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Solis, S. Lynneth; Grotzer, Tina A. – Journal of Research in Childhood Education, 2016
The aim of this study was to investigate kindergartners' exploration of interactive causality during their play with a pair of toy sound blocks. Interactive causality refers to a type of causal pattern in which two entities interact to produce a causal force, as in particle attraction and symbiotic relationships. Despite being prevalent in nature,…
Descriptors: Kindergarten, Play, Interaction, Concept Formation
Wiley, Jennifer; Hastings, Peter; Blaum, Dylan; Jaeger, Allison J.; Hughes, Simon; Wallace, Patricia; Griffin, Thomas D.; Britt, M. Anne – International Journal of Artificial Intelligence in Education, 2017
This article describes several approaches to assessing student understanding using written explanations that students generate as part of a multiple-document inquiry activity on a scientific topic (global warming). The current work attempts to capture the causal structure of student explanations as a way to detect the quality of the students'…
Descriptors: Science Instruction, Climate, Ecology, Concept Formation
MacPherson, Anna C. – Science Education, 2016
This study sought to investigate the arguments that ecologists engage in as part of their work and to compare their arguments with the way in which ecological arguments have been presented in school argumentation tasks. Ten ecologists, in subfields ranging from individual/behavioral ecology to global ecology, participated in semistructured…
Descriptors: Comparative Analysis, Ecology, Scientists, Persuasive Discourse
Blaum, Dylan; Griffin, Thomas D.; Wiley, Jennifer; Britt, M. Anne – Discourse Processes: A multidisciplinary journal, 2017
We examined students' understanding of the causes of a scientific phenomenon from a multiple-document-inquiry unit. Students read several documents that each described causal factors that could be integrated to address the given writing task of explaining the causes of change in average global temperature. We manipulated whether the document set…
Descriptors: Climate, Public Policy, Causal Models, Essays
Alvarez, Aubry; Booth, Amy E. – Developmental Psychology, 2016
Preschoolers, as a group, are highly attuned to causality, and this attunement is known to facilitate memory, learning, and problem solving. However, recent work reveals substantial individual variability in the strength of children's "causal stance," as demonstrated by their curiosity about and preference for new causal information. In…
Descriptors: Preschool Children, Individual Differences, Preferences, Causal Models
Wu, Hsin-Kai; Wu, Pai-Hsing; Zhang, Wen-Xin; Hsu, Ying-Shao – Science Education, 2013
Drawing upon the literature in computational modeling, multivariable reasoning, and causal attribution, this study aims at characterizing multivariable reasoning practices in computational modeling and revealing the nature of understanding about multivariable causality. We recruited two freshmen, two sophomores, two juniors, two seniors, four…
Descriptors: College Students, Thinking Skills, Logical Thinking, Semi Structured Interviews
Mair, Patrick; von Eye, Alexander – Psychological Methods, 2007
In this article, the authors have 2 aims. First, hierarchical, nonhierarchical, and nonstandard log-linear models are defined. Second, application scenarios are presented for nonhierarchical and nonstandard models, with illustrations of where these scenarios can occur. Parameters can be interpreted in regard to their formal meaning and in regard…
Descriptors: Hypothesis Testing, Causal Models, Matrices, Coding
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection

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