is. The children with SLI were less accurate than their peers and more likely to produce the novel verb without is if the verb had been heard in a nonfinite subject-verb sequence. In Study 2, children with SLI and typically developing peers were tested on their comprehension of sentences such as The cow sees the horse eating. The children with SLI were less accurate than their peers and were disproportionately influenced by the nonfinite subject-verb clause at the end of the sentence. We interpret these findings within the framework of construction learning. (shrink)

Leech et al.'s demonstration that analogical reasoning can be an emergent property of low-level incremental learning processes is critical for analogical theory. Along with insights into neural learning based on the salience of dynamic spatio-temporal structure, and the neural priming mechanism of repetition suppression, it establishes relational primacy as a plausible theoretical description of how brains make analogies.

Leech et al.'s model proposes representing relations as primed transformations rather than as structured representations (explicit representations of relations and their roles dynamically bound to fillers). However, this renders the model unable to explain several developmental trends (including relational integration and all changes not attributable to growth in relational knowledge). We suggest looking to an alternative computational model that learns structured representations from examples.

Despite its strengths, Leech et al.'s model fails to address the important benefits that derive from self-explanation and task feedback in analogical reasoning development. These components encourage explicit, self-reflective processes that do not necessarily link to knowledge accretion. We wonder, therefore, what mechanisms can be included within a connectionist framework to model self-reflective involvement and its beneficial consequences.