Applying science of learning in education: Infusing psychological science into the curriculum

The field of specialization known as the science of learning is not, in fact, one field. Science of learning is a term that serves as an umbrella for many lines of research, theory, and application. A term with an even wider reach is Learning Sciences (Sawyer, 2006). The present book represents a sliver, albeit a substantial one, of the scholarship on the science of learning and its application in educational settings (Science of Instruction, Mayer 2011). Although much, but not all, of what is presented in this book is focused on learning in college and university settings, teachers of all academic levels may find the recommendations made by chapter authors of service. The overarching theme of this book is on the interplay between the science of learning, the science of instruction, and the science of assessment (Mayer, 2011). The science of learning is a systematic and empirical approach to understanding how people learn. More formally, Mayer (2011) defined the science of learning as the “scientific study of how people learn” (p. 3). The science of instruction (Mayer 2011), informed in part by the science of learning, is also on display throughout the book. Mayer defined the science of instruction as the “scientific study of how to help people learn” (p. 3). Finally, the assessment of student learning (e.g., learning, remembering, transferring knowledge) during and after instruction helps us determine the effectiveness of our instructional methods. Mayer defined the science of assessment as the “scientific study of how to determine what people know” (p.3). Most of the research and applications presented in this book are completed within a science of learning framework. Researchers first conducted research to understand how people learn in certain controlled contexts (i.e., in the laboratory) and then they, or others, began to consider how these understandings could be applied in educational settings. Work on the cognitive load theory of learning, which is discussed in depth in several chapters of this book (e.g., Chew; Lee and Kalyuga; Mayer; Renkl), provides an excellent example that documents how science of learning has led to valuable work on the science of instruction. Most of the work described in this book is based on theory and research in cognitive psychology. We might have selected other topics (and, thus, other authors) that have their research base in behavior analysis, computational modeling and computer science, neuroscience, etc. We made the selections we did because the work of our authors ties together nicely and seemed to us to have direct applicability in academic settings

Passion and Purpose: One Student\u27s Journey to Medical School

In a creative essay, a student describes her passion for science and finding a greater purpose in serving people through science—leading her to pursue a medical career

Data Science and Ebola

Data Science---Today, everybody and everything produces data. People produce large amounts of data in social networks and in commercial transactions. Medical, corporate, and government databases continue to grow. Sensors continue to get cheaper and are increasingly connected, creating an Internet of Things, and generating even more data. In every discipline, large, diverse, and rich data sets are emerging, from astrophysics, to the life sciences, to the behavioral sciences, to finance and commerce, to the humanities and to the arts. In every discipline people want to organize, analyze, optimize and understand their data to answer questions and to deepen insights. The science that is transforming this ocean of data into a sea of knowledge is called data science. This lecture will discuss how data science has changed the way in which one of the most visible challenges to public health is handled, the 2014 Ebola outbreak in West Africa.Comment: Inaugural lecture Leiden Universit

Systems of innovation are systems of mediation: a discussion of the critical role of science communication in innovation and knowledge-based development

This discussion paper highlights the critical role of science communication, not as an 'add-on' topic to bring about the acceptance of science, but as a process which guides the processes of innovation and knowledge-based development. It argues that people do not passively adopt science for homogeneous activities; rather, scientific knowledge and technologies are adapted to the everyday lives of very different communities and vice versa. If one wishes to design processes to support and respond to innovation and knowledge based-development without excluding certain groups of people, it is not enough to say that science is applied in society, nor that technologies impact on society. Rather, what needs to be recognised is that it is through the efforts of science communication activities that scientific knowledge and technologies are made meaningful to the everyday lives of very different communities. It is therefore through the support of science communication activities that socio-economic and political systems may give rise to, and may be influenced by, the patterns of use and adaptation of technologies by different communities of interest. The paper ends with a discussion of the policy objectives of the Office of Science and Technology (OST) and the Department for International Development (DFID) in the UK, and the kinds of science communication policies that might fulfil those objectives

Deconstructing climate misinformation to identify reasoning errors

Misinformation can have significant societal consequences. For example, misinformation about climate change has confused the public and stalled support for mitigation policies. When people lack the expertise and skill to evaluate the science behind a claim, they typically rely on heuristics such as substituting judgment about something complex (i.e. climate science) with judgment about something simple (i.e. the character of people who speak about climate science) and are therefore vulnerable to misleading information. Inoculation theory offers one approach to effectively neutralize the influence of misinformation. Typically, inoculations convey resistance by providing people with information that counters misinformation. In contrast, we propose inoculating against misinformation by explaining the fallacious reasoning within misleading denialist claims. We offer a strategy based on critical thinking methods to analyse and detect poor reasoning within denialist claims. This strategy includes detailing argument structure, determining the truth of the premises, and checking for validity, hidden premises, or ambiguous language. Focusing on argument structure also facilitates the identification of reasoning fallacies by locating them in the reasoning process. Because this reason-based form of inoculation is based on general critical thinking methods, it offers the distinct advantage of being accessible to those who lack expertise in climate science. We applied this approach to 42 common denialist claims and find that they all demonstrate fallacious reasoning and fail to refute the scientific consensus regarding anthropogenic global warming. This comprehensive deconstruction and refutation of the most common denialist claims about climate change is designed to act as a resource for communicators and educators who teach climate science and/or critical thinking

Science and Values

This short paper, written for a wide audience, introduces "science and values" topics as they have arisen in the context of eugenics. The paper especially focuses on the context of 20th century eugenics in western Canada, where eugenic legislation in two provinces was not repealed until the 1970s and thousands of people were sterilized without their consent. A framework for understanding science-value relationships within this context is discussed, and so too is recent relevant work in philosophy of science

Science lives: School choices and ‘natural tendencies’

An analysis of 12 semi-structured interviews with university-based scientists and non-scientists illustrates their life journeys towards, or away from, science and the strengths and impact of life occurrences leading them to choose science or non-science professions. We have adopted narrative approaches and used Mezirow's transformative learning theory framework. The areas of discussion from the result have stressed on three main categories that include ‘smooth transition’, ‘incremental wavering transition' and ‘transformative transition’. The article concludes by discussing the key influences that shaped initial attitudes and direction in these people through natural inclination, environmental inspirations and perceptions of science

Grist to the mill of anti-evolutionism: the failed strategy of ruling the supernatural out of science by philosophical fiat

According to a widespread philosophical opinion, science is strictly limited to investigating natural causes and putting forth natural explanations. Lacking the tools to evaluate supernatural claims, science must remain studiously neutral on questions of metaphysics. This (self-imposed) stricture, which goes under the name of ‘methodological naturalism’, allows science to be divorced from metaphysical naturalism or atheism, which many people tend to associate with it. However, ruling the supernatural out of science by fiat is not only philosophically untenable, it actually provides grist to the mill of anti-evolutionism. The philosophical flaws in this conception of methodological naturalism have been gratefully exploited by advocates of Intelligent Design Creationism to bolster their false accusations of naturalistic bias and dogmatism on the part of modern science. We argue that it promotes a misleading view of the scientific endeavor and is at odds with the foremost arguments for evolution by natural selection. Reconciling science and religion on the basis of such methodological strictures is therefore misguided