Environmental risks are among the most serious challenges of today's societies. Virtually all environmental risks are anthropogenic. The consequences of past decisions made by individuals, business, and governments have already devastated many of the earth's ecological systems and there is an ongoing discussion about the potential effects of environmental change and whether the earth will still provide a livable environment for future generations. The past decade has seen a dramatic growth in publications that focus on environmental issues. However, this literature has been dominated by the natural sciences and research focuses on obtaining more accurate information about natural and ecological processes, with the tacit assumption that this information will prove useful to improve individual, organizational, and societal decision making. This volume focuses on the psychological, sociological, and cultural aspects of environmental risks that have not been given adequate and integrated attention in the past. Understanding of the psychological, social, cultural, and political forces will determine the successes and failures of environmental risk management. In particular, public policy could be improved by the integration of more accurate assumptions about people's cognitions, attitudes, and emotions towards environmental risks.

Order affects the results you get: Different orders of presenting material can lead to qualitatively and quantitatively different learning outcomes. These differences occur in both natural and artificial learning systems. In Order to Learn shows how order effects are crucial in human learning, instructional design, machine learning, and both symbolic and connectionist cognitive models. Each chapter explains a different aspect of how the order in which material is presented can strongly influence what is learned by humans and theoretical models of learning in a variety of domains. In addition to data, models are provided that predict and describe order effects and analyze how and when they will occur. The introductory and concluding chapters compile suggestions for improving learning through better sequences of learning materials, including how to take advantage of order effects that encourage learning and how to avoid order effects that discourage learning. Each chapter also highlights questions that may inspire further research. Taken together, these chapters show how order effects in different areas can and do inform each other. In Order to Learn will be of interest to researchers and students in cognitive science, education, machine learning.