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Louca, Loucas T.
How to study learning processes? Reflection on methods for fine-grain data analysis
1/12/2008, Parnafes, Orit, Hammer, David, Louca, Loucas T., Sherin, Bruce L., Lee, Victor R., Krakowski, Moshe, Di Sessa, Andrea A., Edelson, Daniel C., Parnafes, Orit
This symposium addresses methodological issues in studying children's knowledge and learning processes. The class of methods discussed here looks at processes of learning in fine-grained detail, through which a theoretical framework evolves rather than is merely applied. This class of methodological orientations to studying learning processes diverges from more common ones in several important ways: 1) Attention to diverse features of the learning interaction; 2) conducting a moment-by-moment analysis, zooming in on the fine details of the studied processes; 3) rather than proving or applying a theory, the objective is to make theoretical innovations, or to develop a "humble theory." The challenge of using such techniques is that, by their nature, they do not follow a strongly delineated procedure, especially not the usual sort of coding. This symposium attempts to begin addressing the methodological issues by reflecting on several cases of data analysis.
Epistemological Resources: Applying a New Epistemological Framework to Science Instruction
2004-12-01, Louca, Loucas T., Elby, Andrew, Hammer, David, Kagey, Trisha
Most research on personal epistemologies has conceived them as made up of relatively large, coherent, and stable cognitive structures, either developmental stages or beliefs (perhaps organized into theories). Recent work has challenged these views, arguing that personal epistemologies are better understood as made up of finer grained cognitive resources whose activation depends sensitively on context. In this article, we compare these different frameworks, focusing on their instructional implications by using them to analyze a third-grade teacher's epistemologically motivated intervention and its effect on her students. We argue that the resources framework has more predictive and explanatory power than stage- and beliefs-based frameworks do.