Fit of Different Models for Multitrait-Multimethod Experiments

In the past, several models have been developed for the estimation of the reliability and validity of measurement instruments from multitrait-multimethod (MTMM) experiments. Suggestions have been made for additive, multiplicative and correlated uniqueness models, whereas recently Coenders and Saris (2000) suggested a procedure to test these models against one another. In this article, the different models suggested for the analysis of MTMM matrixes have been compared for their fit to 87 data sets collected in the United States (Andrews, 1984; Rodgers, Andrews, & Herzog, 1992), Austria (Koltringer, 1995), and the Netherlands (Scherpenzeel & Saris, 1997). As most variables are categorical, the analysis has been carried out on the basis of polychoric-polyserial correlation coefficients and of Pearson correlations. The fit of the models based on polychoric correlations is much worse than the fit of models based on product moment correlations, but in both cases a model that assumes additive method effects fits most data sets better than the other models, including the so-called multiplicative models.     

On the Estimation of Nonlinear Mixed-Effects Models and Latent Curve Models for Longitudinal Data

Nonlinear models are effective tools for the analysis of longitudinal data. These models provide a flexible means for describing data that follow complex forms of change. Exponential and logistic functions that include a parameter to represent an asymptote, for instance, are useful for describing responses that tend to level off with time. There are forms of nonlinear latent curve models and nonlinear mixed-effects model that are equivalent, and so given the same set of data, growth function, distributional assumptions, and method of estimation, the 2 models yield equivalent results. There are also forms that are strikingly different and can yield different interpretations for a given set of data. This article discusses cases in which nonlinear mixed-effects models and nonlinear latent curve models are equivalent and those in which they are different and clarifies the estimation needs of the different models. Examples based on empirical data help to illustrate these points.     

Computer-Supported Collaborative Inquiry on Buoyancy: A Discourse Analysis Supporting the “Pieces” Position on Conceptual Change

This article describes in detail a conversation analysis of conceptual change in a computer-supported collaborative learning environment. Conceptual change is an essential learning process in science education that has yet to be fully understood. While many models and theories have been developed over the last three decades, empirical data to support them are scarce. The present paper aims to provide such evidence. To this end, the article first reviews seven proposed models of conceptual change before it recalls the main ideas behind the two different positions on conceptual change, the pieces (diSessa 2008) versus coherence (Vosniadou et al. 2008) positions. Then, the article presents and discusses how a close discourse analysis of asynchronous collaborative conversations between grade 5 and 6 students on buoyancy and relative density provides further empirical evidence of the knowledge in pieces position.     

Another Perspective on Assessing the Significance of Information Technology in Education

Summary

The significance of information technology in education is usually assessed or evaluated on terms of some measures of effectiveness. In different school settings the effectiveness is operationalized in different ways, and in the literature various methods of determining the effectiveness have been discussed (e.g., Secretary's Conference on Educational Technology 1999). In this article, models for assessing the significance of information technology in education based on the teachers' subjective perspective are introduced. Theoretical backgrounds of the models are based on methods developed in information management science to assess the impact of information technology (IT) in industry and business. The first model is comprised of categorizing the rationales for using IT in education, the second model assesses the strategic impact of existing IT applications on one hand and of future IT applications on the other on education, and the third model assesses the roles of applications of IT in teaching. Also, the empirical findings of a small scale test of the two latter models in the Teacher Training School in Rauma (TTSR), a primary school in Finland with about 260 pupils and 19 teachers, are introduced.     

Detecting Unobserved Heterogeneity in Latent Growth Curve Models

Growth mixture models combine latent growth curve models and finite mixture models to examine the existence of latent classes that follow distinct developmental patterns. Analyses based on these models are becoming quite common in social and behavioral science research because of recent advances in computing, the availability of specialized statistical programs, and the ease of programming. In this article, we show how mixture models can be fit to examine the presence of multiple latent classes by algorithmically grouping or clustering individuals who follow the same estimated growth trajectory based on an evaluation of individual case residuals. The approach is illustrated using empirical longitudinal data along with an easy to use computerized implementation.     

Leading Educational Change: reflections on the practice of instructional and transformational leadership

Over the past two decades, debate over the most suitable leadership role for principals has been dominated by two conceptual models: instructional leadership and transformational leadership. This article reviews the conceptual and empirical development of these two leadership models. The author concludes that the suitability or effectiveness of a particular leadership model is linked to factors in the external environment and the local context of a school. Moreover, the paper argues that the definitions of the two models are also evolving in response to the changing needs of schools in the context of global educational reforms.     

Models of Self-regulated Learning: A review

Questions connected with the regulation of one's own cognitive processes attract increasing numbers of researchers in psychology, as evidenced by the several different models of self-regulation that have been developed over the past two decades. The aim of this article was to present and compare the latest models of self-regulated learning (SRL), including those by Boekaerts, Borkowski, Pintrich, Winne and Zimmerman. The models were compared on four criteria (i.e. background theories, definitions of SRL, components included in the models and empirical work). The results show that theoretical background is an important differentiating feature. The two models that resembled each other more than any other two models (i.e. Pintrich and Zimmerman) were inspired by the same background theory (i.e. social cognitive theory). On the other hand, the models that differed most from the other models (i.e. Borkowski and Winne) were also theoretically the farthest removed ones.     

儿童入学问题研究中的性别视角——理论模型及发展中国家的经验

从经济学角度来看,基础教育阶段的儿童入学是一种典型的家庭决策行为。对此,经济学家发展了两个理论模型———新古典家庭决策模型和讨价还价家庭模型,并把性别因素考虑进模型中。这两个模型对儿童入学中的性别差异提供了不同解释,并且,许多经济学家利用这两个家庭模型对发展中国家的儿童入学问题做了广泛的实证研究。     

The practice of multimodal consultation: An integrating approach for consultation service delivery

Multimodal consultation provides a problem-solving approach that recognizes and analyzes the components of multifaceted, multisubsystem referral problems. The approach, which is exemplified in the present article within the ecological perspective, consists of five parts: from the identification and analysis of maladaptive interactions that cause, support, or maintain a referral problem's environment to the evaluation of consultation interventions that target different aspects of the referral environment and are based on different consultation models. Multimodal consultation is primarily a conceptual model at this time; however, suggestions for empirical and heuristic research also are discussed.     

The Best of Both Worlds: Factor Analysis of Dichotomous Data Using Item Response Theory and Structural Equation Modeling

Both structural equation modeling (SEM) and item response theory (IRT) can be used for factor analysis of dichotomous item responses. In this case, the measurement models of both approaches are formally equivalent. They were refined within and across different disciplines, and make complementary contributions to central measurement problems encountered in almost all empirical social science research fields. In this article (a) fundamental formal similiarities between IRT and SEM models are pointed out. It will be demonstrated how both types of models can be used in combination to analyze (b) the dimensional structure and (c) the measurement invariance of survey item responses. All analyses are conducted with Mplus, which allows an integrated application of both approaches in a unified, general latent variable modeling framework. The aim is to promote a diffusion of useful measurement techniques and skills from different disciplines into empirical social research.     

Standardized Parameters in Misspecified Structural Equation Models: Empirical Performance in Point Estimates,Standard Errors,and Confidence Intervals

In practice, models always have misfit, and it is not well known in what situations methods that provide point estimates, standard errors (SEs), or confidence intervals (CIs) of standardized structural equation modeling (SEM) parameters are trustworthy. In this article we carried out simulations to evaluate the empirical performance of currently available methods. We studied maximum likelihood point estimates, as well as SE estimators based on the delta method, nonparametric bootstrap (NP-B), and semiparametric bootstrap (SP-B). For CIs we studied Wald CI based on delta, and percentile and BC_a intervals based on NP-B and SP-B. We conducted simulation studies using both confirmatory factor analysis and SEM models. Depending on (a) whether point estimate, SE, or CI is of interest; (b) amount of model misfit; (c) sample size; and (d) model complexity, different methods can be the one that renders best performance. Based on the simulation results, we discuss how to choose proper methods in practice.     

最低工资制度对就业的影响:文献综述

文章从国内外关于最低工资制度对就业影响这一问题的争论出发,对相关研究成果和研究方法进行了梳理。在这一问题上,目前国内外学者大致有2种不同的观点:一部分学者和研究结论支持标准理论的负就业效应;而另一部分学者和研究结论则支持非负就业效应。之所以产生分歧,是由于计量工具、计量模型、以及数据的差异。目前国内学者的研究则大多只是停留在理论层面上的讨论,实证研究相当有限。     

Steering Dynamics in Complex Education Systems. An Agenda for Empirical Research

Many policy systems and education systems have grown more complex in the last three decades. Power has moved away from central governments in different directions: upwards towards international organisations, sideways towards private institutions and non‐governmental organisations and downwards towards local governments and public enterprises such as schools. Where once we had central government, we now have governance, which can be defined as the processes of establishing priorities, formulating and implementing policies, and being accountable in complex networks with many different actors. Steering in such complex education systems emerges from the activities, tasks and responsibilities of state and non‐state actors, operating at different levels and from different positions and often has un‐deliberate, un‐intentional and un‐foreseen consequences. There are many conceptual models that encapsulate this complexity, but this article suggests that there is a real need for empirical research. Without empirical research it remains unknown whether and how steering in complex networks works out in practice, what are its effects and for whom. Moreover, it is only through empirical research that we can find out whether central government has become less dominant, or rather whether its appearance has changed and it has become less visible, but not necessarily less influential. Foucault's governmentality perspective is a useful notion on which to build such a framework for empirical research which allows for a careful study of the interactions that signify steering. Inspired by Foucault, this article develops a trilogy of assumed conditions for steering to take effect in modern societies. Following this reasoning, ‘something' first needs to be made thinkable, calculable and practicable by different actors for steering to occur. This trilogy is a promising starting point for empirical research into very specific phenomena which can help us to understand how steering in complex education systems works.     

中国旅游贷款发展影响因素的实证研究

中国旅游贷款的发展相当缓慢,理论界对此现象给出了多种原因解释,但这些解释都缺乏实证性研究。文章在广泛调查的基础上,使用Logistic回归模型,确定了各不同因素对民众接受旅游贷款的可以量化的影响。并在实证分析的基础上得出结论,认为民众的意识还是影响我国民众接受旅游贷款积极性的一个最重要因素。     

Neurological basis of language and reading

The central theme of this article is that contemporary neuroanatomical-neurolinguistic models which conceptualize language and reading as multidimensional, interactive functional systems are more able than earlier localizationist viewpoints to contribute to our understanding of individual differences. After providing a theoretical rationale for this position based on Luria (1973,1980), three modern neuroanatomical-neuroloinguistic models, derived from the extensive case study literature of adult asphasia, alexia, and acquired dyslexia, are discussed. Specifically, the Geschwind-Dejerine model of reading which stresses involvement of classical perisylvian structures in the left hemisphere, Bastian's (1898) competing model which postulates more bihemispheric involvement in reading, and a neurolinguistic model to account for the different ways surface, phonological, and deep dyslexics access meaning, are critically evaluated in terms of their empirical validation, utility, and limitations for understanding individual differences. Finally, suggestions for future research are offered.     

School Level Conditions Affecting the Effectiveness of Instruction

In this article, the current status of school level factors, as they appear in research reviews and in school effectiveness models is criticised both from a theoretical and from an empirical perspective. School level factors are often related to student achievement without taking into account the classroom level, where teaching and learning primarily take place. As a theoretical alternative, an overview of school level factors that enhance the quality of instruction, time for learning and opportunity to learn at the classroom level is provided. These factors are supposed to contribute to the explanation of differences in student achievement. Some empirical support for these ideas is found in educational research studies that have made use of three‐level analyses.     

Quantifying Error in Survey Measures of School and Classroom Environments

Developing indicators that reflect important aspects of school and classroom environments has become central in a nationwide effort to develop comprehensive programs that measure teacher quality and effectiveness. Formulating teacher evaluation policy necessitates accurate and reliable methods for measuring these environmental variables. This article investigates different approaches to quantify measurement error in school- and classroom-level indicators constructed from survey data collected at a lower level of aggregation (i.e., teachers or students). Within a generalizability theory framework the article first compares four widely used approaches for accounting for measurement error in school- and classroom-level aggregate indicators. Then, it uses two empirical examples to demonstrate how each of these approaches can lead to different conclusions about the precision of aggregate indicators, and can influence inferences about the relationships between environmental variables and policy-relevant outcomes. Finally, the article discusses the degree to which these commonly used models accurately represent the structure of the data found in common survey administration scenarios.     

Governmental policies and organisational change in higher education

In this article a theoretical framework designed for a comparative research project on organisational change in higher education is presented. In the project the main focus is on how organisational change in universities and colleges is affected by governmental policies and programmes. The framework is based upon two major theoretical perspectives, resource dependency and neo-institutionalism. It is argued that for examining changes in universities and colleges both the relationship between these organisations and the government, as well as their internal dynamics are of importance. In addition to integrating the two main theoretical perspectives in the project also attempts to do justice to the complexities of the concept of (governmental) steering by attempting to incorporate general models on the role of the state. The article suggests that these models offer a meaningful insight into how and why governmental steering approaches have been changed over time.