by Jessica J. Luke, Karen Knutson

Abstract

The Learning Science in Informal Environments report holds great potential for creating change among those who work in the field of science education. But to what extent can it inform other sectors of the informal education world? This article explores how the LSIE report might influence research and practice in art museums. By comparing the report to a recent study in art education, the authors point out areas of overlap and divergence relative to content and skills, identity, and communities of practice. We suggest several implications for how art museums and science museums might learn from one another. A call to action is made for further research and discussion about common learning goals and outcomes for the art museum experience.

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by James Kisiel, David Anderson

Abstract

The National Research Council report Learning Science in Informal Environments provides a much-needed synthesis of what research says about informal learning. LSIE makes key observations about science learning and emphasizes the challenges faced in trying to understand and document those complex processes. Yet assumptions about how—and under what conditions—people learn science are not necessarily universal constructs. Such assumptions are driven by the theoretical perspectives of the researchers, as well as the culture of the learners themselves. The limited scope of the volume prohibits it from fully addressing such cultural and historical contexts, and the subsequent implications for methodological approaches. Nevertheless, the report is an important starting point for informing educators, researchers, and policy-makers who work with or within informal science institutions.

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by AMANDA KRANTZ, RANDI KORN, AND MARGARET MENNINGER

Understanding visitors is a necessary and complex undertaking. In this article, we present K-means cluster analysis as one strategy that is particularly useful in unpacking the complex nature of museum visitors.

Three questions organize the article and are as follows:

1. What is K-means cluster analysis?
2. How is K-means cluster analysis conducted?
3. Most importantly: What are the applications of K-means cluster analysis for museum practitioners?

To answer these questions, we present five steps that are vital to conducting a K-means cluster analysis.

We also present three cases studies to demonstrate differences among the results of three K-means cluster analyses and provide practical applications of the findings.