Domain-General and Domain-Specific Scientific Thinking in Childhood: Measurement and Educational Interplay
01 Jan 2017-
TL;DR: Zusammenfassung et al. as mentioned in this paper discussed psychometric issues in Research on Scientific Reasoning and proposed a methodological approach to find the root cause of such issues.
Abstract: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I Zusammenfassung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III 1 General Introduction 1 1.1 History of Research on Scientific Thinking . . . . . . . . . . . . . . . . . . . . . . 4 1.2 The Present Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1.3 Methodological Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2 Psychometric Issues in Research on Scientific Reasoning 35 2.
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01 Jan 2015
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01 Mar 2021
TL;DR: In this article, Schuler*innen der 5. and 6. Klassenstufe in einem „Interaktionseffekte“-Kontext, in dem zwei unabhangige Variablen systematisch miteinander interagieren, in ihrer Argumentation vorgegebene experimentelle Evidenz nutzen.
Abstract: In dieser Studie wird untersucht, in welchem Ausmas Schuler*innen der 5. und 6. Klassenstufe in einem „Interaktionseffekte“-Kontext, in dem zwei unabhangige Variablen systematisch miteinander interagieren, in ihrer Argumentation vorgegebene experimentelle Evidenz nutzen. Zusatzlich wird untersucht, ob ein im „Haupteffekte“-Kontext situiertes Training der Variablenkontrollstrategie (VKS) die evidenzbasierte Argumentation in einem „Interaktionseffekte“-Kontext beeinflusst. Etwa die Halfte einer Stichprobe von $$N=618$$
Schuler*innen (
$$M_{\text{alter}}=11.61$$
, $$\text{SD}=0.65$$
; 50 % weiblich) erhielt ein im „Haupteffekte“-Kontext situiertes Training der VKS und die andere Halfte ein aktives Kontrolltraining. Vor und nach dem Training bearbeiteten die Schuler*innen zwei Aufgaben in einem „Interaktionseffekte“-Kontext, in welchem sie ihre Interpretationen prasentierter Evidenz in offenen Antworten begrundeten. Zur Klassifizierung des Grades an Evidenzbasierung in den Antworten der Schuler*innen wurde ein Kodiersystem mit funf Kategorien entwickelt. Analysen der kodierten Antworten zeigen, dass im Vortest bereits etwa 20 Prozent der Schuler*innen in ihren Begrundungen den Interaktionseffekt korrekt interpretierten. Der Grad an Evidenzbasierung war bei Schuler*innen der 6. Klassenstufe hoher ausgepragt als bei Schuler*innen der 5. Klassenstufe. Bei einer vorwissensnahen Aufgabe zeigten die Schuler*innen uberproportional viele Antworten mit vorwissenbasierter Argumentation ohne Evidenzbezug. Eine kategorienspezifische, ordinale Mehrebenen-Regressionsanalyse zeigte, dass das Training der VKS die Haufigkeit von Begrundungen erhohte, in denen die Schuler*innen Evidenz korrekt nutzten, um Haupteffekte zu interpretieren; auf die Haufigkeit, mit der Interaktionseffekte erkannt wurden, wurde keine Auswirkung gefunden.
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TL;DR: Whereas the Bayesian Information Criterion performed the best of the ICs, the bootstrap likelihood ratio test proved to be a very consistent indicator of classes across all of the models considered.
Abstract: Mixture modeling is a widely applied data analysis technique used to identify unobserved heterogeneity in a population. Despite mixture models' usefulness in practice, one unresolved issue in the application of mixture models is that there is not one commonly accepted statistical indicator for deciding on the number of classes in a study population. This article presents the results of a simulation study that examines the performance of likelihood-based tests and the traditionally used Information Criterion (ICs) used for determining the number of classes in mixture modeling. We look at the performance of these tests and indexes for 3 types of mixture models: latent class analysis (LCA), a factor mixture model (FMA), and a growth mixture models (GMM). We evaluate the ability of the tests and indexes to correctly identify the number of classes at three different sample sizes (n = 200, 500, 1,000). Whereas the Bayesian Information Criterion performed the best of the ICs, the bootstrap likelihood ratio test ...
7,716 citations
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19 Nov 2008TL;DR: This meta-analyses presents a meta-analysis of the contributions from the home, the school, and the curricula to create a picture of visible teaching and visible learning in the post-modern world.
Abstract: Preface Chapter 1 The challenge Chapter 2 The nature of the evidence: A synthesis of meta-analyses Chapter 3 The argument: Visible teaching and visible learning Chapter 4: The contributions from the student Chapter 5 The contributions from the home Chapter 6 The contributions from the school Chapter 7 The contributions from the teacher Chapter 8 The contributions from the curricula Chapter 9 The contributions from teaching approaches - I Chapter 10 The contributions from teaching approaches - II Chapter 11: Bringing it all together Appendix A: The 800 meta-analyses Appendix B: The meta-analyses by rank order References
6,776 citations
"Domain-General and Domain-Specific ..." refers background in this paper
...In groups of students who receive inquiry-based science instruction, inquiry is an effective instructional means for developing conceptual content knowledge (Furtak, Seidel, Iverson, & Briggs, 2012; Hattie, 2009; Slavin, Lake, Hanley, & Thurston, 2014)....
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TL;DR: A fatal flaw of NHST is reviewed and some benefits of Bayesian data analysis are introduced and illustrative examples of multiple comparisons in Bayesian analysis of variance and Bayesian approaches to statistical power are presented.
Abstract: Bayesian methods have garnered huge interest in cognitive science as an approach to models of cognition and perception. On the other hand, Bayesian methods for data analysis have not yet made much headway in cognitive science against the institutionalized inertia of 20th century null hypothesis significance testing (NHST). Ironically, specific Bayesian models of cognition and perception may not long endure the ravages of empirical verification, but generic Bayesian methods for data analysis will eventually dominate. It is time that Bayesian data analysis became the norm for empirical methods in cognitive science. This article reviews a fatal flaw of NHST and introduces the reader to some benefits of Bayesian data analysis. The article presents illustrative examples of multiple comparisons in Bayesian analysis of variance and Bayesian approaches to statistical power. Copyright © 2010 John Wiley & Sons, Ltd. For further resources related to this article, please visit the WIREs website.
6,081 citations
TL;DR: This work generalizes the method proposed by Gelman and Rubin (1992a) for monitoring the convergence of iterative simulations by comparing between and within variances of multiple chains, in order to obtain a family of tests for convergence.
Abstract: We generalize the method proposed by Gelman and Rubin (1992a) for monitoring the convergence of iterative simulations by comparing between and within variances of multiple chains, in order to obtain a family of tests for convergence. We review methods of inference from simulations in order to develop convergence-monitoring summaries that are relevant for the purposes for which the simulations are used. We recommend applying a battery of tests for mixing based on the comparison of inferences from individual sequences and from the mixture of sequences. Finally, we discuss multivariate analogues, for assessing convergence of several parameters simultaneously.
5,493 citations
"Domain-General and Domain-Specific ..." refers background in this paper
...As convergence criterion, potential scale reduction (PSR; Brooks & Gelman, 1998) equal or below 1.030 for each parameter after the first 10000 effective draws was applied....
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...There were no convergence problems, potential scale reduction factors were equal or smaller 1.020 for all estimated parameters (Brooks & Gelman, 1998)....
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