Recently there has been controversy about whether Intelligent Tutoring Systems are. even potentially, more effective than standard C A L programs, that is, whether it is educationally more valuable to attempt to identify the cause of user's mistakes rather than merely explain the correct method. This issue was addressed by comparative testing of two versions of the S U M I T Intelligent Tutoring Assistant for arithmetic using a diagnostic version, which diagnosed errors and gave appropriate messages, and a 'CAL' version was identical in all respects except that it made no diagnoses and therefore gave standard error messages indicating the correct method. In a comparative study of the two versions, a class of 9 year old children were flrst divided into two matched groups on the basis of a pencil and paper pre-tesi, then both groups had two 30 minute individual sessions with the appropriate version of SUMIT, and then performance was assessed on a subsequent pencil and paper post-test. Both groups improved significantly in their performance from pre-test to post-test, but the diagnostic group showed significantly greater reductions in the number of bugs. It is concluded that diagnostic remediation can be more effective than non-diagnostic approaches.

Declarative learning by experience is a foundation cognitive c^ability, and w e argue that, over and above the normal processes of declarative learning, the ability for truly novel learning is the critical capability which bootstraps human cognition. Next w e assert that none of the established models of machine learning and no established architecture for cognition have adequate declarative learning capabilities, in that all depend for their success on some pre-characterisation of the learning domain in terms of state space or pre-existing primitives geared to the domain. Finally we describe briefly the Contextual Memory System, which was designed explicitly to sup{>ort all five declarative learning capabilities. The C M S underlies the Maths Understander machine learning system which 'reads' mathematics texts from scratch, assimilating mathematics concepts, and using them not only to check proofs but also to solve problems.

A series of experiments will be reported comparing the performance of groups of 11 year old and IS year old children with dyslexia with groups of normal children matched for chronological age (CA) and reading age (RA) respectively. Experiments testing gross motor skill demonstrated that both groups of children with dyslexia showed significant deficits in balance when required to undertake a further task at the same time, whereas the control groups were not affected. It was concluded that the control children balanced automatically whereas the children with dyslexia did not. Further experiments indicated that working memory performance was not diswdered, in that deficits in memory span were paralleled by deficits in speed of articulation. Tests of information processing speed led to an interesting dissociation. Simple reaction performance was indistinguishable from that of the C A controls. By contrast, on the simplest possible choice reaction, both groups of children with dyslexia were slowed to the level of their R A controls. It was concluded that the locus of the speed deficit lay within the decision-making process. Further experiments demonstrating deficits in sensory thresholds and abnormal evoked potentials will also be reported. W e conclude that an auiomatisation deficit is consistent with most of the known problems of children with dyslexia.

Anomalies have been found in a range of skills for children with dyslexia. The study presented here investigated performance on the full range of primitive skills for with dyslexia and normal children at ages 8, 11 and 16 years. Unexpectedly severe deficits were revealed in a range of skills, including motor skill, phonological skill, and processing speed. Overall, the performance of the 16 year old children with dyslexia was no better than that of the 8 year old normal children, with some skills being significantly worse, and some better. The results are inierpteted in terms of a developmental progression in which children with dyslexia suffer from general deficits in primitive skill learning, but are able to consciously compensate in many skills. We believe that a connectionist learning framewcxk may provide a parsimonious account of the range of deficits, providing a potential link between these difficulties in skilled performance and the underlying neuroanatomical abnormalities

Two studies are reported in which a group of adolescent children with dyslexia and a group of normal children matched for age and IQ undertook extended training. In Study 1, which comprised three phases of learning over an 18 month period, the children learned to navigate via key presses around a fixed circuit of a computer maze. It w a s concluded that, following extended training under these optimal conditions, the children with dyslexia had normal 'strength' of automatisation (as assessed by resistance to unlearning, by ease of releaming, and by dual task performance) but that their 'quality' of automatisation (as assessed by speed and accuracy) was impaired. Study 2 investigated the blending of two compatible simple reaction responses into a two choice reaction. Although performance on the simple reactions was equivalent across groups, the children with dyslexia had m o r e difficulty combining the two skills at firstand showed significantly less learning over the course of the training period. T h e estimated learning rate was around 5 0 % slower for the children with dyslexia, leading to the prediction that the proportionate slowing in acquisition time would increase as the square root of the normal acquisition time. A connectionist frameworic may provide a natural explanation of the phenomena.

We describe an experimental investigation of the development of children's knowledge stmctures which aims to provide data for connectionist modelling. 167 children between 5 and 11 years of age completed two category fluency tasks where they were asked to produce as many names of a) animals and b) parts of the body, as they could in one minute. Similarity scores were derived based on distances between concepts in the lists produced. These were analysed using the ADDtree algorithm (Sattath & Tversky, 1977) to build structures representing the organisation of the children's knowledge of animals and body parts. The results showed that animal knowledge was generally organised in terms of environmental context/habitat, however, there was evidence for subtle changes in knowledge organisation between age groups. More pronounced changes were observed in the organisation of knowledge of body parts which gave some support to the assertion that children progress from making coarser to making fmer distinctions between concepts (see Keil, 1979) and reflected the progression observed in knowledge structure development in a connectionist model of semantic memory discussed by McClelland, McNaughton and O'Reilly (1995). Our aim is to extend this work to provide data enabling connectionist modelling of semantic memory within a developmental framework.