155 research outputs found

    Developing structural representations: their role in analogical reasoning

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    Recent research into the development of analogical reasoning has shown that young children are able to recognise and use relational similarity between situations, provided that they possess the necessary domain knowledge (Goswami, 1992). However, in most of the reported studies, the relational structure of the analogy has been made very salient. Circumstances where the relational structure of a problem has to be represented by the problem-solver themselves could result in differing performance. We do not know whether, or in what circumstances, children can correctly construct a representation of the relevant relational information. This thesis reports a series of experiments which investigate the role and development of structural representations for the purposes of analogical reasoning. The first two experiments tested whether primary aged children are able to construct an integrated external task representation by combining separate pieces of relational knowledge. Using series problems as a domain, they provided evidence that performance was not affected by the actual relation used, i.e. either spatial or non-spatial (abstract). However, it was observed that the order in which the task information was presented had an effect. The next four studies explored this by using spatial series problems. They showed that tasks which required a novel item to be placed to the left of (that is, at the front of) a partially ordered array inhibited performance. A further three experiments found that the reason for the inhibition was that unless the different pieces of relational information were highlighted as distinct items, they would be incorrectly integrated by using simple 'add-to-end' ordering rules. The final set of studies, using abstract evaluative relations in series problems, found that relational-highlighting effects generalised to these types of tasks. Also, the results showed that some evaluative relations were tied to either horizontal or vertical spatial representations and that performance was affected by how consistent the representation was with the child's experience of every-day life. The thesis showed that the ability to construct structural task representations is affected by features which are inherent in the presentation of specific tasks, and that incorrect structural representations in turn affect analogical mapping. These findings are discussed in terms of the 'generalised schemas' used during analogical mapping. It is suggested that these might be reconstructed using specific task information, rather than being retrieved intact from memory

    Developing structural representations: their role in analogical reasoning

    Get PDF
    Recent research into the development of analogical reasoning has shown that young children are able to recognise and use relational similarity between situations, provided that they possess the necessary domain knowledge (Goswami, 1992). However, in most of the reported studies, the relational structure of the analogy has been made very salient. Circumstances where the relational structure of a problem has to be represented by the problem-solver themselves could result in differing performance. We do not know whether, or in what circumstances, children can correctly construct a representation of the relevant relational information. This thesis reports a series of experiments which investigate the role and development of structural representations for the purposes of analogical reasoning. The first two experiments tested whether primary aged children are able to construct an integrated external task representation by combining separate pieces of relational knowledge. Using series problems as a domain, they provided evidence that performance was not affected by the actual relation used, i.e. either spatial or non-spatial (abstract). However, it was observed that the order in which the task information was presented had an effect. The next four studies explored this by using spatial series problems. They showed that tasks which required a novel item to be placed to the left of (that is, at the front of) a partially ordered array inhibited performance. A further three experiments found that the reason for the inhibition was that unless the different pieces of relational information were highlighted as distinct items, they would be incorrectly integrated by using simple 'add-to-end' ordering rules. The final set of studies, using abstract evaluative relations in series problems, found that relational-highlighting effects generalised to these types of tasks. Also, the results showed that some evaluative relations were tied to either horizontal or vertical spatial representations and that performance was affected by how consistent the representation was with the child's experience of every-day life. The thesis showed that the ability to construct structural task representations is affected by features which are inherent in the presentation of specific tasks, and that incorrect structural representations in turn affect analogical mapping. These findings are discussed in terms of the 'generalised schemas' used during analogical mapping. It is suggested that these might be reconstructed using specific task information, rather than being retrieved intact from memory

    Tangible user interfaces : past, present and future directions

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    In the last two decades, Tangible User Interfaces (TUIs) have emerged as a new interface type that interlinks the digital and physical worlds. Drawing upon users' knowledge and skills of interaction with the real non-digital world, TUIs show a potential to enhance the way in which people interact with and leverage digital information. However, TUI research is still in its infancy and extensive research is required in or- der to fully understand the implications of tangible user interfaces, to develop technologies that further bridge the digital and the physical, and to guide TUI design with empirical knowledge. This paper examines the existing body of work on Tangible User In- terfaces. We start by sketching the history of tangible user interfaces, examining the intellectual origins of this field. We then present TUIs in a broader context, survey application domains, and review frame- works and taxonomies. We also discuss conceptual foundations of TUIs including perspectives from cognitive sciences, phycology, and philoso- phy. Methods and technologies for designing, building, and evaluating TUIs are also addressed. Finally, we discuss the strengths and limita- tions of TUIs and chart directions for future research

    Aspects of strip-cartoon interpretation in 5 to 7 - year old children

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    Intelligent systems: towards a new synthetic agenda

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    Statistical language learning

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    Theoretical arguments based on the "poverty of the stimulus" have denied a priori the possibility that abstract linguistic representations can be learned inductively from exposure to the environment, given that the linguistic input available to the child is both underdetermined and degenerate. I reassess such learnability arguments by exploring a) the type and amount of statistical information implicitly available in the input in the form of distributional and phonological cues; b) psychologically plausible inductive mechanisms for constraining the search space; c) the nature of linguistic representations, algebraic or statistical. To do so I use three methodologies: experimental procedures, linguistic analyses based on large corpora of naturally occurring speech and text, and computational models implemented in computer simulations. In Chapters 1,2, and 5, I argue that long-distance structural dependencies - traditionally hard to explain with simple distributional analyses based on ngram statistics - can indeed be learned associatively provided the amount of intervening material is highly variable or invariant (the Variability effect). In Chapter 3, I show that simple associative mechanisms instantiated in Simple Recurrent Networks can replicate the experimental findings under the same conditions of variability. Chapter 4 presents successes and limits of such results across perceptual modalities (visual vs. auditory) and perceptual presentation (temporal vs. sequential), as well as the impact of long and short training procedures. In Chapter 5, I show that generalisation to abstract categories from stimuli framed in non-adjacent dependencies is also modulated by the Variability effect. In Chapter 6, I show that the putative separation of algebraic and statistical styles of computation based on successful speech segmentation versus unsuccessful generalisation experiments (as published in a recent Science paper) is premature and is the effect of a preference for phonological properties of the input. In chapter 7 computer simulations of learning irregular constructions suggest that it is possible to learn from positive evidence alone, despite Gold's celebrated arguments on the unlearnability of natural languages. Evolutionary simulations in Chapter 8 show that irregularities in natural languages can emerge from full regularity and remain stable across generations of simulated agents. In Chapter 9 I conclude that the brain may endowed with a powerful statistical device for detecting structure, generalising, segmenting speech, and recovering from overgeneralisations. The experimental and computational evidence gathered here suggests that statistical language learning is more powerful than heretofore acknowledged by the current literature
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