This chapter elaborates on the definition of data visualization, highlights its historical development, and offers examples of how data visualization has been used in evaluations to help aid understanding, collect data and information, conduct analysis, and communicate to a variety of stakeholders. This chapter also outlines future trends in data visualization and their potential influence on evaluation practice. The chapter concludes with some of the main limitations and cautions that are associated with data visualization. © Wiley Periodicals, Inc., and the American Evaluation Association.

Data visualization is often used in two main

This article presents the development and evaluation of a measurement device designed to assess elementary-aged students' social-emotional learning needs. A sample of 633 fourth-, fifth-, and sixth-grade elementary students from 11 public schools in a midsized Midwestern U.S. city was used to evaluate the reliability and validity of the 20-item Social-Emotional Learning Scale (SELS) for the sample. A correlated three-factor model consisting of the factors Task Articulation, Peer Relationships, and Self-Regulation was fit using maximum likelihood estimation and found to be adequate. For the sample, the SELS demonstrated evidence of both precision and accuracy, including internal consistency as well as convergent and discriminant validity. Potential applications for the SELS and further research are discussed.

Legitimate knowledge claims about causation have been a central concern among evaluators and applied researchers for several decades and often have been the subject of heated debates. In recent years these debates have resurfaced with a renewed intensity, due in part to the priority currently being given to randomized experiments by many funders of evaluation studies, such as the Institute for Educational Sciences. In this dialogue, which took place at Western Michigan University in October 2008, two of the field's leading theorists and methodologists, Thomas D. Cook and Michael Scriven, described their current thinking and views about causation and causal inference in evaluation. They also discussed recent methodological developments for causeprobing investigations that sometimes produce results comparable to those produced by randomized experiments. Both Cook and Scriven prepared clarifying postscripts after reading the edited transcript. Keywords causal inference, causation, randomized controlled trials, methodologyThe Evaluation Center's Evaluation Café, held weekly during the academic year, is a public forum intended to foster engaging dialogue and debate on a variety of evaluation-related topics. On October 24, 2008, The Evaluation Center and Western Michigan University's Interdisciplinary PhD in Evaluation program jointly hosted a special Café event on contemporary thinking about causation and causal inference in evaluation. Largely centered on randomized controlled trials (RCTs), causal inference in evaluation has been a point of high priority as well as contention, given the recent resurgence of debates regarding legitimate knowledge claims and conceptions of ''evidence'' in applied

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