Studying Science Second Edition
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| Author | : Pauline Millican |
| Publisher | : Scion Publishing Ltd |
| Total Pages | : 161 |
| Release | : 2018-09-21 |
| Genre | : Study Aids |
| ISBN | : 1911510312 |
Those starting a science degree at university will want to get the most out of their studies and do well. University is a big jump from school, but this book will help new students to cope with the transition. It will help the reader get the most out of lectures, tutorials and practicals, show how to read effectively and how best to work as part of a team. It explains how to use library databases, find reliable web resources, avoid problems with plagiarism, etc., etc. Discover the best learning strategies and learn how to present work for maximum marks; find out the best revision and exam techniques. Studying Science covers all of this and more: How to study effectively at university and make the most of teaching Making the best use of VLEs Presenting work well, including using information technology Revision and examinations Taking a year out The final year and preparation of first job applications PLUS, it has a brand new appendix showing how to make the most of the computer programs that will be used to prepare essays, analyse data, and deliver presentations – with lots of hints and tips for Word, Excel, PowerPoint and Access.
| Author | : Pauline Millican |
| Publisher | : Scion Publishing |
| Total Pages | : 0 |
| Release | : 2014 |
| Genre | : Science |
| ISBN | : 9781907904509 |
This revised edition of an invaluable handbook introduces new undergraduate bioscience students to the skills needed to succeed in the Life Sciences at University.
| Author | : James M. Lang |
| Publisher | : John Wiley & Sons |
| Total Pages | : 272 |
| Release | : 2016-03-07 |
| Genre | : Education |
| ISBN | : 1118944496 |
Employ cognitive theory in the classroom every day Research into how we learn has opened the door for utilizing cognitive theory to facilitate better student learning. But that's easier said than done. Many books about cognitive theory introduce radical but impractical theories, failing to make the connection to the classroom. In Small Teaching, James Lang presents a strategy for improving student learning with a series of modest but powerful changes that make a big difference—many of which can be put into practice in a single class period. These strategies are designed to bridge the chasm between primary research and the classroom environment in a way that can be implemented by any faculty in any discipline, and even integrated into pre-existing teaching techniques. Learn, for example: How does one become good at retrieving knowledge from memory? How does making predictions now help us learn in the future? How do instructors instill fixed or growth mindsets in their students? Each chapter introduces a basic concept in cognitive theory, explains when and how it should be employed, and provides firm examples of how the intervention has been or could be used in a variety of disciplines. Small teaching techniques include brief classroom or online learning activities, one-time interventions, and small modifications in course design or communication with students.
| Author | : Edward Watson |
| Publisher | : Taylor & Francis |
| Total Pages | : 251 |
| Release | : 2021-04-28 |
| Genre | : Education |
| ISBN | : 1000371670 |
Supporting teachers in the quest to help students learn as effectively and efficiently as possible, The Science of Learning translates 99 of the most important and influential studies on the topic of learning into accessible and easily digestible overviews. Building on the bestselling original book, this second edition delves deeper into the world of research into what helps students learn, with 22 new studies covering key issues including cognitive-load theory, well-being and performing well under exam pressure. Demystifying key concepts and translating research into practical advice for the classroom, this unique resource will increase teachers’ understanding of crucial psychological research so they can help students improve how they think, feel and behave in school. From large- to small-scale studies, from the quirky to the iconic, the book breaks down complicated research to provide teachers with the need-to-know facts and implications of each study. Each overview combines graphics and text, asks key questions, describes related research and considers implications for practice. Highly accessible, each overview is attributed to one of seven key categories: Memory: increasing how much students remember Mindset, motivation and resilience: improving persistence, effort and attitude Self-regulation and metacognition: helping students to think clearly and consistently Student behaviours: encouraging positive student habits and processes Teacher attitudes, expectations and behaviours: adopting positive classroom practices Parents: how parents’ choices and behaviours impact their childrens’ learning Thinking biases: avoiding faulty thinking habits that get in the way of learning A hugely accessible resource, this unique book will support, inspire and inform teaching staff, parents and students, and those involved in leadership and CPD.
| Author | : Lori Fulton |
| Publisher | : Heinemann Educational Books |
| Total Pages | : 0 |
| Release | : 2014 |
| Genre | : Education |
| ISBN | : 9780325056593 |
The bestselling first edition of Science Notebooks inspired thousands of teachers to use science notebooks as a powerful way to help students reveal and develop their thinking about scientific concepts, engage in the work of scientists and engineers, and exercise language skills. Lori Fulton and Brian Campbell make the Second Edition even more valuable by showing how science notebooks support implementation of the Next Generation Science Standards as well as the Common Core State Standards for ELA. The authors have also added new material to every chapter, including: strategies to scaffold science notebook instruction how science notebooks help students develop explanations and arguments based on evidence strategies for collecting and analyzing science notebooks for formative assessment new interviews with scientists and engineers that spotlight the use of science notebooks in their work. Student samples and classroom vignettes from a variety of settings illustrate the transformative effect of science notebooks on students' scientific thinking as well as their literacy skills. Download a sample chapter
| Author | : Page Keeley |
| Publisher | : Corwin |
| Total Pages | : 353 |
| Release | : 2019-09-11 |
| Genre | : Education |
| ISBN | : 1071800051 |
Today’s science standards reflect a new vision of teaching and learning. | How to make this vision happen Scientific literacy for all students requires a deep understanding of the three dimensions of science education: disciplinary content, scientific and engineering practices, and crosscutting concepts. If you actively engage students in using and applying these three dimensions within curricular topics, they will develop a scientifically-based and coherent view of the natural and designed world. The latest edition of this best-seller, newly mapped to the Framework for K-12 Science Education and the Next Generation Science Standards (NGSS), and updated with new standards and research-based resources, will help science educators make the shifts needed to reflect current practices in curriculum, instruction, and assessment. The methodical study process described in this book will help readers intertwine content, practices, and crosscutting concepts. The book includes: • An increased emphasis on STEM, including topics in science, technology, and engineering • 103 separate curriculum topic study guides, arranged in six categories • Connections to content knowledge, curricular and instructional implications, concepts and specific ideas, research on student learning, K-12 articulation, and assessment Teachers and those who support teachers will appreciate how Curriculum Topic Study helps them reliably analyze and interpret their standards and translate them into classroom practice, thus ensuring that students achieve a deeper understanding of the natural and designed world.
| Author | : Page Keeley |
| Publisher | : Corwin Press |
| Total Pages | : 321 |
| Release | : 2005-02-23 |
| Genre | : Education |
| ISBN | : 1412908922 |
′Without question, this book will be of great value to the profession of science teaching. Given today′s educational landscape of standards and high-stakes testing, curriculum topic study is an essential piece of the puzzle′ - Cary Sneider, Vice President for Educator Programs, Museum of Science, Boston Discover the "missing link" between science standards, teacher practice, and improved student achievement! Becoming an accomplished science teacher not only requires a thorough understanding of science content, but also a familiarity with science standards and research on student learning. However, a comprehensive strategy for translating standards and research into instructional, practice has been lacking since the advent of standards-based education reform. Science Curriculum Topic Study provides a systematic professional development strategy that links science standards and research to curriculum, instruction, and assessment. Developed by author Page Keeley of the Maine Mathematics and Science Alliance, the Curriculum Topic Study (CTS) process can help teachers align curriculum, instruction, and assessment with specific, research-based ideas and skills. The CTS process will help teachers: - Improve their understanding of science content - Clarify a hierarchy of content and skills in a learning goal from state or local standards - Define formative and summative assessment goals and strategies - Learn to recognize and address learning difficulties - Increase opportunities for students of all backgrounds to achieve science literacy - Design or utilize instructional materials effectively Containing 147 separate curriculum topic study guides arranged in eleven categories that represent the major domains of science, this book provides the tools to both positively impact student learning and develop the knowledge and skills that distinguish expert science teachers from novices.
| Author | : Mike Schmoker |
| Publisher | : ASCD |
| Total Pages | : 330 |
| Release | : 2018-07-16 |
| Genre | : Education |
| ISBN | : 1416626379 |
In this 2nd edition of Focus: Elevating the Essentials to Radically Improve Student Learning, Mike Schmoker extends and updates the case that our schools could be on the cusp of swift, unparalleled improvements. But we are stymied by a systemwide failure to simplify and prioritize; we have yet to focus our limited time and energy on the most essential, widely acknowledged, evidence-based practices that could have more impact than all other initiatives combined. They are: simple, coherent curricula; straightforward, traditional literacy practices; and lessons built around just a few hugely effective elements of good teaching. As Schmoker demonstrates, the case for these practices—and the need for them—has grown prodigiously. In every chapter, you’ll find late-breaking discoveries and practical advice on how to simplify the implementation of new state standards in the subject areas; on the hidden pitfalls of our most popular, but unproven instructional fads and programs; and on simple, versatile strategies for building curriculum, planning lessons, and integrating literacy into every discipline. All of these strategies and findings are supported with exciting new evidence from actual schools. Their success confirms, as Michael Fullan writes, that a focus on the best "high-leverage practices" won’t only improve student performance; they will produce "stunningly powerful consequences" in our schools.
| Author | : Gareth James |
| Publisher | : Springer Nature |
| Total Pages | : 617 |
| Release | : 2023-08-01 |
| Genre | : Mathematics |
| ISBN | : 3031387473 |
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
| Author | : Sebastian Raschka |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 455 |
| Release | : 2015-09-23 |
| Genre | : Computers |
| ISBN | : 1783555149 |
Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
