Products related to Data:
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Knowledge Guided Machine Learning : Accelerating Discovery using Scientific Knowledge and Data
Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines.Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of limited training data and generalize to unseen scenarios.As a result, there is a growing interest in the scientific community on creating a new generation of methods that integrate scientific knowledge in ML frameworks.This emerging field, called scientific knowledge-guided ML (KGML), seeks a distinct departure from existing "data-only" or "scientific knowledge-only" methods to use knowledge and data at an equal footing.Indeed, KGML involves diverse scientific and ML communities, where researchers and practitioners from various backgrounds and application domains are continually adding richness to the problem formulations and research methods in this emerging field.Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data provides an introduction to this rapidly growing field by discussing some of the common themes of research in KGML using illustrative examples, case studies, and reviews from diverse application domains and research communities as book chapters by leading researchers.KEY FEATURES First-of-its-kind book in an emerging area of research that is gaining widespread attention in the scientific and data science fields Accessible to a broad audience in data science and scientific and engineering fields Provides a coherent organizational structure to the problem formulations and research methods in the emerging field of KGML using illustrative examples from diverse application domains Contains chapters by leading researchers, which illustrate the cutting-edge research trends, opportunities, and challenges in KGML research from multiple perspectives Enables cross-pollination of KGML problem formulations and research methods across disciplines Highlights critical gaps that require further investigation by the broader community of researchers and practitioners to realize the full potential of KGML
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Pragmatist Philosophy for Critical Knowledge, Learning and Consciousness : A New Epistemological Framework for Education
Emerging from the confusion and chaos of neoliberal economic systems around the world, this book brings together a collection of major philosophical ideas from previous centuries and applies them to the practice of education.The book argues that pragmatist philosophy is the most appropriate to guide the organisation of curriculum, pedagogy and assessment.It outlines a number of philosophical dilemmas, exploring these in relation to particular philosophers and offers philosophical insights for educational practice.Further, the book proposes Critical Praxis Bricolage, an epistemological framework articulating a view that education practices are embedded in a social context.This reshapes formal education from being dominated by the market forces of neoliberalism, into a way of ethical life that respects the dignity and knowledgeability of each person and community regardless of background.Written in a narrative style, Pragmatist Philosophy for Critical Knowledge, Learning and Consciousness provides a philosophical paradigm of experience, culture and inquiry that actively connects with human interests of the everyday and with the distinctiveness of being human.This work will be of interest to researchers and higher degree students of education and philosophy of education.
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Constructing Pragmatist Knowledge : Education, Philosophy and Social Emancipation
Constructing Pragmatist Knowledge reintroduces an explicit and systematic philosophical approach to education through American Pragmatism, expanding and detailing the practice of pragmatism itself for practitioners across various fields of social action.While a number of theorists are referenced, it focuses on the work of the original pragmatists Charles Sanders Peirce, William James, John Dewey, George Herbert Mead and Jane Addams.It is written in a narrative style and connects personal and professional experience of the author with philosophical description, analysis and explanation.Major themes of pragmatism are encountered throughout involving knowledge, experience, inquiry, social acts, dialectic and contradiction, giving rise to human constructs of values, moral conduct and bricolage.Reintroducing pragmatism and epistemology as the focus of teaching and learning heralds revolutionary and democratic change for education systems worldwide and corrects neoliberal tendencies that impose anti-educational ideological, economic and political distortions.This book will be of interest to academics, graduate students, teachers and pre-service teachers, policy makers and researchers in education, philosophy, sociology and epistemology.
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Improving Equity in Data Science : Re-Imagining the Teaching and Learning of Data in K-16 Classrooms
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.
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What contribution does philosophy education make to learning about morality?
Philosophy education plays a crucial role in helping individuals explore and understand different ethical theories and perspectives on morality. By engaging with philosophical texts and debates, students are encouraged to think critically about moral issues, develop their own ethical reasoning skills, and reflect on their values and beliefs. This process of philosophical inquiry can deepen one's understanding of complex moral dilemmas, foster empathy and open-mindedness, and ultimately contribute to the development of a more informed and ethical decision-making process.
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Is this wisdom teaching correct?
Wisdom teachings are subjective and can vary depending on individual beliefs and perspectives. It is important to consider the context and source of the teaching before determining its correctness. It is advisable to critically analyze the teaching, reflect on its relevance to your own life, and consider seeking guidance from trusted sources or mentors to gain a well-rounded understanding. Ultimately, the correctness of a wisdom teaching is a personal interpretation that may resonate differently with each individual.
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Should one learn teaching before teaching learning?
It is important to have a solid understanding of teaching methods and strategies before embarking on the journey of teaching others. Learning how to effectively communicate information, engage students, and assess their understanding are essential skills that can be acquired through formal education or training in teaching. By learning teaching techniques first, one can better support the learning process and create a more effective and engaging learning environment for their students.
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How does philosophy gain new knowledge?
Philosophy gains new knowledge through critical thinking, analysis, and reflection on existing ideas and concepts. Philosophers engage in dialogue and debate, challenging and expanding upon established theories and beliefs. They also draw from other disciplines such as science, psychology, and sociology to inform their inquiries and develop new insights. By questioning assumptions and exploring different perspectives, philosophy continues to evolve and generate new knowledge.
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The Feedback Loop : Using Formative Assessment Data for Science Teaching and Learning
What really helps your students learn science: Labs?Group work? Certain types of problems or test questions? Something you never even thought about? Find out with data that go way beyond what standardized test scores tell you.The Feedback Loop describes a process by which you design formative assessments of what you do and collect a variety of forms of data.Then, the book shows you ways to actually use the information to improve your teaching. Drawing on research-based findings and the experiences of both new and veteran classroom teachers, the guide offers practical ideas for middle and high school teachers, regardless of discipline.The first chapters introduce the Feedback Loop framework; highlight the four elements of goals, tools, data, and inferences; and explore how to close the loop by connecting inferences and goals through feedback.Later chapters show how to use the full loop to inform your instruction.The book supports the Next Generation Science Standards and includes classroom vignettes that ground the ideas in real-life situations.Meant to illuminate without overwhelming you, The Feedback Loop’s data-driven approach will support student learning and help strengthen your teaching practice in your very next lesson or unit.
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Understanding Teaching and Learning in Primary Education
This textbook gives you guidance and insights into the knowledge, values and commitments necessary to succeed in the primary classroom, supported by links to theory and research literature and realistic scenarios you may encounter as a new teacher. Fully updated throughout, key features of this second edition include:· A new chapter on inclusive education· Newly expanded coverage of digital learning, engaging with educational research and the role of the primary teacher· New ‘View from Practice’ examples· Cross-referenced links to the Teachers’ Standards in England and the GTCS Professional Standards in Scotland and where they are covered within the bookThis is essential reading for professional studies modules on primary initial teacher education courses, including university-based (PGCE, PGDE, BA QTS, BEd), school-based (SCITT, School Direct) and employment-based routes into teaching.
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Higher Education Teaching & Learning Space Design Guide
This book is essential reading for teaching staff and librarians to assist them in briefing the project design teams.It should also be a reference book for architects and interior designers.Student's need for social learning, collaborative and interactive facilities have had the greatest impact on the design of new teaching and learning spaces.The author, Brian Griffin, Architect researched this subject over many years and has included a large number of international Case Studies of successful designs.He is also the author of 'Laboratory Design Guide' 3rd Ed 2012 Routledge.
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Education, Teaching, and Learning : Discourses, Cultures, Conversations
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Does this wisdom teaching hold true?
Yes, this wisdom teaching holds true as it emphasizes the importance of being mindful of our thoughts and actions. By being aware of our intentions and choosing to act with kindness and compassion, we can create positive outcomes for ourselves and others. This teaching encourages us to cultivate a mindset of positivity and mindfulness, which can lead to a more fulfilling and harmonious life.
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Is the Apriori algorithm associated with machine learning or data mining?
The Apriori algorithm is associated with data mining. It is a classic algorithm used for association rule mining in large datasets. It is specifically used to identify frequent itemsets in transactional databases. While it is often used in the context of machine learning tasks, its primary application is in data mining for discovering patterns and relationships in data.
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Are data science and machine learning just trends from AI hype?
Data science and machine learning are not just trends from AI hype, but rather essential fields that have become increasingly important in various industries. Data science involves extracting insights and knowledge from data, while machine learning focuses on developing algorithms that can learn from and make predictions based on data. Both fields have proven to be valuable in solving complex problems and making data-driven decisions, making them more than just passing trends from AI hype.
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Does anyone have experience with further education in data analysis?
Yes, I have experience with further education in data analysis. I have completed a certification program in data analysis and have also taken advanced courses in statistics, programming, and data visualization. This education has provided me with the skills and knowledge necessary to work with large datasets, perform complex analysis, and communicate insights effectively. I have also gained practical experience through projects and internships, which have further solidified my understanding of data analysis concepts and techniques.
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