Representing to learn in science education: Theoretical framework and analytical approaches

Learning to trust and trusting to learn: a theoretical framework.

Learning from other people requires integrating reasoning about an informant's psychological properties, such as knowledge and intent, with reasoning about the implications of the data the informant chooses to present. Here, we argue for an approach that considers these two reasoning paths as interrelated, reciprocal processes that develop over experience and guide learners when acquiring knowl...

Education and Social Mobility: New Analytical Approaches

This article develops tools for measuring the role of education in intergenerational social class mobility. Sociologists have long sought a method of decomposing the log odds-ratios involving class origins and destinations into a direct part and an indirect part mediated by education. Drawing on recent work we, first, present such a method and, second, suggest ways in which researchers might su...

Network Science: A Theoretical and Practical Framework

LeARnInG APPRoACHes to APPLYInG RoBotICs In sCIenCe eDUCAtIon

There has been a growing interest in using robots for science education in schools. This paper focuses mainly on robots used as tools to teach STEM (science, technology, engineering, math) subjects in school, e.g. according to K-12 curriculum (K-12 is a shortening of kindergarten through twelfth grade). Robotics used at universities is mostly object-based, which means that students learn roboti...

The Brain in Science Education: What Should Everyone Learn?

Dr. Jo Ellen Roseman and Mary Koppal, from the American Academy for the Advancement of Science (AAAS), discuss how brain science fits into national classroom curricula. While recommendations published by AAAS, the National Research Council, the Society for Neuroscience, and the College Board all include standards relating to the brain, what students actually learn in the classroom varies greatl...