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Chuenjai Sukpan; Rebecca M. Kuiper – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The (Random Intercept) Cross-Lagged Panel Model ((RI-)CLPM) is increasingly used in psychology and related fields to assess the longitudinal relationship of two or more variables on each other. Researchers are interested in the question which of the lagged effects is causally dominant receives considerable attention. However, currently used…
Descriptors: Causal Models, Psychological Studies, Multivariate Analysis, Cognitive Mapping
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Quoc Hoa Tran-Duong – Cambridge Journal of Education, 2024
The quality of products from the causal mapping process and the effect of factors related to causal map quality are unlikely to be the same for students at different educational levels. However, there is a lack of studies that provide insights into causal maps constructed by primary school students to reveal appropriate strategies. This study…
Descriptors: Cognitive Mapping, Causal Models, Prior Learning, Elementary School Students
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Jinruo Duan; Rong Yan; Samad Zare; Jike Qin – Asia-Pacific Science Education, 2024
Causal reasoning is important to children's cognition and academic development. However, there have been few empirical studies on the impact of visual cues and non-verbal scaffolding on children's reasoning in continuous causal processes. Hence, the present study aims to explore how causal reasoning in continuous processes is facilitated by visual…
Descriptors: Cues, Visual Aids, Nonverbal Communication, Science Education
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Lakusta, Laura; Muentener, Paul; Petrillo, Lauren; Mullanaphy, Noelle; Muniz, Lauren – Cognitive Science, 2017
Previous studies have shown a robust bias to express the goal path over the source path when describing events ("the bird flew into the pitcher," rather than "… out of the bucket into the pitcher"). Motivated by linguistic theory, this study manipulated the causal structure of events (specifically, making the source cause the…
Descriptors: Linguistic Theory, Motion, Preschool Children, English
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Öllinger, Michael; Hammon, Stephanie; von Grundherr, Michael; Funke, Joachim – Educational Technology Research and Development, 2015
Causal mapping is often recognized as a technique to support strategic decisions and actions in complex problem situations. Such drawing of causal structures is supposed to particularly foster the understanding of the interaction of the various system elements and to further encourage holistic thinking. It builds on the idea that humans make use…
Descriptors: Problem Solving, Causal Models, Cognitive Mapping, Computer Simulation
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Huey, Maryann E.; Baker, Deidra L. – Mathematics Teacher, 2015
Many teachers of required secondary school mathematics classes are introducing statistics and probability topics traditionally relegated to college or AP Statistics courses. As a result, they need guidance in preparing lesson plans and orchestrating effective classroom discussions. In this article, the authors will describe the students' learning…
Descriptors: Misconceptions, Causal Models, Secondary School Mathematics, Probability
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de Kwaadsteniet, Leontien; Hagmayer, York; Krol, Nicole P. C. M.; Witteman, Cilia L. M. – Psychological Assessment, 2010
An important reason to choose an intervention to treat psychological problems of clients is the expectation that the intervention will be effective in alleviating the problems. The authors investigated whether clinicians base their ratings of the effectiveness of interventions on models that they construct representing the factors causing and…
Descriptors: Intervention, Causal Models, Psychologists, Cognitive Mapping
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Perales, Jose C.; Shanks, David R. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2008
It has been proposed that causal power (defined as the probability with which a candidate cause would produce an effect in the absence of any other background causes) can be intuitively computed from cause-effect covariation information. Estimation of power is assumed to require a special type of counterfactual probe question, worded to remove…
Descriptors: Figurative Language, Probability, Cognitive Mapping, Knowledge Representation
Garcia, GNA – Online Submission, 2008
A rich narrative-style bibliography of concept mapping (reviewing six articles published between 1992-2005). Articles reviewed include: (1) Cognitive mapping: A qualitative research method for social work (C. Bitoni); (2) Collaborative concept mapping: Provoking and supporting meaningful discourse (C. Boxtel, J. Linden, E. Roelofs, and G. Erkens);…
Descriptors: Concept Mapping, Qualitative Research, Maps, Cognitive Mapping
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Gopnik, Alison; Glymour, Clark; Sobel, David M.; Schulz, Laura E.; Kushnir, Tamar; Danks, David – Psychological Review, 2004
The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously…
Descriptors: Causal Models, Young Children, Learning Strategies, Cognitive Processes
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Ringer, Fritz – Comparative Education, 2006
Since the classical authors of the nineteenth century, the explanation of macro-social phenomena has been considered as the essential epistemic achievement, hence the "raison d'etre," of comparative analysis in the social sciences. In practice, however, the claims of comparative social enquiry for providing convincing explanations are…
Descriptors: Comparative Analysis, Intellectual History, Social Theories, Social Sciences
Kleinfeld, Judith – 1991
This paper examines what student teachers learn from writing a case about their student teaching experience. An analytic framework was developed to understand what students learn from writing such narratives. It contained six elements: (1) an intention, which formed the springboard for the dramatic action; (2) an initial conceptual map which…
Descriptors: Alaska Natives, Case Method (Teaching Technique), Case Studies, Causal Models