谈语文课堂提问的偏差及解决策略

课堂提问因突出了学生的主体地位而被教师广泛采用,但许多教师在运用课堂提问时都存在不少偏差。透视这些偏差并予以纠正,将有利于课堂教学积极作用的充分发挥。     

语文课堂提问偏差问题分析与有效性探究

课堂提问是突出学生学习主体地位的主要教学形式,但在实际教学过程中,教师在运用课堂提问时会出现偏差,影响了教学效果的提高.本文对语文课堂提问偏差的原因及表现进行了分析,对提高语文课堂提问有效性策略进行了深入探究.     

中学语文课堂引领艺术初探

<正>在中学语文教学实践中,教师对课堂引领的预设会遇到一些"意外",比如学生对问题理解的偏差、学生回答问题的指向偏颇、对问题的理解不够深刻、没有达到教师的预想等,那么如何对课堂提问进行"校正"和"突破"呢?对课堂引领的追问成为提高提问有效性、解决引领生成偏差的有效手段。一、中学语文课堂引领的有效性思考中学语文提高了课堂的思维含量,对学生的学习过程设置了更多的思考节点,教师的提问指向性更强,     

新课改下如何提高物理课堂提问的有效性

随着新课程改革的逐步深入,物理课堂提问的组织和形式都发生了很大的变化,教学实践过程中也出现了一些不足与偏差。以课堂提问的有效性来看,部分教师在物理课堂教学的提问过程中存在的     

分析数学提问偏差,构建和谐课堂氛围

课堂提问是教学的重要环节。教师恰当有效的提问能够激起学生思维的火花。然而,目前的教学提问中常在问题设置、提问对象、问题导向上出现偏差。对此,进行归因分析和探究纠偏策略,以期创造性地开展问题教学,营造教与学和谐的课堂氛围。     

设问有方,英语课堂教学有效性的依托

英语课堂"提问"是师生双方教与学活动的内容,要求师生在课堂上互相配合,互相促进。英语课堂"提问"教学存在一些偏差,本文主要分析目前高中英语课堂提问存在的一些问题,探究教师如何设问有方,从而提高英语课堂教学的有效性。     

分析数学提问偏差,构建和谐课堂氛围

课堂提问是教学的重要环节.教师恰当有效的提问能够激起学生思维的火花.然而,目前的教学提问中常在问题设置、提问对象、问题导向上出现偏差.对此,进行归因分析和探究纠偏策略,以期创造性地开展问题教学,营造教与学和谐的课堂氛围.     

初中英语教学克服提问失误的对策

<正>在新课程背景下,课堂提问仍然是初中英语课堂教学最常用的师生互动方式,但是,我们在随堂听课、日常行课中,不难发现不少教师的英语课堂提问仍然存在一些偏差或失误,需要加以克服,提高初中英语课堂提问质量。     

优质的提问,创造有效的历史教学

<正>教育心理学认为:学生的思维过程往往是从问题开始的。在课堂教学中,教师恰当的课堂提问,能够点燃学生思维的火花,调动其主体参与性,实现教学互动交流,最终达到解决问题的目的。因此,课堂提问被视为有效教学的核心。加强对课堂提问的诊断,会帮助教师检视并纠正教学存在的偏差,提高教学的有效性。本文冀图通过诊断教师自身的课堂提问行为,得出些许有助于促进有效历史教学的启示。     

中学教师课堂提问的社会学分析

教师课堂提问是师生互动的主要方式,可以从社会学视角进行分析。通过对初中和高中64节新授课的课堂观察记录,发现教师的课堂提问在学业成绩、学生职务、家庭背景、课堂座位、民族种族等五个方面产生着不公平现象,其原因包括教师对教学效果的追求、对个人利益的渴望和教学时的站位等。教师应建立纯洁的师生关系,运用多种技术消除教学中的社会偏差。     

A Two-Stage Approach to Missing Data: Theory and Application to Auxiliary Variables

A well-known ad-hoc approach to conducting structural equation modeling with missing data is to obtain a saturated maximum likelihood (ML) estimate of the population covariance matrix and then to use this estimate in the complete data ML fitting function to obtain parameter estimates. This 2-stage (TS) approach is appealing because it minimizes a familiar function while being only marginally less efficient than the full information ML (FIML) approach. Additional advantages of the TS approach include that it allows for easy incorporation of auxiliary variables and that it is more stable in smaller samples. The main disadvantage is that the standard errors and test statistics provided by the complete data routine will not be correct. Empirical approaches to finding the right corrections for the TS approach have failed to provide unequivocal solutions. In this article, correct standard errors and test statistics for the TS approach with missing completely at random and missing at random normally distributed data are developed and studied. The new TS approach performs well in all conditions, is only marginally less efficient than the FIML approach (and is sometimes more efficient), and has good coverage. Additionally, the residual-based TS statistic outperforms the FIML test statistic in smaller samples. The TS method is thus a viable alternative to FIML, especially in small samples, and its further study is encouraged.     

Alternative approaches to structural modeling of ordinal data: A Monte Carlo study

In practice, several measures of association are used when analyzing structural equation models with ordinal variables: ordinary Pearson correlations (PE approach), polychoric and polyserial correlations (PO approach), and conditional polychoric correlations (CPO approach). In the case of structural equation models without latent variables, the literature has shown that the PE approach is outperformed by the alternatives. In this article we report a Monte Carlo study showing the comparative performance of the aforementioned alternative approaches under deviations from their respective assumptions in the case of structural equation models with latent variables when attention is restricted to point estimates of model parameters. The CPO approach is shown to be the most robust against nonnormality. It is also robust to randomness of the exogenous variables, but not to the existence of measurement errors in them. The PO approach lacks robustness against nonnormality. The PE approach lacks robustness against transformation errors but otherwise it can perform about as well as the alternative approaches.     

Asymptotic Standard Errors for Item Response Theory True Score Equating of Polytomous Items

Building on previous works by Lord and Ogasawara for dichotomous items, this article proposes an approach to derive the asymptotic standard errors of item response theory true score equating involving polytomous items, for equivalent and nonequivalent groups of examinees. This analytical approach could be used in place of empirical methods like the bootstrap method, to obtain standard errors of equated scores. Formulas are introduced to obtain the derivatives for computing the asymptotic standard errors. The approach was validated using mean‐mean, mean‐sigma, random‐groups, or concurrent calibration equating of simulated samples, for tests modeled using the generalized partial credit model or the graded response model.     

A coding scheme for analysing problem-solving processes of first-year engineering students

This study describes the development and structure of a coding scheme for analysing solutions to well-structured problems in terms of cognitive processes and problem-solving deficiencies for first-year engineering students. A task analysis approach was used to assess students’ problem solutions using the hierarchical structure from a theoretical framework from mathematics research. The coding scheme comprises 54 codes within the categories of knowledge access, knowledge generation, self-management, conceptual errors, mechanical errors, management errors, approach strategies and solution accuracy, and was demonstrated to be both dependable and credible for analysing problems typical of topics in first-year engineering courses. The problem-solving processes were evaluated in terms of time, process elements, errors committed and self-corrected errors. Therefore, problem-solving performance can be analysed in terms of both accuracy and efficiency of processing, pinpointing areas meriting further study from a cognitive perspective, and for documenting processes for research purposes.     

Performance of the geometric approach to fault detection and isolation in SISO, MISO, SIMO and MIMO systems

In this paper,a geometric approach to fault detection and isolation (FDI) is applied to a Multiple-Input Multi-ple-Output (MIMO) model of a frame and the FDI results are compared to the ones obtained in the Single-Input Single-Output (SISO),Multiple-Input Single-Output (MISO),and Single-Input Multiple-Output (SIMO) cases. A proper distance function based on parameters obtained from parametric system identification method is used in the geometric approach. ARX (Auto Regressive with eXogenous input) and VARX (Vector ARX) models with 12 parameters are used in all of the above-mentioned models. The obtained results reveal that by increasing the number of inputs,the classification errors reduce,even in the case of applying only one of the inputs in the computations. Furthermore,increasing the number of measured outputs in the FDI scheme results in decreasing classification errors. Also,it is shown that by using probabilistic space in the distance function,fault diagnosis scheme has better performance in comparison with the deterministic one.     

中国比较文学现况分析

在比较学的研究方法中，影响研究引起的歧解最多，争议最大。本专门针对当前我国一些名学对影响研究的价值评判进行梳理，将他们对传统的法国学派及其所提倡的实证方法的态度分为四个门类，并且通过对这些迥异观点的透视，进而证明，在化与交流日益增强的时代，有必要对传统的影响研究进行重新思考与定位。     

三坐标测量机动态误差的分析和测量(英文)

对三坐标测量机动态误差的分析和计算方法进行讨论．为将线位移误差和转角误差联系起来,提出一种由转角误差得到测头线位移误差的方法,还用有限元法建立动态误差的模型．此外,用电感测微仪对动态转角误差进行了测量．     

A critique of the expectancy formula approach: Beating a dead horse?

The expectancy and severe discrepancy formulas, like those originally considered by the US. Office of Education (1976), provide the oldest but least defensible method of quantifying academic discrepancy. A logical and mathematical analysis reveals that all variations of this approach have several major weaknesses. First, the expectancy formulas themselves are predicated upon the very questionable assumption that achievement follows a straight line growth pattern, which raises questions about the accuracy of the resulting severe discrepancy values. Second, when discrepancy values are obtained by multiplying the expected values by a fractional constant, the approach is necessarily biased in the direction of applying a more stringent underachievement criterion for older and brighter children. Third, the formulas employ a grade equivalent scale that results in inconsistencies, one being that fewer arithmetic problems are identified. Finally, the expectancy approach does not consider errors in measurement or regression effects, and consequently produces serious identification errors. A variation of the expectancy approach involving a discrepancy ratio between obtained and expected achievement has the previously mentioned limitations, except the bias, and it produces scores that cannot be easily interpreted.     

Concept-referenced testing

It is suggested that for criterion-referenced tests to have any educational value, they must be linked to the categories of learning that have been demonstrated in learning theory. These categories form the basis of the test domains. The nature of the two main categories, concepts and rules, is reviewed and it is suggested that the errors produced by pupils that indicate faulty concept learning or rules application should form the basis for the production of tests. Examples of such tests are also discussed. As this approach to testing is markedly different to the current psychometric approach to criterion-referenced testing it is suggested that the form of testing described here be calledconcept-referenced testing to distinguish it from other forms of criterion-referenced measures.     

Not quite normal: Consequences of violating the assumption of normality in regression mixture models

Regression mixture models are a new approach for finding differential effects which have only recently begun to be used in applied research. This approach comes at the cost of the assumption that error terms are normally distributed within classes. The current study uses Monte Carlo simulations to explore the effects of relatively minor violations of this assumption, the use of an ordered polytomous outcome is then examined as an alternative which makes somewhat weaker assumptions, and finally both approaches are demonstrated with an applied example looking at differences in the effects of family management on the highly skewed outcome of drug use. Results show that violating the assumption of normal errors results in systematic bias in both latent class enumeration and parameter estimates. Additional classes which reflect violations of distributional assumptions are found. Under some conditions it is possible to come to conclusions that are consistent with the effects in the population, but when errors are skewed in both classes the results typically no longer reflect even the pattern of effects in the population. The polytomous regression model performs better under all scenarios examined and comes to reasonable results with the highly skewed outcome in the applied example. We recommend that careful evaluation of model sensitivity to distributional assumptions be the norm when conducting regression mixture models.