Division of Behavioral and Social Sciences and Education’s research while affiliated with Harvard University and other places

Computing in some form touches nearly every aspect of day to day life and is reflected in the ubiquitous use of cell phones, the expansion of automation into many industries, and the vast amounts of data that are routinely gathered about people's health, education, and buying habits. Computing is now a part of nearly every occupation, not only those in the technology industry. Given the ubiquity of computing in both personal and professional life, there are increasing calls for all learners to participate in learning experiences related to computing including more formal experiences offered in schools, opportunities in youth development programs and after-school clubs, or self-initiated hands-on experiences at home. At the same time, the lack of diversity in the computing workforce and in programs that engage learners in computing is well-documented. It is important to consider how to increase access and design experiences for a wide range of learners. Authentic experiences in STEM - that is, experiences that reflect professional practice and also connect learners to real-world problems that they care about - are one possible approach for reaching a broader range of learners. These experiences can be designed for learners of all ages and implemented in a wide range of settings. However, the role they play in developing youths' interests, capacities, and productive learning identities for computing is unclear. There is a need to better understand the role of authentic STEM experiences in supporting the development of interests, competencies, and skills related to computing. Cultivating Interest and Competencies in Computing examines the evidence on learning and teaching using authentic, open-ended pedagogical approaches and learning experiences for children and youth in grades K-12 in both formal and informal settings. This report gives particular attention to approaches and experiences that promote the success of children and youth from groups that are typically underrepresented in computing fields. Cultivating Interest and Competencies in Computing provides guidance for educators and facilitators, program designers, and other key stakeholders on how to support learners as they engage in authentic learning experiences. © 2021 by the National Academy of Sciences. All rights reserved.

On March 11, 2020, the World Health Organization declared COVID-19 to be a global pandemic. From that moment, leaders of institutions of higher education have had to make quick decisions about how to provide high-quality educational experiences for their students while protecting the health of their students, faculty, and staff and maintaining the fiscal stability of their institutions. Institutions of higher learning took various approaches to the COVID-19 pandemic, which raised two questions: what factors informed decisions at these institutions, and what new initiatives or practices seem to be effective for students during the COVID-19 pandemic? To explore these questions and others regarding the effect of higher education's current COVID-19 response on students in undergraduate and graduate science, technology, engineering, and mathematics programs, the National Academies of Sciences, Engineering, and Medicine held a virtual workshop consisting of four online sessions that took place between September 22 and October 6, 2020. Organized by the Board on Science Education and the Board on Higher Education and Workforce, the virtual workshops provided an opportunity for participants from a range of institutions to share strategies and lessons learned. This publication summarizes the presentation and discussion of the workshop. © 2021 by the National Academy of Sciences. All rights reserved.

Social isolation and loneliness are serious yet underappreciated public health risks that affect a significant portion of the older adult population. Approximately one-quarter of community-dwelling Americans aged 65 and older are considered to be socially isolated, and a significant proportion of adults in the United States report feeling lonely. People who are 50 years of age or older are more likely to experience many of the risk factors that can cause or exacerbate social isolation or loneliness, such as living alone, the loss of family or friends, chronic illness, and sensory impairments. Over a life course, social isolation and loneliness may be episodic or chronic, depending upon an individual's circumstances and perceptions.

In the last twenty years, citizen science has blossomed as a way to engage a broad range of individuals in doing science. Citizen science projects focus on, but are not limited to, nonscientists participating in the processes of scientific research, with the intended goal of advancing and using scientific knowledge. A rich range of projects extend this focus in myriad directions, and the boundaries of citizen science as a field are not clearly delineated. Citizen science involves a growing community of professional practitioners, participants, and stakeholders, and a thriving collection of projects. While citizen science is often recognized for its potential to engage the public in science, it is also uniquely positioned to support and extend participants' learning in science. Contemporary understandings of science learning continue to advance. Indeed, modern theories of learning recognize that science learning is complex and multifaceted. Learning is affected by factors that are individual, social, cultural, and institutional, and learning occurs in virtually any context and at every age. Current understandings of science learning also suggest that science learning extends well beyond content knowledge in a domain to include understanding of the nature and methods of science. Learning Through Citizen Science: Enhancing Opportunities by Design discusses the potential of citizen science to support science learning and identifies promising practices and programs that exemplify the promising practices. This report also lays out a research agenda that can fill gaps in the current understanding of how citizen science can support science learning and enhance science education. © 2018 by the National Academy of Sciences. All rights reserved.

There are many reasons to be curious about the way people learn, and the past several decades have seen an explosion of research that has important implications for individual learning, schooling, workforce training, and policy. In 2000, How People Learn: Brain, Mind, Experience, and School: Expanded Edition was published and its influence has been wide and deep. The report summarized insights on the nature of learning in school-aged children; described principles for the design of effective learning environments; and provided examples of how that could be implemented in the classroom. Since then, researchers have continued to investigate the nature of learning and have generated new findings related to the neurological processes involved in learning, individual and cultural variability related to learning, and educational technologies. In addition to expanding scientific understanding of the mechanisms of learning and how the brain adapts throughout the lifespan, there have been important discoveries about influences on learning, particularly sociocultural factors and the structure of learning environments. How People Learn II: Learners, Contexts, and Cultures provides a much-needed update incorporating insights gained from this research over the past decade. The book expands on the foundation laid out in the 2000 report and takes an in-depth look at the constellation of influences that affect individual learning. How People Learn II will become an indispensable resource to understand learning throughout the lifespan for educators of students and adults. © 2018 by the National Academy of Sciences. All rights reserved.

The need to manage, analyze, and extract knowledge from data is pervasive across industry, government, and academia. Scientists, engineers, and executives routinely encounter enormous volumes of data, and new techniques and tools are emerging to create knowledge out of these data, some of them capable of working with real-time streams of data. The nation's ability to make use of these data depends on the availability of an educated workforce with necessary expertise. With these new capabilities have come novel ethical challenges regarding the effectiveness and appropriateness of broad applications of data analyses. The field of data science has emerged to address the proliferation of data and the need to manage and understand it. Data science is a hybrid of multiple disciplines and skill sets, draws on diverse fields (including computer science, statistics, and mathematics), encompasses topics in ethics and privacy, and depends on specifics of the domains to which it is applied. Fueled by the explosion of data, jobs that involve data science have proliferated and an array of data science programs at the undergraduate and graduate levels have been established. Nevertheless, data science is still in its infancy, which suggests the importance of envisioning what the field might look like in the future and what key steps can be taken now to move data science education in that direction. This study will set forth a vision for the emerging discipline of data science at the undergraduate level. This interim report lays out some of the information and comments that the committee has gathered and heard during the first half of its study, offers perspectives on the current state of data science education, and poses some questions that may shape the way data science education evolves in the future. The study will conclude in early 2018 with a final report that lays out a vision for future data science education. © 2018 by the National Academy of Sciences. All rights reserved.

The National Agricultural Statistics Service (NASS) is the primary statistical data collection agency within the U.S. Department of Agriculture (USDA). NASS conducts hundreds of surveys each year and prepares reports covering virtually every aspect of U.S. agriculture. Among the small-area estimates produced by NASS are county-level estimates for crops (planted acres, harvested acres, production, and yield by commodity) and for cash rental rates for irrigated cropland, nonirrigated cropland, and permanent pastureland. Key users of these county-level estimates include USDA’s Farm Services Agency (FSA) and Risk Management Agency (RMA), which use the estimates as part of their processes for distributing farm subsidies and providing farm insurance, respectively. Improving Crop Estimates by Integrating Multiple Data Sources assesses county-level crop and cash rents estimates, and offers recommendations on methods for integrating data sources to provide more precise county-level estimates of acreage and yield for major crops and of cash rents by land use. This report considers technical issues involved in using the available data sources, such as methods for integrating the data, the assumptions underpinning the use of each source, the robustness of the resulting estimates, and the properties of desirable estimates of uncertainty. © 2017 by the National Academy of Sciences. All rights reserved.

The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel’s first report described federal statistical agencies’ current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel’s two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals. © 2017 by the National Academy of Sciences. All rights reserved.

Here are the first two paragraphs of the Executive Summary. The social cost of carbon (SC-CO2) is an economic metric intended to provide a comprehensive estimate of the net damages—that is, the monetized value of the net impacts, both negative and positive— from the global climate change that results from a small (1 metric ton) increase in carbon dioxide (CO2) emissions. Under Executive Orders regarding regulatory impact analysis and as required by a court ruling, the U.S. government has since 2008 used estimates of the SC-CO2 in federal rulemakings to value the costs and benefits associated with changes in CO2 emissions. In 2010, the Interagency Working Group on the Social Cost of Greenhouse Gases (IWG) developed a methodology for estimating the SC-CO2 across a range of assumptions about future socioeconomic and physical earth systems. The IWG asked the National Academies of Sciences, Engineering, and Medicine to examine potential approaches, along with their relative merits and challenges, for a comprehensive update to the current methodology. The task was to ensure that the SC-CO2 estimates reflect the best available science, focusing on issues related to the choice of models and damage functions, climate science modeling assumptions, socioeconomic and emissions scenarios, presentation of uncertainty, and discounting.

Skilled technical occupations - defined as occupations that require a high level of knowledge in a technical domain but do not require a bachelor's degree for entry - are a key component of the U.S. economy. In response to globalization and advances in science and technology, American firms are demanding workers with greater proficiency in literacy and numeracy, as well as strong interpersonal, technical, and problem-solving skills. However, employer surveys and industry and government reports have raised concerns that the nation may not have an adequate supply of skilled technical workers to achieve its competitiveness and economic growth objectives. In response to the broader need for policy information and advice, Building America's Skilled Technical Workforce examines the coverage, effectiveness, flexibility, and coordination of the policies and various programs that prepare Americans for skilled technical jobs. This report provides action-oriented recommendations for improving the American system of technical education, training, and certification. © 2017 by the National Academy of Sciences. All rights reserved.