Causal Models and Experimentation Strategies in Scientific Reasoning

This study explores how novices' conceptions about electric circuits affected their self-directed experimentation in a computer-based circuit laboratory. The participants, 22 undergraduates with no formal college instruction in physics, worked individually on an initial problem to assess their conceptual models of circuits and in subsequent sessions on open-ended experimentation with the computer laboratory, attempted to rediscover the laws of electric circuits. Analysis of the initial problem identified four conceptual models in students' solutions. Lower level models were local, piecemeal, and represented the surface features of the materials, whereas higher level models were progressively more cohesive, integrated, and principled. Relations were found between students' causal models and their learning gains in the computer laboratory. Good and poor learners with the laboratory were identified; these groups showed strategic differences in goal-directed planning, generating and interpreting evidence, and managing data. In general, sophisticated models in the initial problem were related to sophisticated reasoning in the computer discovery task. It is suggested that research oriented to the improvement of science learning should attend to interactive relationships between prior conceptions, inference strategies, and the structure of domain-specific knowledge.     

The Specification of Causal Models with Tetrad IV: A Review

Tetrad IV is a program designed for the specification of causal models. It is specifically designed to search for causal relations, but also offers the possibility to estimate the parameters of a structural equation model. It offers a remarkable graphical user interface, which facilitates building, evaluating, and searching for causal models. The search algorithms make it possible to find alternatives for existing models, as well as to find new models when a theoretical directive is lacking. This is illustrated by the detection of a causal model for longitudinal data, which is a viable alternative for a latent growth model.     

教育政策定量评估方法中的因果推断模型以及混合方法的启示

本文从概述的角度介绍了国际上主流的评估教育政策的定量方法——因果推断模型.因果推断模型是借鉴自然科学中实验的理念而演化出来的一整套定量研究方法,包括随机试验、自然实验、断点回归模型、倾向分数配对法等.这些方法主要是为了解决教育领域中的自选择偏误.基于对因果推断模型的介绍,本文总结了定量研究方法的复杂性和局限性,并探讨了混合方法在教育政策评估中的潜在优势.     

Supporting and Developing Teachers through Telecommunications

Abstract

This article looks at how knowledge can be accessed using current technologies, so that forms of alternative delivery can be made available. It examines the effect of establishing links between schools and the university producing ‘virtual institutions’, and looks to the future.     

Structural Equations and Causal Explanations: Some Challenges for Causal SEM

One common application of structural equation modeling (SEM) involves expressing and empirically investigating causal explanations. Nonetheless, several aspects of causal explanation that have an impact on behavioral science methodology remain poorly understood. It remains unclear whether applications of SEM should attempt to provide complete explanations or partial explanations. Moreover, it remains unclear what sorts of things researchers can best take as causes and effects. Finally, the meaning of causal assertions itself remains poorly understood. Attempting to clarify the use of structural equations as causal explanations by addressing these issues has implications for behavioral science methodology because applications of SEM typically remain vague about causation and thus about their substantive conclusions. Research aimed at clarifying these issues can lead to a sharper and more refined use of SEM for causal explanation, and by extension, clarify behavioral science methodology more generally.     

When collaborative is not collaborative: Supporting student learning through self-surveillance

Collaborative learning has been widely endorsed in education. This qualitative research examines instances of collaborative learning during mathematics that were seen to be predominantly non-collaborative despite the pedagogical efforts and intentions of the teacher and the task. In an effort to disrupt the non-collaborative learning, small groups of eighth grade students engaged in self-surveillance where they viewed video data of their group's collaborations and then reflected collectively on their observations. A key finding from this research is that self-surveillance disrupted students’ normalized patterns of collaborative learning creating greater opportunities for individual student learning and participation. Implications for student learning and pedagogy will be discussed.     

Productive engagements with student difference: Supporting equity through cultural recognition

In this paper, the focus is on how a group of Australian educators support student equity through cultural recognition. Young's theorising of justice is drawn on to illuminate the problematic impacts arising from the group's efforts to value students’ cultural difference associated, for example, with quantifying justice along distributive lines and with essentialising student difference as negation and lack within a frame of cultural imperialism. These theoretical tools draw attention to, and support a critical examination of, the social rules and relations within the school that create barriers to equity. Towards reconciling discrepancies relating to how student difference might best be supported, the paper endorses the prevailing imperative of centring students’ perspectives and experiences. Such centring remains crucial to educators recognising the partiality and interest within their attempts to ‘help’ marginalised students and disrupting the relations of teacher privilege and authority that reinscribe domination, control and exclusion.     

The Impact of Sample Size and Other Factors When Estimating Multilevel Logistic Models

The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying methods of estimation, level-1 and level-2 sample size, outcome prevalence, variance component sizes, and number of predictors using SAS software. Mean estimates of statistical power were influenced primarily by sample sizes at both levels. In addition, confidence interval coverage and width and the likelihood of nonpositive definite random effect covariance matrices were impacted by variance component size and estimation method. The interactions of these and other factors with various model performance outcomes are explored.     

从远程教育系统看我国技术社会化过程的路线、体制与模式

本文以我国远程教育系统的初期解决方案为主要例证,尝试提出目前我国技术社会化过程中的现象要素,在此基础上进一步尝试提出技术社会化的路线预测和模式设计,尤其是新技术在教育领域内的应用,并希望从体制和模式上探讨改进的方案.     

History and Philosophy of Science through Models: The Case of Chemical Kinetics

The case for a greater role for the history and philosophy of science in science education is reviewed. It is argued that such a role can only be realised if it is based on both a credible analytical approach to the history and philosophy of science and if the evolution of a sufficient number of major themes in science is known in suitable detail. Adopting Lakatos' Theory of Scientific Research Programmes as the analytical approach, it is proposed that the development, use, and replacement, of specific models forms the core of such programmes.Chemical kinetics was selected as an exemplar major topic in chemistry. Eight models which have played a central role in the evolution of the study of chemical kinetics were identified by an analysis of the literature. The implications that these models have for the teaching and learning of chemistry today are discussed.     

Building a space to dream: Supporting indigenous children's survivance through community-engaged social and emotional learning

Indigenous communities practice survivance and challenge social and political systems to support their children's identity and well-being. Grounded in transformative social-emotional learning (SEL) and tribal critical race theory, this 3-year community-based participatory research study (2019–2021) examined how a SEL program co-created with an Indigenous community in Flathead Nation in Montana supports anti-racism and anti-colonialism among Indigenous children. Critical reflexivity and thematic analyses of Community Advisory Board meetings and journals written by 60 students (M_age = 10.3, SD = 1.45; 47% girls; 60% Native American) during the SEL program revealed themes on Indigenous identity, belonging, wellness, and colonialism. These results shed light on challenging the racist and colonial roots of education to support Indigenous children's survivance and social-emotional well-being.