Mechanical knowledge does matter to tool use even when assessed with a non-production task: Evidence from left brain-damaged patients

In the literature on apraxia of tool use, it is now accepted that using familiar tools requires semantic and mechanical knowledge. However, mechanical knowledge is nearly always assessed with production tasks, so one may assume that mechanical knowledge and familiar tool use are associated only because of their common motor mechanisms. This notion may be challenged by demonstrating that familiar tool use depends on an alternative tool selection task assessing mechanical knowledge, where alternative uses of tools are assumed according to their physical properties but where actual use of tools is not needed. We tested 21 left brain-damaged patients and 21 matched controls with familiar tool use tasks (pantomime and single tool use), semantic tasks and an alternative tool selection task. The alternative tool selection task accounted for a large amount of variance in the single tool use task and was the best predictor among all the semantic tasks. Concerning the pantomime of tool use task, group and individual results suggested that the integrity of the semantic system and preserved mechanical knowledge are neither necessary nor sufficient to produce pantomimes. These results corroborate the idea that mechanical knowledge is essential when we use tools, even when tasks assessing mechanical knowledge do not require the production of any motor action. Our results also confirm the value of pantomime of tool use, which can be considered as a complex activity involving several cognitive abilities (e.g., communicative skills) rather than the activation of gesture engrams.     

Ability and Knowing How in the Situation Calculus

Most agents can acquire information about their environments as they operate. A good plan for such an agent is one that not only achieves the goal, but is also executable, i.e., ensures that the agent has enough information at every step to know what to do next. In this paper, we present a formal account of what it means for an agent to know how to execute a plan and to be able to achieve a goal. Such a theory is a prerequisite for producing specifications of planners for agents that can acquire information at run time. It is also essential to account for cooperation among agents. Our account is more general than previous proposals, correctly handles programs containing loops, and incorporates a solution to the frame problem. It can also be used to prove programs containing sensing actions correct.     

Interpersonal Understanding Fuels Knowledge Acquisition

Beginning in infancy, humans acquire knowledge at a pace far outstripping that found in any other species. Recent evidence indicates that interpersonal understanding—in particular, skill at inferring others' intentions—plays a pivotal role in this achievement. Infants as young as 12 to 18 months actively utilize clues to others' intentions to guide their interpretation of language, emotion, and action more generally. In the language domain, for example, on hearing a new word, infants spontaneously check the speaker for intentional clues such as gaze direction, emotional expression, gestures, and body posture, and interpret the word in light of such information. By capitalizing on information about intentions, infants are able to avoid a wide range of potential errors, and to quickly learn relevant new skills. Current research is exploring the origins and developmental course of such early-emerging interpersonal skill, ultimately with an eye to understanding how disruptions in such abilities affect children's cognitive and social development.     

Metacognitive Development

Traditional developmental research in memory and reasoning, as well as current investigations in such disparate areas as theory of mind, epistemological understanding, knowledge acquisition, and problem solving, share the need to invoke a meta-level of cognition in explaining their respective phenomena. The increasingly influential construct of metacognition can be conceptualized in a developmental framework. Young children's dawning awareness of mental functions lies at one end of a developmental progression that eventuates in complex metaknowing capabilities that many adults do not master. During its extended developmental course, metacognition becomes more explicit, powerful, and effective, as it comes to operate increasingly under the individual's conscious control. Enhancing (a) metacognitive awareness of what one believes and how one knows and (b) metastrategic control in application of the strategies that process new information is an important developmental and educational goal.     

学习策略与程序性知识迁移关系的研究

本研究以学习者拥有领域知识的水平差异为基点 ,结合元认知监控手段 ,考察学习策略与程序性知识迁移之间的关系。结果表明 :(1 )以揭发意义或价值、建立新旧知识信息间实质性联结的解释策略对拥有高、低领域知识组的被试具有明显促进问题解决的作用 ;而以相似性为基础的练习策略往往在学生头脑中建立的是新旧知识间表面特征的联结 ,因而程序化技能的迁移范围不如前者。 (2 )在运用获得的认知技能碰到阻碍时 ,解释策略不仅使高知组被试能够突破无关变量的影响 ,而且也在一定程度上弥补低知组被试掌握的规则缺陷。     

Extending adaptive world modeling by identifying and handling insufficient knowledge models

Adaptive knowledge modeling is an approach for extending the abilities of the Object-Oriented World Model, a system for representing the state of an observed real-world environment, to open-world modeling. In open environments, entities unforeseen at the design-time of a world model can occur. For coping with such circumstances, adaptive knowledge modeling is tasked with adapting the underlying knowledge model according to the environment. The approach is based on quantitative measures, introduced previously, for rating the quality of knowledge models. In this contribution, adaptive knowledge modeling is extended by measures for detecting the need for model adaptation and identifying the potential starting points of necessary model change as well as by an approach for applying such change. Being an extended and more detailed version of [17], the contribution also provides background information on the architecture of the Object-Oriented World Model and on the principles of adaptive knowledge modeling, as well as examination results for the proposed methods. In addition, a more complex scenario is used to evaluate the overall approach.     

小学数学教师职业知识的结构与内在关系

本研究以小学数学分数起始教学为媒介,通过自编的小学数学教师职业知识测验,考察了162名小学数学教师在学科知识、一般教育学知识和教育实践知识等三类知识上的表现,并据此探讨了这三类职业知识间的相互关系。研究结果表明,自编的小学数学职业知识测验具有良好的信度和结构效度,教师的学科知识和一般教育学知识能显著地预测其教育实践知识。     

Categorization as causal reasoning⋆

A theory of categorization is presented in which knowledge of causal relationships between category features is represented in terms of asymmetric and probabilistic causal mechanisms. According to causal‐model theory, objects are classified as category members to the extent they are likely to have been generated or produced by those mechanisms. The empirical results confirmed that participants rated exemplars good category members to the extent their features manifested the expectations that causal knowledge induces, such as correlations between feature pairs that are directly connected by causal relationships. These expectations also included sensitivity to higher‐order feature interactions that emerge from the asymmetries inherent in causal relationships. Quantitative fits of causal‐model theory were superior to those obtained with extensions to traditional similarity‐based models that represent causal knowledge either as higher‐order relational features or “prior exemplars” stored in memory.     

Notes on attribution functions

Let be the knowledge space derived from an attribution function σ on Q. Under an assumption for σ, this paper gives some necessary and sufficient conditions such that is discriminative. It also discusses the resolubility of σ when Q is an infinite set. More precisely, this paper proves that σ is not resoluble if Q is uncountable, and gives a necessary and sufficient condition such that σ is resoluble when is -well-graded. By way of applications of these results, discriminativeness and resolubility are discussed around the merge of skill multimaps and the meshing of the delineated knowledge spaces.