多元智能理论视野下的英语合作学习模式探究

霍华德.加德纳教授的多元智能理论(MI理论)对智能进行了全新的诠释,他认为每个人身上都有8种独立的智能,这些智能之间独特的组合方式构成了人与人之间的差异。目前,人们越来越关注MI理论对教育的促进作用,合作学习是MI理论原则应用于教育领域的一种方式,英语听说课的研究实验表明:以MI理论为指导的合作学习模式有利于学生英语听、说能力的提高,学生之间的个体差异性缩小,学生的学习兴趣和自信心增强。     

基于精准扶贫的安徽省乡村旅游驱动力分析

[目的]文章选取主成分分析法,首次对安徽省的精准扶贫的乡村旅游的驱动力进行分析,以期对安徽省旅游扶贫工作提供借鉴与指导。[方法]选择主成分分析法(principal component analysis,PCA)和多元线性回归方程,结合SPSS22.0对安徽省基于精准扶贫的乡村旅游驱动力以及影响因子进行分析。[结果]基于精准扶贫的安徽省乡村旅游的主要驱动力是经济驱动、城市环境驱动和健康卫生驱动。其中空气可吸入颗粒年均值对于安徽省精准扶贫的乡村旅游呈负向驱动,乡村饮用水水质达标率、农村卫生厕所普及率、农村居民恩格尔系数、乡村旅游扶贫政策性文件发布数量呈正向驱动,这几个因素是安徽省乡村旅游的主要驱动因子。[结论]今后安徽省基于扶贫的乡村旅游要注重乡村环境的维护、卫生质量的提升、设施设备的完善以及督促各地区政府对发展乡村旅游引起高度重视为入手点,着重提升乡村空气质量、饮用水水质达标率、卫生厕所普及率以及相关政策数量等,以促进乡村旅游在精准扶贫中的成效和带动作用。     

资源型城市居民改善空气质量的支付意愿——以山西太原为例

研究资源型城市居民对空气质量改善的支付意愿及影响因素,有利于进一步推动各地区实行减污降碳。基于山西太原443份调研问卷,利用条件价值评估法测算居民的支付意愿及支付额度,构建二元Logistic回归模型和Tobit模型对支付意愿及支付额度的影响因素进行分析。发现79.2%的受访者具有正的支付意愿,平均支付意愿为28.16元/(月·人),其中受教育程度、家庭总收入、是否患有呼吸系统疾病、本地居住时长、是否关注空气质量以及空气质量对健康危害程度具有显著的正向影响,而性别、年龄、职业、居住位置、对空气质量的现状满意度以及对政府采取措施的满意度影响不显著。为此,应加强环保宣传教育,合理制定支付标准,制定相应的实施政策,以引导居民支付空气质量改善的费用。     

公司管理层讨论与分析信息披露的影响因素--基于深沪223家上市公司经验证据的探讨

我国对管理层讨论与分析（MD＆A）不仅理论研究较少，而且实践上也无法对其进行有效的监控，导致目前上市公司对MD＆A信息的披露极不规范，影响到了资本市场的发展。根据对223家深沪上市公司的分析，我国年报中MD＆A信息披露程度较低；虽然资本的竞争性正促使我国公司进行更多的MD＆A信息披露，但仍存在一些阻碍因素；我国公司MD＆A信息披露与高管激励显著相关。     

城建投资公司会计问题的成因透析及对策

近年来,我国城市基础设施建设领域存在着许多问题,究其根源在于城建投融资体制的滞后,投融资平台的不健全.从会计角度分析城建投资公司存在的问题及其成因,应从统一会计制度与科目、建立城建投资公司现代企业制度以及实现多元化投资主体三个方面进行政策改进.     

WAGNER'S LAW: AN ECONOMETRIC TEST FOR SOUTH AFRICA, 1960‐2006

The main objective for this paper is to test Wagner's law by analysing the causal relationships between real government expenditure and real income for South Africa for the period 1960‐2006. The paper tests the long‐run relationship between the two variables using the autoregressive distributive lag approach to cointegration suggested by Pesaran et al. We use the Granger non‐causality test procedure developed by Toda and Yamamoto, which uses a vector autoregression model to test for the causal link between the two. Evidence of cointegration is sufficient to establish a long‐run relationship between government expenditure and income. However, support for Wagner's law would require unidirectional causality from income to government expenditure. Therefore, cointegration should be seen as a necessary condition for Wagner's law, but not sufficient. This research does find a long‐run relationship between real per capita government expenditure and real per capita income. Results for the short‐run causality find bidirectional causality. On the basis of empirical results in this paper, one may tentatively conclude that Wagner's law finds no support in South Africa.     

Analysis of multiple response in marketing research: Estimating the degree of association

Researchers often are forced to analyze nominally-scaled multiple response questions for which respondents have provided more than one response. A Multiple Index of Predictive Association (MIPA) is derived for estimating the effect of the independent variable on the dependent variable when one or both variables have multiple responses. MIPA is illustrated using demographic and preference data. The relevance of the Multiple Index of Predictive Association to marketing and its implications are discussed.     

Enhancing a Delphi study on family-focused prevention

This article discusses how additional inquiries can enhance Delphi findings. We argue that inquiries aimed at supporting and refining Delphi findings is both theoretically and practically meaningful. We illustrate our argument on the basis of a framework for family-focused prevention that was developed through a Delphi study. The results of individual and group interviews conducted as a follow-up to the implementation of the framework provided us with effective ways to support and refine it. We draw the conclusion that adequate follow-up inquiries can enhance Delphi findings, from theoretical and application perspectives.     

Proper and Improper Multiple Imputation

Multiple imputation has become viewed as a general solution to missing data problems in statistics. However, in order to lead to consistent asymptotically normal estimators, correct variance estimators and valid tests, the imputations must be proper . So far it seems that only Bayesian multiple imputation, i.e. using a Bayesian predictive distribution to generate the imputations, or approximately Bayesian multiple imputations has been shown to lead to proper imputations in some settings. In this paper, we shall see that Bayesian multiple imputation does not generally lead to proper multiple imputations. Furthermore, it will be argued that for general statistical use, Bayesian multiple imputation is inefficient even when it is proper.