论课程实施基本取向与教学设计的转变

课程实施的三种基本取向--忠实取向、相互适应取向、课程创生取向--实际上体现了不同的教育价值现与课程价值观.因此,在不同的课程实施取向的视野中,教学设计具有迥然不同的旨趣与方略.新课程视野下的教学设计转型,试图以课程理念发展为背景参照,以促进学习者发展为宗旨,凝聚和整合教学设计理论相关知识,解决传统教学设计范型与促进学习者发展之间的冲突,寻求对传统教学设计范型的某种超越和制衡,是教学设计研究与实践自觉适应社会和教育发展走势嬗变的一种尝试,我们需要关注教学设计转变.     

论工程造价的有效控制

建筑安装工程造价的有效控制,应该以优秀的工程设计为前提,工程招投标为核心,施工管理为重要环节,竣工结算为关键,“以人为本”是基础。工程造价的控制是贯穿于项目建设全过程的控制,即在投资决策阶段、设计阶段、建设项目发包阶段和建设实施阶段,将工程造价控制在批准的造价限额以内。     

乱针绣艺术元素在旗袍设计中的应用探究

传统的中国女装一直与刺绣艺术有着不解之缘,而当代旗袍的设计,更是将乱针绣艺术元素得到充分的应用。本文在对乱针绣艺术及旗袍礼服刺绣装饰进行阐述的基础上,对乱针绣艺术元素在旗袍设计中的创新应用效果进行探究。     

语言能力结构与教学大纲设计

英语学习者语言能力结构由四个层面组成,即语言知识、语言技能、交际能力和综合素质,各层面之间存在密切的关系。学习者语言能力结构建立可以通过教学大纲的选择和设计来实现。语法、技能、主题、情景、功能意念以及任务型教学大纲可供教师在不同的培训阶段选择使用。     

Transparency tested: The influence of message features on public perceptions of organizational transparency

The concept of transparency has been promoted within the public relations and business literature as both ethical and advantageous; however, the effectiveness of transparency is seldom empirically put to the test. In particular, the use of clarity, disclosure, and accuracy in organizational messages needs to be empirically examined. To this end, we conducted an online experiment using a 2 (high vs. low message transparency) x 2 (news story placed before or after an organizational statement) between-subjects design. Participants (n?=?357) perceived organizations as more transparent and credible when exposed to messages exhibiting greater levels of clarity, disclosure, and accuracy as opposed to messages that did not. Placement of an information anchor in the form of an objective news story before the organizational message increased the perceived organizational transparency when messages employed transparent design features and decreased the perceived organizational transparency when messages did not use these features. These results provide significant implications for practitioners attempting to convey organizational transparency at the tactical level through message features.     

Public transport and people with impairments – exploring non-use of public transport through the case of Oslo,Norway

abstract

Despite the attention given to universal design in recent years, many people with impairments still refrain from travelling on public transport. This explorative case study, conducted in the greater Oslo region in Norway, aims to add knowledge on why this is so. Findings indicate that insecurity while travelling and expectations of problems along the way are significant barriers. For many it is the sum of all challenges combined, from experience or anticipation that leads to non-use of public transport. The study shows that universal design policy, as of today, does not lead to accessible public transport systems that rendered impairments irrelevant. If society could safeguard the individuals’ travel needs, this might have profound societal repercussions through increased workforce participation and value added in society. Only then can society make the best use of all its inhabitants while championing inclusiveness and equality.     

Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations

Summary.  Structured additive regression models are perhaps the most commonly used class of models in statistical applications. It includes, among others, (generalized) linear models, (generalized) additive models, smoothing spline models, state space models, semiparametric regression, spatial and spatiotemporal models, log-Gaussian Cox processes and geostatistical and geoadditive models. We consider approximate Bayesian inference in a popular subset of structured additive regression models, latent Gaussian models , where the latent field is Gaussian, controlled by a few hyperparameters and with non-Gaussian response variables. The posterior marginals are not available in closed form owing to the non-Gaussian response variables. For such models, Markov chain Monte Carlo methods can be implemented, but they are not without problems, in terms of both convergence and computational time. In some practical applications, the extent of these problems is such that Markov chain Monte Carlo sampling is simply not an appropriate tool for routine analysis. We show that, by using an integrated nested Laplace approximation and its simplified version, we can directly compute very accurate approximations to the posterior marginals. The main benefit of these approximations is computational: where Markov chain Monte Carlo algorithms need hours or days to run, our approximations provide more precise estimates in seconds or minutes. Another advantage with our approach is its generality, which makes it possible to perform Bayesian analysis in an automatic, streamlined way, and to compute model comparison criteria and various predictive measures so that models can be compared and the model under study can be challenged.     

A simple two-stage design for quantitative responses with application to a study in diabetic neuropathic pain

Two-stage designs offer substantial advantages for early phase II studies. The interim analysis following the first stage allows the study to be stopped for futility, or more positively, it might lead to early progression to the trials needed for late phase II and phase III. If the study is to continue to its second stage, then there is an opportunity for a revision of the total sample size. Two-stage designs have been implemented widely in oncology studies in which there is a single treatment arm and patient responses are binary. In this paper the case of two-arm comparative studies in which responses are quantitative is considered. This setting is common in therapeutic areas other than oncology. It will be assumed that observations are normally distributed, but that there is some doubt concerning their standard deviation, motivating the need for sample size review. The work reported has been motivated by a study in diabetic neuropathic pain, and the development of the design for that trial is described in detail.     

Cumulative correspondence analysis of ordered categorical data from industrial experiments

Most studies of quality improvement deal with ordered categorical data from industrial experiments. Accounting for the ordering of such data plays an important role in effectively determining the optimal factor level of combination. This paper utilizes the correspondence analysis to develop a procedure to improve the ordered categorical response in a multifactor state system based on Taguchi's statistic. Users may find the proposed procedure in this paper to be attractive because we suggest a simple and also popular statistical tool for graphically identifying the really important factors and determining the levels to improve process quality. A case study for optimizing the polysilicon deposition process in a very large-scale integrated circuit is provided to demonstrate the effectiveness of the proposed procedure.     

Analysis of robust design experiments with time-dependent ordinal response characteristics: a quality improvement study from the horticulture industry

An approach to the analysis of time-dependent ordinal quality score data from robust design experiments is developed and applied to an experiment from commercial horticultural research, using concepts of product robustness and longevity that are familiar to analysts in engineering research. A two-stage analysis is used to develop models describing the effects of a number of experimental treatments on the rate of post-sales product quality decline. The first stage uses a polynomial function on a transformed scale to approximate the quality decline for an individual experimental unit using derived coefficients and the second stage uses a joint mean and dispersion model to investigate the effects of the experimental treatments on these derived coefficients. The approach, developed specifically for an application in horticulture, is exemplified with data from a trial testing ornamental plants that are subjected to a range of treatments during production and home-life. The results of the analysis show how a number of control and noise factors affect the rate of post-production quality decline. Although the model is used to analyse quality data from a trial on ornamental plants, the approach developed is expected to be more generally applicable to a wide range of other complex production systems.