汽车维修专业学习领域课程开发的探索与实践

工作过程导向的学习领域课程开发成为了高职教育课程开发的主要模式。一般开发步骤：工作任务分析。行动领域归纳,学习领域转换,学习情境设计。广东机电职业技术学院“基于工学结合的汽车专业高技能人才职业能力的御新培养”获第六届广东省高等教育教学成果一等奖,其中对汽车维修专业学习领域课程开发进行了研究与实践,提供了实例。     

Estimating future prices for stationary fuel cells with empirically derived experience curves

Fuel cells presently require an order of magnitude cost reduction to become a commercial success in domestic energy markets. Previous analyses using learning curves have shown that competitive costs are feasible, but these have been unanimously based on theoretical estimates.     

基于复杂网络的社会性软件研究

本文阐述了社会性软件的概念及其主要研究情况,结合社会性软件的特点及其与复杂网络的联系,介绍了复杂网络的相关概念和特性,讨论了一个基于复杂网络而构建的学习网络模型.     

Parameter determination for a generalized fuzzy model

This paper underlines a way to evolve a generalized fuzzy model (GFM), using the interpolation of CRI and TS models in their consequent parts of fuzzy rules. The GFM possesses the index of fuzziness of CRI model and the local model of the TS model. The parameters of the GFM are estimated by a two-step process. The consequent part of fuzzy rules is reformulated to suit the LSE framework for estimating the associated parameters. By assuming Generalized Gaussian membership function for the premise parts, Gradient descent technique is used to update its parameters. The performance of two classes of GFM has been tested on two systems and it is shown that class II GFM is the best out of all the fuzzy models tested.     

Increasing the power of uniform inductive learners

The analysis of theoretical learning models is basically concerned with the comparison of identification capabilities in different models. Modifications of the formal constraints affect the quality of the corresponding learners on the one hand and regulate the quantity of learnable classes on the other hand.For many inductive inference models—such as Gold's identification in the limit—the corresponding relationships of learning potential provided by the compatible learners are well-known. Recent work even corroborates the relevance of these relationships by revealing them still in the context of uniform Gold-style learning. Uniform learning is rather concerned with the synthesis of successful learners instead of their mere existence.The subsequent analysis further strengthens the results regarding uniform learning, particularly aiming at the design of methods for increasing the potential of the relevant learners. This demonstrates how to improve given learning strategies instead of just verifying the existence of more powerful uniform learners.For technical reasons these results are achieved using various formal conditions concerning the learnability of unions of uniformly learnable classes. Therefore numerous sufficient properties for the learnability of such unions are presented and illustrated with several examples.     

A dialogic understanding of the relationship between CSCL and teaching thinking skills

How to teach flexible thinking and learning skills, particularly creativity and the skill of “learning to learn,” is a key concern for CSCL in the context of the emerging Networked Society. The currently dominant paradigms for supporting pedagogical design within CSCL, including socio-cultural theory, are limited in the support that they can offer to the project of teaching general thinking skills. This paper uses critical literature review, conceptual analysis, and evidence from case studies to argue for the value of a dialogic interpretative framework that links the goal of teaching thinking with the method of CSCL. The evidence reviewed suggests that dialogue is itself the primary thinking skill from which all others are derived. It is argued from this that dialogic theory offers a possible solution to the problem of how to conceptualize general thinking skills for CSCL: this is that teaching dialogue as an end in itself promotes the learning of general thinking skills. Implications of the proposed framework for pedagogical design are brought out through case studies illustrating the use of CSCL to broaden and deepen dialogic spaces of reflection.     

小剂量氚水宫内辐射对出生后仔鼠行为、学习及记忆能力的影响

报道了在妊娠期以单次腹腔注入氚水,宫内受到累积剂量分别为0、0.05、0.10和0.30Gyβ射丝辐射后,对雄性仔鼠行为、学习及记忆能力的影响。研究发现0.10Gy以上剂量组对旷场行为,跳台学习及记忆能力、食物迷宫、水迷宫和孔板探究等多项测试指标均有影响,表现为早期兴奋性增强、晚期抑制及学习记忆能力的减退。结果提示阈剂量大约在0.05和0.10 Gy之间。     

Supporting reflection and dialogue in a community of machine setters: Lessons learned from design and use of a hypermedia type training material

The debate about experience-based or tacit knowledge has focused much attention on the limits to formalisation of work process knowledge. A main line of argument has been that, for example, industrial work even with highly advanced technical equipment can only be performed adequately when the worker through experience on the job has gained a feel for the functioning of the machinery and the properties and behaviour of the materials. In this debate links tend to be created between on the one hand formalised-abstracted-verbal knowledge as opposed to on the other hand informalised-concrete-tacit knowledge. We have worked for some years with the design of training materials which at its core have video documentation of best practice as we have found it at work. In this paper we will present and discuss experience with design and use of a hypermedia type training material, SPRING to be used by new machine setters in the spring industry. Based on our own experience we will argue for the relevance of this type of training materials as a means of supporting reflection and dialogue in the community of practitioners.     

Spatial learning with perceptually grounded representations

The goal of this paper is to develop the foundation for a spatial navigation without objective representations. Rather than building the spatial representations on a Euclidean space, a weaker conception of space is used. A type of spatial representation is described that uses perceptual information directly to define the regions in space. By combining such regions, it is possible to derive a number of useful spatial representations such as place-fields, paths and topological maps. Compared to other methods, the representations of the present approach have the advantage that they are always grounded in the perceptual abilities of the robot.     

A comparison of adaptive control strategies for hot steel strip rolling mills

Many modeling situations occur in which the plant has uncertain dynamics, nonlinearities, time varying characteristics and noise corrupted input and output measurements. These processes generally require a human operator whose function is to provide intelligent modeling and control. This exact situation occurs in the modeling and control of roll force in a hot steel rolling mill. It is the purpose of this paper to investigate and compare various adaptive control strategies for this problem.The first strategy uses a parameter identification technique to track the parameters in the roll force setup model from one steel run to the next. The next algorithm provides feedback control from run to run by an adaptive controller which uses a linear reinforcement learning scheme to adjust its parameters. The third method accounts for the above complexities by approaching the problem from a behavioral and structural point of view. The behavior of the model is assessed through a performance evaluator and the model is modified structurally and parametrically to improve the performance of the system as the process evolves. The derivation is based on correlation techniques and linear reinforcement learning theory, the latter of which provides memory and intelligence to the algorithm to model the decision process of the human operator. The results of this work serve to reinforce the opinion that the nonlinear mathematical structure of the model should be able to change from one steel run to the next in order to compensate for changes in mill characteristics and in the mill environment. Modeling results are presented from actual mill data and comparisons are made with time invariant models. In addition, the algorithms are general enough so that they may be easily applied to other processes that seem to defy traditional modeling techniques. They are not case dependent.