美国早期学习标准中音乐与动作部分的内容分析与启示

美国早期学习标准（以下简称《标准》）是世界范围早期教育行业专业化的典范，通过对美国艺术领域《标准》中音乐和动作部分的内容分析，可概括出早期儿童音乐与动作部分的主要指标与内容，包括：参与和探索多种音乐活动、音乐与动作活动中的回应、通过音乐与动作进行创造性表现和情感表达、理解和欣赏音乐与舞蹈四大分析类目。美国《标准》中对各种乐器探索的关注、对参与歌唱活动而非唱准音调的强调、对舞蹈和创造性动作方面指标的突出、对幼儿回应音乐元素过程的重视，为我国日后艺术领域课程标准的修订提供了一定的启示。     

Facilitation and Dialogue as Methods of Reflective Practice in Professional Education

Students may fear sharing their learning in public because classrooms are not traditional places where we teach skills needed for mutual understanding, such as facilitation and dialogue. This is a pedagogical challenge for planning, policy, and design fields because contemporary teaching requires collaboration among participants. We propose that learning to work collaboratively in the classroom has broader relevance for practice because it mirrors the learning that happens in organizations. To address this opportunity, we trained students in facilitation and dialogue. In this article, we discuss the design, implementation, and outcomes of this intervention.     

终身教育下成人教育转型动力研究

终身教育与学习型社会是当今时代对教育事业的两个基本要求，成人教育作为二者实施与构建的主体实现方式地位突出。“学习、开放、多元、终身、全民”型结构是成人教育转型之道，让学习成为一种习惯，成为引领成人教育转型动力，以适应终身教育有序发展。     

Toward Probabilistic Prediction of Flash Flood Human Impacts

This article focuses on conceptual and methodological developments allowing the integration of physical and social dynamics leading to model forecasts of circumstance‐specific human losses during a flash flood. To reach this objective, a random forest classifier is applied to assess the likelihood of fatality occurrence for a given circumstance as a function of representative indicators. Here, vehicle‐related circumstance is chosen as the literature indicates that most fatalities from flash flooding fall in this category. A database of flash flood events, with and without human losses from 2001 to 2011 in the United States, is supplemented with other variables describing the storm event, the spatial distribution of the sensitive characteristics of the exposed population, and built environment at the county level. The catastrophic flash floods of May 2015 in the states of Texas and Oklahoma are used as a case study to map the dynamics of the estimated probabilistic human risk on a daily scale. The results indicate the importance of time‐ and space‐dependent human vulnerability and risk assessment for short‐fuse flood events. The need for more systematic human impact data collection is also highlighted to advance impact‐based predictive models for flash flood casualties using machine‐learning approaches in the future.     

Response-adaptive trial designs with accelerated Thompson sampling

In a clinical trial, sometimes it is desirable to allocate as many patients as possible to the best treatment, in particular, when a trial for a rare disease may contain a considerable portion of the whole target population. The Gittins index rule is a powerful tool for sequentially allocating patients to the best treatment based on the responses of patients already treated. However, its application in clinical trials is limited due to technical complexity and lack of randomness. Thompson sampling is an appealing approach, since it makes a compromise between optimal treatment allocation and randomness with some desirable optimal properties in the machine learning context. However, in clinical trial settings, multiple simulation studies have shown disappointing results with Thompson samplers. We consider how to improve short-run performance of Thompson sampling and propose a novel acceleration approach. This approach can also be applied to situations when patients can only be allocated by batch and is very easy to implement without using complex algorithms. A simulation study showed that this approach could improve the performance of Thompson sampling in terms of average total response rate. An application to a redesign of a preference trial to maximize patient's satisfaction is also presented.     

基于利他偏好的学习模型及其实验研究

利他行为一直伴随着人类的历史,同时企业的成长过程也是一个不断学习的过程,因此建立基于利他偏好的学习博弈模型更加符合企业的需要,然而目前尚未见此研究.考虑了利他偏好之后,用效用函数取代直接收益,建立了改进的EWA学习模型,确定各参数的取值方法,给出了初始魅力值计算公式.设计了二级供应链情景下的实验,通过实验获得了数据.采用Matlab软件统计分析后发现:与基本EWA模型相比,考虑了利他偏好之后,实验者的策略选择更快地收敛,说明考虑利他偏好后EWA学习模型的学习效果更好.另外,社会距离越小,实验者的策略选择也越快地收敛,说明社会距离对策略的选择有显著影响,企业应该注重培养战略伙伴关系,降低社会距离,形成长期的合作关系.     

Propensity score prediction for electronic healthcare databases using super learner and high-dimensional propensity score methods

ABSTRACT

The optimal learner for prediction modeling varies depending on the underlying data-generating distribution. Super Learner (SL) is a generic ensemble learning algorithm that uses cross-validation to select among a ‘library’ of candidate prediction models. While SL has been widely studied in a number of settings, it has not been thoroughly evaluated in large electronic healthcare databases that are common in pharmacoepidemiology and comparative effectiveness research. In this study, we applied and evaluated the performance of SL in its ability to predict the propensity score (PS), the conditional probability of treatment assignment given baseline covariates, using three electronic healthcare databases. We considered a library of algorithms that consisted of both nonparametric and parametric models. We also proposed a novel strategy for prediction modeling that combines SL with the high-dimensional propensity score (hdPS) variable selection algorithm. Predictive performance was assessed using three metrics: the negative log-likelihood, area under the curve (AUC), and time complexity. Results showed that the best individual algorithm, in terms of predictive performance, varied across datasets. The SL was able to adapt to the given dataset and optimize predictive performance relative to any individual learner. Combining the SL with the hdPS was the most consistent prediction method and may be promising for PS estimation and prediction modeling in electronic healthcare databases.     

儿童社会情绪学习：Strong Kids系列课程介绍及启示

Strong Kids系列课程是儿童社会情绪学习的经典课程之一，包括5个相对独立的版本，具有扎实的理论基础，是一项方便、经济且见效快的短期预防干预项目，能有效地预防和减少儿童的情绪行为障碍，提升儿童的社会情绪能力。该课程的设计、内容及形式等都值得为他人所借鉴。为此，笔者通过对Strong Kids系列课程的理论基础、主要内容及应用的阐述，探讨该课程的优势及对我国儿童社会情绪学习课程开发与实施的启示。     

Mapuche education and situated learning in a community school in Chile

The article analyses the Mapuche language and culture teaching practices of a rural school in the Chilean Araucanía region run by Mapuche teachers, aimed at reinforcing the language, culture and identity of children. Based on a comparative study of two school ethnographies, the article shows and discusses the ways children learn to be Mapuche by participating of social and communitarian practices reproduced in school. While teaching of traditional core subjects is conducted in standard ways, Mapuche language and culture are taught through the recreation of modes of living, producing and reproducing indigenous traditional knowledge that normally occur in family and community. The maintenance of this ‘bicultural pedagogy’ is grounded on an epistemological claim on the indivisibility of contents from its forms of transmission.