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| data science summer programs for high school students: Mindset Mathematics Jo Boaler, Jen Munson, Cathy Williams, 2017-08-28 Engage students in mathematics using growth mindset techniques The most challenging parts of teaching mathematics are engaging students and helping them understand the connections between mathematics concepts. In this volume, you'll find a collection of low floor, high ceiling tasks that will help you do just that, by looking at the big ideas at the first-grade level through visualization, play, and investigation. During their work with tens of thousands of teachers, authors Jo Boaler, Jen Munson, and Cathy Williams heard the same message—that they want to incorporate more brain science into their math instruction, but they need guidance in the techniques that work best to get across the concepts they needed to teach. So the authors designed Mindset Mathematics around the principle of active student engagement, with tasks that reflect the latest brain science on learning. Open, creative, and visual math tasks have been shown to improve student test scores, and more importantly change their relationship with mathematics and start believing in their own potential. The tasks in Mindset Mathematics reflect the lessons from brain science that: There is no such thing as a math person - anyone can learn mathematics to high levels. Mistakes, struggle and challenge are the most important times for brain growth. Speed is unimportant in mathematics. Mathematics is a visual and beautiful subject, and our brains want to think visually about mathematics. With engaging questions, open-ended tasks, and four-color visuals that will help kids get excited about mathematics, Mindset Mathematics is organized around nine big ideas which emphasize the connections within the Common Core State Standards (CCSS) and can be used with any current curriculum. |
| data science summer programs for high school students: Data Science for Undergraduates National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Board on Science Education, Division on Engineering and Physical Sciences, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, Computer Science and Telecommunications Board, Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective, 2018-11-11 Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field. |
| data science summer programs for high school students: Envisioning the Data Science Discipline National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Board on Science Education, Division on Engineering and Physical Sciences, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, Computer Science and Telecommunications Board, Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective, 2018-03-05 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. |
| data science summer programs for high school students: Making Summer Count Jennifer Sloan McCombs, Catherine H. Augustine, Heather L. Schwartz, 2011 Students typically lose knowledge and skills during the summer, particularly low-income students. Districts and private providers can benefit from the evidence on summer programming to maximize program effectiveness, quality, reach, and funding. |
| data science summer programs for high school students: Learning to Solve Problems by Searching for Macro-operators Richard E. Korf, 1985 This monograph explores the idea of learning efficient strategies for solving problems by searching for macro-operators. |
| data science summer programs for high school students: Investing in Successful Summer Programs Jennifer Sloan McCombs, Catherine H. Augustine, Fatih Unlu, 2021-06-30 Research evidence suggests that summer breaks contribute to income-based achievement and opportunity gaps for children and youth. However, summertime can also be used to provide programs that support an array of goals for children and youth, including improved academic achievement, physical health, mental health, social and emotional well-being, the acquisition of skills, and the development of interests. This report is intended to provide practitioners, policymakers, and funders current information about the effectiveness of summer programs designed for children and youth entering grades K-12. Policymakers increasingly expect that the creation of and investment in summer programs will be based on research evidence. Notably, the 2015 Every Student Succeeds Act (ESSA) directs schools and districts to adopt programs that are supported by research evidence if those programs are funded by specific federal streams. Although summer programs can benefit children and youth who attend, not all programs result in improved outcomes. RAND researchers identified 43 summer programs with positive outcomes that met the top three tiers of ESSA's evidence standards. These programs were identified through an initial literature search of 3,671 citations and a full-text review of 1,360 documents and address academic learning, learning at home, social and emotional well-being, and employment and career outcomes. The authors summarize the evidence and provide detailed information on each of the 43 programs, focusing on the evidence linking summer programs with outcomes and classifying the programs according to the top three evidence tiers (strong, moderate, or promising evidence) consistent with ESSA and subsequent federal regulatory guidance. |
| data science summer programs for high school students: Mathematical Mindsets Jo Boaler, 2015-10-12 Banish math anxiety and give students of all ages a clear roadmap to success Mathematical Mindsets provides practical strategies and activities to help teachers and parents show all children, even those who are convinced that they are bad at math, that they can enjoy and succeed in math. Jo Boaler—Stanford researcher, professor of math education, and expert on math learning—has studied why students don't like math and often fail in math classes. She's followed thousands of students through middle and high schools to study how they learn and to find the most effective ways to unleash the math potential in all students. There is a clear gap between what research has shown to work in teaching math and what happens in schools and at home. This book bridges that gap by turning research findings into practical activities and advice. Boaler translates Carol Dweck's concept of 'mindset' into math teaching and parenting strategies, showing how students can go from self-doubt to strong self-confidence, which is so important to math learning. Boaler reveals the steps that must be taken by schools and parents to improve math education for all. Mathematical Mindsets: Explains how the brain processes mathematics learning Reveals how to turn mistakes and struggles into valuable learning experiences Provides examples of rich mathematical activities to replace rote learning Explains ways to give students a positive math mindset Gives examples of how assessment and grading policies need to change to support real understanding Scores of students hate and fear math, so they end up leaving school without an understanding of basic mathematical concepts. Their evasion and departure hinders math-related pathways and STEM career opportunities. Research has shown very clear methods to change this phenomena, but the information has been confined to research journals—until now. Mathematical Mindsets provides a proven, practical roadmap to mathematics success for any student at any age. |
| data science summer programs for high school students: Situating Data Science Michelle Hoda Wilkerson, Joseph L. Polman, 2022-04-19 The emerging field of Data Science has had a large impact on science and society. This book explores how one distinguishing feature of Data Science – its focus on data collected from social and environmental contexts within which learners often find themselves deeply embedded – suggests serious implications for learning and education. Drawing from theories of learning and identity development in the learning sciences, this volume investigates the impacts of these complex relationships on how learners think about, use, and share data, including their understandings of data in light of history, race, geography, and politics. More than just using ‘real world examples’ to motivate students to work with data, this book demonstrates how learners’ relationships to data shape how they approach those data with agency, as part of their social and cultural lives. Together, the contributions offer a vision of how the learning sciences can contribute to a more expansive, socially aware, and transformative Data Science Education. The chapters in this book were originally published as a special issue of the Journal of the Learning Sciences. |
| data science summer programs for high school students: Data Science for Undergraduates National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Board on Science Education, Division on Engineering and Physical Sciences, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, Computer Science and Telecommunications Board, Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective, 2018-10-11 Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field. |
| data science summer programs for high school students: Learning from Summer Catherine H. Augustine, Jennifer Sloan McCombs, John F. Pane, Heather L. Schwartz, Jonathan David Schweig, Andrew McEachin, Kyle Siler-Evans, 2016 RAND researchers assess voluntary, district-led summer learning programs for low-income, urban elementary students. This third report in a series examines student outcomes after one and two summers of programming. |
| data science summer programs for high school students: Practical Python Data Wrangling and Data Quality Susan E. McGregor, 2021-12-03 The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations. Complementing foundational concepts with expert advice, author Susan E. McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data. Use Python 3.8+ to read, write, and transform data from a variety of sources Understand and use programming basics in Python to wrangle data at scale Organize, document, and structure your code using best practices Collect data from structured data files, web pages, and APIs Perform basic statistical analyses to make meaning from datasets Visualize and present data in clear and compelling ways |
| data science summer programs for high school students: The Summer Quarter Stanford University, 1920 |
| data science summer programs for high school students: The Ultimate Summer Program Guide Jennifer Williams Taylor, Joyce Wong, 2019-01-21 If you're seeking one fundamental resource which inspires both academic and personal discovery in the pursuit of higher education, The Ultimate Summer Program Guide: For High School Students is for you! A roadmap to the college admissions process, this book is a powerful and distinctive planning strategy guide that accounts for academic and personal self-exploration. With the power to make a student's college application stand out, ability to assess campuses, and the chance to discover a career path, this is an essential resource for any student no matter their college or career path.It's no secret that college costs are getting higher while admissions rates are dropping. Students and parents are faced with growing fears that higher education might not even be worth it in the long run. With the release of The Ultimate Summer Program Guide: For High School Students, readers will find a better way to prepare for one of life's largest and most impactful decisions. As the academic industry's largest, most extensive publication dedicated exclusively to summer programs, it's an essential guide for every prospective college student and family. -Do I really know what my major of interest entails? -Do I even know what other majors are out there? -Will I like living away from home as much as I hope I will? -Does my desired campus atmosphere support my learning needs? -Am I really ready?Very few college resources address these types of questions, much less by virtue of fingertip access to experiences that provide the answers in context. Unlike the majority of college resources, which are designed for students who know exactly what they want to do, this guide provides a connection to trialing colleges, careers, and communities, which in turn aids in self-reflection and educational planning. The diverse and far-reaching offerings enclosed within The Ultimate Summer Program Guide: For High School Students are intended to give students a glimpse into what they think they want, and question what else there might be. Those who apply for and complete one or more summer programs using the information provided will no doubt join the ranks of the most academically, socially and contextually prepared college applicants. In addition, they will have gained an unrivaled and distinctive edge that makes their application stand out. |
| data science summer programs for high school students: Research on Reasoning with Data and Statistical Thinking: International Perspectives Gail F. Burrill, Leandro de Oliveria Souza, Enriqueta Reston, 2023-07-21 This book is derived from selected papers from the Fourteenth International Congress on Mathematical Education Topic Study Group 12, Teaching and Learning Statistics. It describes recent research on curriculum, pedagogy and outreach initiatives from countries as diverse as Brazil, Chile, Columbia, Denmark, Germany, the Netherlands, Spain, Sweden, Thailand, Turkey, the United Kingdom, and the United States. The book has a focus on the use of data in the teaching and learning of statistics across grade levels and begins with an overview of the status of statistics education and the use of data from seven different countries across the continents and the link between research and practice in those countries. Because it contains specific examples of the research, for example, on the ways children learn, the choice and implementation of tasks, or the role of informal inference, the book will be a great resource to those interested and involved in the teaching of statistics, curriculum developers, and statistics education researchers. |
| data science summer programs for high school students: Shaping Summertime Experiences National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Board on Children, Youth, and Families, Committee on Summertime Experiences and Child and Adolescent Education, Health, and Safety, 2020-01-30 For children and youth, summertime presents a unique break from the traditional structure, resources, and support systems that exist during the school year. For some students, this time involves opportunities to engage in fun and enriching activities and programs, while others face additional challenges as they lose a variety of supports, including healthy meals, medical care, supervision, and structured programs that enhance development. Children that are limited by their social, economic, or physical environments during the summer months are at higher risk for worse academic, health, social and emotional, and safety outcomes. In contrast, structured summertime activities and programs support basic developmental needs and positive outcomes for children and youth who can access and afford these programs. These discrepancies in summertime experiences exacerbate pre-existing academic inequities. While further research is needed regarding the impact of summertime on developmental domains outside of the academic setting, extensive literature exists regarding the impact of summertime on academic development trajectories. However, this knowledge is not sufficiently applied to policy and practice, and it is important to address these inequalities. Shaping Summertime Experiences examines the impact of summertime experiences on the developmental trajectories of school-age children and youth across four areas of well-being, including academic learning, social and emotional development, physical and mental health, and health-promoting and safety behaviors. It also reviews the state of science and available literature regarding the impact of summertime experiences. In addition, this report provides recommendations to improve the experiences of children over the summertime regarding planning, access and equity, and opportunities for further research and data collection. |
| data science summer programs for high school students: Leadership in Statistics and Data Science Amanda L. Golbeck, 2021-03-22 This edited collection brings together voices of the strongest thought leaders on diversity, equity and inclusion in the field of statistics and data science, with the goal of encouraging and steering the profession into the regular practice of inclusive and humanistic leadership. It provides futuristic ideas for promoting opportunities for equitable leadership, as well as tested approaches that have already been found to make a difference. It speaks to the challenges and opportunities of leading successful research collaborations and making strong connections within research teams. Curated with a vision that leadership takes a myriad of forms, and that diversity has many dimensions, this volume examines the nuances of leadership within a workplace environment and promotes storytelling and other competencies as critical elements of effective leadership. It makes the case for inclusive and humanistic leadership in statistics and data science, where there often remains a dearth of women and members of certain racial communities among the employees. Titled and non-titled leaders will benefit from the planning, evaluation, and structural tools offered within to contribute inclusive excellence in workplace climate, environment, and culture. |
| data science summer programs for high school students: Guide to Teaching Data Science Orit Hazzan, Koby Mike, 2023-03-20 Data science is a new field that touches on almost every domain of our lives, and thus it is taught in a variety of environments. Accordingly, the book is suitable for teachers and lecturers in all educational frameworks: K-12, academia and industry. This book aims at closing a significant gap in the literature on the pedagogy of data science. While there are many articles and white papers dealing with the curriculum of data science (i.e., what to teach?), the pedagogical aspect of the field (i.e., how to teach?) is almost neglected. At the same time, the importance of the pedagogical aspects of data science increases as more and more programs are currently open to a variety of people. This book provides a variety of pedagogical discussions and specific teaching methods and frameworks, as well as includes exercises, and guidelines related to many data science concepts (e.g., data thinking and the data science workflow), main machine learning algorithms and concepts (e.g., KNN, SVM, Neural Networks, performance metrics, confusion matrix, and biases) and data science professional topics (e.g., ethics, skills and research approach). Professor Orit Hazzan is a faculty member at the Technion’s Department of Education in Science and Technology since October 2000. Her research focuses on computer science, software engineering and data science education. Within this framework, she studies the cognitive and social processes on the individual, the team and the organization levels, in all kinds of organizations. Dr. Koby Mike is a Ph.D. graduate from the Technion's Department of Education in Science and Technology under the supervision of Professor Orit Hazzan. He continued his post-doc research on data science education at the Bar-Ilan University, and obtained a B.Sc. and an M.Sc. in Electrical Engineering from Tel Aviv University. |
| data science summer programs for high school students: STEM Gems Stephanie Espy, 2016-06-06 Tired of seeing the same careers foisted upon women in TV, movies and magazines? Chemical engineer Stephanie Espy, a graduate of MIT, UC Berkeley and Emory University, tells the stories of 44 inspiring women in STEM to show girls and young women around the world a new set of women heroes to look up to.The statistics for women in Science, Technology, Engineering and Mathematics (STEM) careers are just plain sad. In recent years, fewer than 20% of college graduates in engineering and computer science were women. While stereotypes pervade about women in these fields, the truth is that most girls have never even heard of these careers and are not aware of the wide range of options that exist.In STEM Gems, you and your daughter, niece, neighbor, friend or student will discover: The stories of 44 inspiring women in diverse STEM fields and how they made it; The challenges these incredible women faced in pursuit of their dreams; The tremendous accomplishments these Gems have achieved in their respective STEM fields; Advice on how to pursue science, technology, engineering and mathematics careers; Actionable steps girls and young women can take right now to set themselves up for success; What girls and young women can expect in a promising STEM career, and much, much more!Through the powerful stories of the STEM Gems in this book, girls and young women will have their pick of current role models of various ages, ethnicities and job types. And through the eight chapters that outline actionable steps, girls and young women will learn what they can do right now, today, to set themselves up for success and to create their own unique paths. STEM Gems is relatable, encouraging and inspiring, demonstrating the limitless possibilities for the next generation of women. |
| data science summer programs for high school students: Improving Equity in Data Science Colby Tofel-Grehl, Emmanuel Schanzer, 2024-06-03 Improving Equity in Data Science offers a comprehensive look at the ways in which data science can be conceptualized and engaged more equitably within the K-16 classroom setting, moving beyond merely broadening participation in educational opportunities. This book makes the case for field wide definitions, literacies and practices for data science teaching and learning that can be commonly discussed and used, and provides examples from research of these practices and literacies in action. Authors share stories and examples of research wherein data science advances equity and empowerment through the critical examination of social, educational, and political topics. In the first half of the book, readers will learn how data science can deliberately be embedded within K-12 spaces to empower students to use it to identify and address inequity. The latter half will focus on equity of access to data science learning opportunities in higher education, with a final synthesis of lessons learned and presentation of a 360-degree framework that links access, curriculum, and pedagogy as multiple facets collectively essential to comprehensive data science equity work. Practitioners and teacher educators will be able to answer the question, “how can data science serve to move equity efforts in computing beyond basic inclusion to empowerment?” whether the goal is to simply improve definitions and approaches to research on data science or support teachers of data science in creating more equitable and inclusive environments within their classrooms. |
| data science summer programs for high school students: Research in Education , 1974 |
| data science summer programs for high school students: Full STEAM Ahead Cherie P. Pandora, Kathy Fredrick, 2017-10-03 This book is a toolkit for youth and young adult librarians—school and public—who wish to incorporate science, technology, engineering, art, and math (STEAM) into their programs and collections but aren't sure where to begin. Most educators are well aware of the reasons for emphasizing STEAM—topics that fall within the broad headings of science, technology, engineering, arts, and mathematics—in the curriculum, regardless of grade level. But how do librarians who work with 'tweens in middle school, high school, and public libraries—fit into the picture and play their roles to underscore their relevance in making STEAM initiatives successful? This book answers those key questions, providing program guidelines and resources for each of the STEAM areas. Readers will learn how to collaborate in STEAM efforts by providing information on resources, activities, standards, conferences, museums, programs, and professional organizations. Emphasis is placed on encouraging girls and minorities to take part in and get excited about STEAM. In addition, the book examines how makerspaces can enhance this initiative; how to connect your programs to educational standards; where to find funding; how to effectively promote your resources and programs, including how school and public librarians can collaborate to maximize their efforts; how to find and provide professional development; and how to evaluate your program to make further improvements and boost effectiveness. Whether you are on the cusp of launching a STEAM initiative, or looking for ways to grow and enhance your program, this book will be an invaluable resource. |
| data science summer programs for high school students: Urban Environmental Education Review Alex Russ, Marianne E. Krasny, 2017-06-06 Urban Environmental Education Review explores how environmental education can contribute to urban sustainability. Urban environmental education includes any practices that create learning opportunities to foster individual and community well-being and environmental quality in cities. It fosters novel educational approaches and helps debunk common assumptions that cities are ecologically barren and that city people don't care for, or need, urban nature or a healthy environment. Topics in Urban Environmental Education Review range from the urban context to theoretical underpinnings, educational settings, participants, and educational approaches in urban environmental education. Chapters integrate research and practice to help aspiring and practicing environmental educators, urban planners, and other environmental leaders achieve their goals in terms of education, youth and community development, and environmental quality in cities. The ten-essay series Urban EE Essays, excerpted from Urban Environmental Education Review, may be found here: naaee.org/eepro/resources/urban-ee-essays. These essays explore various perspectives on urban environmental education and may be reprinted/reproduced only with permission from Cornell University Press. |
| data science summer programs for high school students: Summer Melt Benjamin L. Castleman, Lindsay C. Page, 2020-01-15 Under increasing pressure to raise graduation rates and ensure that students leave high school college- and career-ready, many school and district leaders may believe that, when students graduate with college acceptances in hand, their work is done. But as Benjamin L. Castleman and Lindsay C. Page show, summer can be a time of significant attrition among college-intending seniors—especially those from low-income families. Anywhere from 10 to 40 percent of students presumed to be headed to college fail to matriculate at any postsecondary institution in the fall following high school. Summer Melt explores the complex factors that contribute to this trend—the absence of school support, confusion over paperwork, lack of parental guidance, and the teenage tendency to procrastinate. The authors draw on findings from fields such as neuroscience, behavioral economics, and social psychology to contextualize these factors. Drawing on a series of research studies, they show how schools and districts can develop effective, low-cost, scalable responses—including counselor outreach, peer mentoring, and using text messages and social media—to help students stay on track over the summer. Summer Melt offers very practical guidance for schools and districts committed to helping their students make the transition to college. |
| data science summer programs for high school students: Resources in Education , 2001 |
| data science summer programs for high school students: Roundtable on Data Science Postsecondary Education National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Division on Engineering and Physical Sciences, Board on Science Education, Computer Science and Telecommunications Board, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, 2020-10-02 Established in December 2016, the National Academies of Sciences, Engineering, and Medicine's Roundtable on Data Science Postsecondary Education was charged with identifying the challenges of and highlighting best practices in postsecondary data science education. Convening quarterly for 3 years, representatives from academia, industry, and government gathered with other experts from across the nation to discuss various topics under this charge. The meetings centered on four central themes: foundations of data science; data science across the postsecondary curriculum; data science across society; and ethics and data science. This publication highlights the presentations and discussions of each meeting. |
| data science summer programs for high school students: The Comer School Development Program Pat Coulter, 1993 |
| data science summer programs for high school students: The Laboratory for Hydrospheric Processes , 1994 |
| data science summer programs for high school students: Keeping Track Jeannie Oakes, 2005-05-10 Selected by the American School Board Journal as a “Must Read” book when it was first published and named one of 60 “Books of the Century” by the University of South Carolina Museum of Education for its influence on American education, this provocative, carefully documented work shows how tracking—the system of grouping students for instruction on the basis of ability—reflects the class and racial inequalities of American society and helps to perpetuate them. For this new edition, Jeannie Oakes has added a new Preface and a new final chapter in which she discusses the “tracking wars” of the last twenty years, wars in which Keeping Track has played a central role. From reviews of the first edition:“Should be read by anyone who wishes to improve schools.”—M. Donald Thomas, American School Board Journal“[This] engaging [book] . . . has had an influence on educational thought and policy that few works of social science ever achieve.”—Tom Loveless in The Tracking Wars“Should be read by teachers, administrators, school board members, and parents.”—Georgia Lewis, Childhood Education“Valuable. . . . No one interested in the topic can afford not to attend to it.”—Kenneth A. Strike, Teachers College Record |
| data science summer programs for high school students: A Framework for K-12 Science Education National Research Council, Division of Behavioral and Social Sciences and Education, Board on Science Education, Committee on a Conceptual Framework for New K-12 Science Education Standards, 2012-02-28 Science, engineering, and technology permeate nearly every facet of modern life and hold the key to solving many of humanity's most pressing current and future challenges. The United States' position in the global economy is declining, in part because U.S. workers lack fundamental knowledge in these fields. To address the critical issues of U.S. competitiveness and to better prepare the workforce, A Framework for K-12 Science Education proposes a new approach to K-12 science education that will capture students' interest and provide them with the necessary foundational knowledge in the field. A Framework for K-12 Science Education outlines a broad set of expectations for students in science and engineering in grades K-12. These expectations will inform the development of new standards for K-12 science education and, subsequently, revisions to curriculum, instruction, assessment, and professional development for educators. This book identifies three dimensions that convey the core ideas and practices around which science and engineering education in these grades should be built. These three dimensions are: crosscutting concepts that unify the study of science through their common application across science and engineering; scientific and engineering practices; and disciplinary core ideas in the physical sciences, life sciences, and earth and space sciences and for engineering, technology, and the applications of science. The overarching goal is for all high school graduates to have sufficient knowledge of science and engineering to engage in public discussions on science-related issues, be careful consumers of scientific and technical information, and enter the careers of their choice. A Framework for K-12 Science Education is the first step in a process that can inform state-level decisions and achieve a research-grounded basis for improving science instruction and learning across the country. The book will guide standards developers, teachers, curriculum designers, assessment developers, state and district science administrators, and educators who teach science in informal environments. |
| data science summer programs for high school students: Money for Colleges Otto W. Buschgen, 1924 |
| data science summer programs for high school students: Pacesetters in Innovation United States. Office of Education, 1967 |
| data science summer programs for high school students: The Summer Slide Karl Alexander, Sarah Pitcock, Matthew C. Boulay, 2016 This book is an authoritative examination of summer learning loss, featuring original contributions by scholars and practitioners at the forefront of the movement to understand—and stem—the “summer slide.” The contributors provide an up-to-date account of what research has to say about summer learning loss, the conditions in low-income children’s homes and communities that impede learning over the summer months, and best practices in summer programming with lessons on how to strengthen program evaluations. The authors also show how information on program costs can be combined with student outcome data to inform future planning and establish program cost-effectiveness. This book will help policymakers, school administrators, and teachers in their efforts to close academic achievement gaps and improve outcomes for all students. Book Features: Empirical research on summer learning loss and efforts to counteract it. Original contributions by leading authorities. Practical guidance on best practices for implementing and evaluating strong summer programs. Recommendations for using program evaluations more effectively to inform policy. Contributors: Emily Ackman, Allison Atteberry, Catherine Augustine, Janice Aurini, Amy Bohnert, Geoffrey D. Borman, Claudia Buchmann, Judy B. Cheatham, Barbara Condliffe, Dennis J. Condron, Scott Davies, Douglas Downey, Ean Fonseca, Linda Goetze, Kathryn Grant, Amy Heard, Michelle K. Hosp, James S. Kim, Heather Marshall, Jennifer McCombs, Andrew McEachin, Dorothy McLeod, Joseph J. Merry, Emily Milne, Aaron M. Pallas, Sarah Pitcock, Alex Schmidt, Marc L. Stein, Paul von Hippel, Thomas G. White, Doris Terry Williams, Nicole Zarrett “A comprehensive look at what’s known about summer’s impact on learning and achievement. It is a wake-up call to policymakers and educators alike” —Jane Stoddard Williams, Chair, Horizons National “Provides the reader with everything they didn’t know about summer learning loss and also provides information on everything we do know about eliminating summer learning loss. Do your school a favor and read this book and then act upon what you have learned.” —Richard Allington, University of Tennessee |
| data science summer programs for high school students: The Science of Reading Margaret J. Snowling, Charles Hulme, 2008-04-15 The Science of Reading: A Handbook brings together state-of-the-art reviews of reading research from leading names in the field, to create a highly authoritative, multidisciplinary overview of contemporary knowledge about reading and related skills. Provides comprehensive coverage of the subject, including theoretical approaches, reading processes, stage models of reading, cross-linguistic studies of reading, reading difficulties, the biology of reading, and reading instruction Divided into seven sections:Word Recognition Processes in Reading; Learning to Read and Spell; Reading Comprehension; Reading in Different Languages; Disorders of Reading and Spelling; Biological Bases of Reading; Teaching Reading Edited by well-respected senior figures in the field |
| data science summer programs for high school students: Brave, Not Perfect Reshma Saujani, 2019-02-05 INTERNATIONAL BESTSELLER • Inspired by her popular TED Talk, the founder and CEO of Girls Who Code urges women to embrace imperfection and live a bolder, more authentic life. “A timely message for women of all ages: Perfection isn’t just impossible but, worse, insidious.”—Angela Duckworth, bestselling author of Grit Imagine if you lived without the fear of not being good enough. If you didn’t care how your life looked on Instagram. If you could let go of the guilt and stop beating yourself up for making human mistakes. Imagine if, in every decision you faced, you took the bolder path? As women, too many of us feel crushed under the weight of our own expectations. We run ourselves ragged trying to please everyone, pass up opportunities that scare us, and avoid rejection at all costs. There’s a reason we act this way, Saujani says. As girls, we were taught to play it safe. Well-meaning parents and teachers praised us for being quiet and polite, urged us to be careful so we didn’t get hurt, and steered us to activities at which we could shine. As a result, we grew up to be women who are afraid to fail. It’s time to stop letting our fears drown out our dreams and narrow our world, along with our chance at happiness. By choosing bravery over perfection, we can find the power to claim our voice, to leave behind what makes us unhappy, and to go for the things we genuinely, passionately want. Perfection may set us on a path that feels safe, but bravery leads us to the one we’re authentically meant to follow. In Brave, Not Perfect,Saujani shares powerful insights and practices to help us let go of our need for perfection and make bravery a lifelong habit. By being brave, not perfect, we can all become the authors of our best and most joyful life. |
| data science summer programs for high school students: Increasing Access to College William G. Tierney, Linda Serra Hagedorn, 2012-02-01 At a time when college enrollment rates for low income and under-represented students are far below those of non-minority students, policies and practices designed to increase access should be a priority for colleges, universities, high schools, and community agencies. Increasing Access to College examines pre-college enrichment programs that offer a specific and immediate remedy. |
| data science summer programs for high school students: The The Python Workshop Andrew Bird, Dr Lau Cher Han, Mario Corchero Jiménez, Graham Lee, Corey Wade, 2019-11-06 Learn the fundamentals of clean, effective Python coding and build the practical skills to tackle your own software development or data science projects Key FeaturesBuild key Python skills with engaging development tasks and challenging activitiesImplement useful algorithms and write programs to solve real-world problemsApply Python in realistic data science projects and create simple machine learning modelsBook Description Have you always wanted to learn Python, but never quite known how to start? More applications than we realize are being developed using Python because it is easy to learn, read, and write. You can now start learning the language quickly and effectively with the help of this interactive tutorial. The Python Workshop starts by showing you how to correctly apply Python syntax to write simple programs, and how to use appropriate Python structures to store and retrieve data. You'll see how to handle files, deal with errors, and use classes and methods to write concise, reusable, and efficient code. As you advance, you'll understand how to use the standard library, debug code to troubleshoot problems, and write unit tests to validate application behavior. You'll gain insights into using the pandas and NumPy libraries for analyzing data, and the graphical libraries of Matplotlib and Seaborn to create impactful data visualizations. By focusing on entry-level data science, you'll build your practical Python skills in a way that mirrors real-world development. Finally, you'll discover the key steps in building and using simple machine learning algorithms. By the end of this Python book, you'll have the knowledge, skills and confidence to creatively tackle your own ambitious projects with Python. What you will learnWrite clean and well-commented code that is easy to maintainAutomate essential day-to-day tasks with Python scriptsDebug logical errors and handle exceptions in your programsExplore data science fundamentals and create engaging visualizationsGet started with predictive machine learningKeep your development process bug-free with automated testingWho this book is for This book is designed for anyone who is new to the Python programming language. Whether you're an aspiring software engineer or data scientist, or are just curious about learning how to code with Python, this book is for you. No prior programming experience is required. |
| data science summer programs for high school students: National Plant Genome Initiative National Science and Technology Council (U.S.). Interagency Working Group on Plant Genomes, 2001 |
| data science summer programs for high school students: Stuck in the Shallow End, updated edition Jane Margolis, 2017-03-03 Why so few African American and Latino/a students study computer science: updated edition of a book that reveals the dynamics of inequality in American schools. The number of African Americans and Latino/as receiving undergraduate and advanced degrees in computer science is disproportionately low. And relatively few African American and Latino/a high school students receive the kind of institutional encouragement, educational opportunities, and preparation needed for them to choose computer science as a field of study and profession. In Stuck in the Shallow End, Jane Margolis and coauthors look at the daily experiences of students and teachers in three Los Angeles public high schools: an overcrowded urban high school, a math and science magnet school, and a well-funded school in an affluent neighborhood. They find an insidious “virtual segregation” that maintains inequality. The race gap in computer science, Margolis discovers, is one example of the way students of color are denied a wide range of occupational and educational futures. Stuck in the Shallow End is a story of how inequality is reproduced in America—and how students and teachers, given the necessary tools, can change the system. Since the 2008 publication of Stuck in the Shallow End, the book has found an eager audience among teachers, school administrators, and academics. This updated edition offers a new preface detailing the progress in making computer science accessible to all, a new postscript, and discussion questions (coauthored by Jane Margolis and Joanna Goode). |
| data science summer programs for high school students: Behavioral Neurogenetics John F. Cryan, Andreas Reif, 2012-05-04 This book covers a wide array of topics relevant to behavioral genetics from both a preclinical and clinical standpoint. Indeed in juxtaposing both areas of research the reader will appreciate the true translational nature of the field. Topics covered range from technical advances in genetic analysis in humans and animals to specific descriptions of advances in schizophrenia, attention disorders, depression and anxiety disorders, autism, aggression, neurodegeneration and neurodevelopmental disorders. The importance of gene-environment interactions is emphasised and the role of neuroimaging in unravelling the functional consequences of genetic variability described. This volume will be valued by both the basic scientist and clinician alike who may use it as a detailed reference book. It will also be of use to the novice to the field, to whom it will serve as an in-depth introduction to this exciting area of research. |
| data science summer programs for high school students: Environmental Health Perspectives , 2006-08 |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
