政论语体中“使”字句的使用意图

句式的使用意图,都必须联系上下文语境去考察。“使”字句存在着条件、因果、目的和假设等多种不同的语义关系类型。各种不同语义关系的“使”字句的具体内容都能满足说话人不同的使用需求。使用条件关系的“使”字句,在意图上具有明显的一致性,使用目的和假设关系的“使”字句,有两种意图：有的是以句式的内容得出结论,有的则是把句式内容当作一种理由;而使用因果关系和可然（做法和作用）的“使”字句,其目的则是以句式本身的内容作为得出某种结论的理由或论据。     

Measuring Communication Styles in the Malaysian Workplace: Instrument Development and Validation

The aim of the present study is to access communication style in the Malaysian workplace through the development and validation of a communication scale appropriate to the Malaysian workplace. The analysis involved data from 200 state development employees, and construct and criterion-related validation using data from 510 employees, representing three organizations in Malaysia. The results provided support for the use of language (pekerti) and communication and interaction (bicara) as crucial communication dimensions for the Malaysian workplace, which are identified from the item-generation procedure.     

多元函数极值判别法推广

利用代数中的正定阵对多元函数的极值的判别法作一些推广     

动态语法教学资源的开发和运用

动态语法教学对提高学生理解语言和运用语言能力具有重要作用.为此,从动态语法教学资源的开发和利用着手,探讨动态语法教学的理论和实践,对走出语法教学的误区,开辟语法教学新路具有重要意义.     

Bayesian Analysis of Mixture Structural Equation Models With an Unknown Number of Components

Multivariate heterogenous data with latent variables are common in many fields such as biological, medical, behavioral, and social-psychological sciences. Mixture structural equation models are multivariate techniques used to examine heterogeneous interrelationships among latent variables. In the analysis of mixture models, determination of the number of mixture components is always an important and challenging issue. This article aims to develop a full Bayesian approach with the use of reversible jump Markov chain Monte Carlo method to analyze mixture structural equation models with an unknown number of components. The proposed procedure can simultaneously and efficiently select the number of mixture components and conduct parameter estimation. Simulation studies show the satisfactory empirical performance of the method. The proposed method is applied to study risk factors of osteoporotic fractures in older people.     

反生产行为管理策略研究:组织公正视角

通过对反生产行为控制策略文献的研究,以组织公正效果变量为基础,通过前人对组织公正的三维度、组织公正效果变量的三维度,结合反生产行为人际—组织二维度构建组织公正对反生产行为的影响机制,并依据该机制提出有效的管理策略和步骤。     

三元函数极值的探索

函数极值的存在性及判别方法是微分的重要应用之一.文章就三元函数给出了判别极值的存在的一个必要条件和充分条件.     

高等医学院校医学专业英语阅读测试内容效度实证分析

本文从内容效度的主要影响因素入手,基于近5年来某高等医学院校医学专业英语阅读测试试题为样本,以语篇输入视角,进行历时性研究与分析,客观评价某高等医学院校医学专业英语阅读测试的内容效度,提出相应建议,以期对提高医学专业英语测试水平有所裨益。     

Biology Teachers Designing Context-Based Lessons for Their Classroom Practice—The importance of rules-of-thumb

In science education in the Netherlands new, context‐based, curricula are being developed. As in any innovation, the outcome will largely depend on the teachers who design and implement lessons. Central to the study presented here is the idea that teachers, when designing lessons, use rules‐of‐thumb: notions of what a lesson should look like if certain classroom outcomes are to be reached. Our study aimed at (1) identifying the rules‐of‐thumb biology teachers use when designing context‐based lessons for their own classroom practice, and (2) assessing how these personal rules‐of‐thumb relate to formal innovative goals and lesson characteristics. Six biology teachers with varying backgrounds designed and implemented a lesson or series of lessons for their own practice, while thinking aloud. We interviewed the teachers and observed their lessons. Our results suggest that rules‐of‐thumb, which differed substantially among the teachers, indeed to a great extent guide the decisions teachers make when designing (innovative) lessons. These rules‐of‐thumb were often strongly associated with intended lesson outcomes. Also, teachers’ personal rules‐of‐thumb were more powerful in determining the lesson design than formal innovative goals and lesson characteristics. The results of this study encourage more research into how rules‐of‐thumb reflect teachers’ practical knowledge, for which suggestions are made.     

Fitting Nonlinear Latent Growth Curve Models With Individually Varying Time Points

Individual growth trajectories of psychological phenomena are often theorized to be nonlinear. Additionally, individuals’ measurement schedules might be unique. In a structural equation framework, latent growth curve model (LGM) applications typically have either (a) modeled nonlinearity assuming some degree of balance in measurement schedules, or (b) accommodated truly individually varying time points, assuming linear growth. This article describes how to fit 4 popular nonlinear LGMs (polynomial, shape-factor, piecewise, and structured latent curve) with truly individually varying time points, via a definition variable approach. The extension is straightforward for certain nonlinear LGMs (e.g., polynomial and structured latent curve) but in the case of shape-factor LGMs requires a reexpression of the model, and in the case of piecewise LGMs requires introduction of a general framework for imparting piecewise structure, along with tools for its automation. All 4 nonlinear LGMs with individually varying time scores are demonstrated using an empirical example on infant weight, and software syntax is provided. The discussion highlights some advantages of modeling nonlinear growth within structural equation versus multilevel frameworks, when time scores individually vary.