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For a horse to succeed in a show-jumping career, the individual has to possess both excellent physical abilities as well as a suitable personality to perform under challenging conditions. Forty-one Dutch Warmblood horses were used to develop personality tests and correlations between test variables and early training performances in jumping were studied. In behavioural tests, during the first 2 years of the horses' lives, personality aspects like emotionality, reactivity to human and learning abilities were quantified. At the age of 3, horses were broken and received early training in show-jumping. The inter-relationship between several performance variables measured during this early training phase were studied using principal component analysis (PCA). Variables measured in the different personality tests (novel-object test, handling test, avoidance-learning test and a reward-learning test) showed no correlations, suggesting that these tests all triggered different aspects of a horse's personality. This study indicates that it is possible to predict a substantial part of the show-jumping performance of an individual horse later in life by personality traits earlier in life.

Ability. --- Age. --- Analysis. --- Association. --- Avoidance learning. --- Behavioural test. --- Emotionality. --- Handling. --- Horse. --- Horses. --- Human. --- Jumping. --- Learning ability. --- Learning-ability. --- Learning. --- Life. --- Performance. --- Personality. --- Physical. --- Principal component analysis. --- Reactivity. --- Test. --- Tests. --- Training.

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The shared platform of the articles collected in this volume is usedto advocate a dynamical systems approach to cognition. It is arguedthat recent developments in cognitive science towards an account ofembodiment, together with the general approach of complexity theoryand dynamics, have a major impact on behavioral and cognitivescience.

Cognition. --- Cognitive psychology. --- Self-organizing systems. --- Learning systems (Automatic control) --- Self-optimizing systems --- Cybernetics --- Intellect --- Learning ability --- Synergetics --- Psychology, Cognitive --- Cognitive science --- Psychology

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Human performance on diverse tests of intellect are impacted by a "general" regulatory factor that accounts for up to 50% of the variance between individuals on intelligence tests. Neurobiological determinants of general cognitive abilities are essentially unknown, owing in part to the paucity of animal research wherein neurobiological analyses are possible. We report a methodology with which we have assessed individual differences in the general learning abilities of laboratory mice. Abilities of mice on tests of associative fear conditioning, operant avoidance, path integration, discrimination, and spatial navigation were assessed. Tasks were designed so that each made unique sensory, motor, motivational, and information processing demands on the animals. A sample of 56 genetically diverse outbred mice (CD-1) was used to assess individuals' acquisition on each task. Indicative of a common source of variance, positive correlations were found between individuals' performance on all tasks. When tested on multiple test batteries, the overall performance ranks of individuals were found to be highly reliable and were "normally" distributed. Factor analysis of learning performance variables determined that a single factor accounted for 38% of the total variance across animals. Animals' levels of native activity and body weights accounted for little of the variability in learning, although animals' propensity for exploration loaded strongly ( and was positively correlated) with learning abilities. These results indicate that diverse learning abilities of laboratory mice are influenced by a common source of variance and, moreover, that the general learning abilities of individual mice can be specified relative to a sample of peers

Ability. --- Acquisition. --- Activity. --- Analysis. --- Animal. --- Animals. --- Avoidance. --- Body weight. --- Body-weight. --- Brain. --- Cognitive-ability. --- Conditioning. --- Demand. --- Discrimination. --- Enhancement. --- Exploration. --- Expression. --- Fear. --- Genetics. --- Human. --- Individual difference. --- Individual differences. --- Individual-differences. --- Intelligence,general intelligence,fluid intelligence,associative learning,memory,spatial learning,emotional learning,learning systems,genetic variation,behavioral phenotypes. --- Intelligence. --- Laboratory mice. --- Laboratory. --- Learning ability. --- Learning-ability. --- Learning. --- Level. --- Memory. --- Methodology. --- Mice. --- Navigation. --- Performance. --- Rank. --- Rat. --- Research. --- Sensory. --- Spatial. --- System. --- Task. --- Tasks. --- Test. --- Tests. --- Variability. --- Weight.

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This volume brings together a distinguished, international list of scholars to explore the role of the learner's intention in knowledge change. Traditional views of knowledge reconstruction placed the impetus for thought change outside the learner's control. The teacher, instructional methods, materials, and activities were identified as the seat of change. Recent perspectives on learning, however, suggest that the learner can play an active, indeed, intentional role in the process of knowledge restructuring. This volume explores this new, innovative view of conceptual change learning u

Concepts. --- Change (Psychology) --- Learning, Psychology of. --- Intention. --- Attitude (Psychology) --- Learning --- Psychology of learning --- Educational psychology --- Comprehension --- Learning ability --- Concept formation --- Abstraction --- Knowledge, Theory of --- Perception --- Psychology --- Psychological aspects --- Concepts --- Intention --- Learning, Psychology of --- #PBIB:2003.3 --- #PBIB:2004.4 --- #PBIB:gift 2004 --- Change (Psychology).

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A goal of mine ever since becoming an educational researcher has been to help construct a sound theory to guide instructional practice. For far too long, educational practice has suffered because we have lacked firm instructional guidelines, which in my view should be based on sound psychological theory, which in turn should be based on sound neurological theory. In other words, teachers need to know how to teach and that "how-to-teach" should be based solidly on how people learn and how their brains function. As you will see in this book, my answer to the question of how people learn is that we all learn by spontaneously generating and testing ideas. Idea generating involves analogies and testing requires comparing predicted consequences with actual consequences. We learn this way because the brain is essentially an idea generating and testing machine. But there is more to it than this. The very process ofgenerating and testing ideas results not only in the construction of ideas that work (i. e. , the learning of useful declarative knowledge), but also in improved skill in learning (i. e. , the development of improved procedural knowledge).

Education. --- Mathematics --- Science education. --- Science Education. --- Mathematics Education. --- Education, general. --- Learning & Instruction. --- Study and teaching. --- #PBIB:2003.2 --- Learning --- Learning, Psychology of. --- Physiological aspects. --- Learning, Psychology of --- Psychology of learning --- Physiological aspects --- Psychological aspects --- Mathematics—Study and teaching . --- Learning. --- Instruction. --- Neuropsychology --- Educational psychology --- Comprehension --- Learning ability --- Learning process --- Education --- Children --- Education, Primitive --- Education of children --- Human resource development --- Instruction --- Pedagogy --- Schooling --- Students --- Youth --- Civilization --- Learning and scholarship --- Mental discipline --- Schools --- Teaching --- Training --- Science education --- Scientific education