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The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
Stanford mathematician and NPR Math Guy Keith Devlin explains why, fun aside, video games are the ideal medium to teach middle-school math. Aimed primarily at teachers and education researchers, but also of interest to game developers who want to produce videogames for mathematics education, Mathematics Education for a New Era: Video Games as a Med
Active engagement is the key to learning. You want your students doing something that stimulates them to ask questions and creates a need to know. Teaching Mathematics Through Games presents a variety of classroom-tested exercises and activities that provoke the active learning and curiosity that you hope to promote. These games run the gamut from well-known favorites like SET and Settlers of Catan to original games involving simulating structural inequality in New York or playing Battleship with functions. The book contains activities suitable for a wide variety of college mathematics courses, including general education courses, math for elementary education, probability, calculus, linear algebra, history of math, and proof-based mathematics. Some chapter activities are short term, such as a drop-in lesson for a day, and some are longer, including semester-long projects. All have been tested, refined, and include extensive implementation notes.
This monograph serves as a resource book on the Model Method. The main purpose is to make explicit how the Model Method is used to develop students' understanding of fundamental mathematics concepts and proficiency in solving basic mathematics word problems. Through the construction of a pictorial model to represent the known and unknown quantities and their relationships in a problem, students gain better understanding of the problem and develop their abilities in mathematical thinking and problem solving. This would provide a strong foundation for the learning of matheatics from the primary to secondary levels and beyond. This monograph also features the Mathematics Framework of the Singapore mathematics curriculum, and discusses the changes that it has undergone over the past two decades. These changes reflected the changing emphases, needs and challenges in the mathematics curriculum as we entered the 21s century.
During the last decade there were significant advances in the study of students' learning and problem solving in mathematics, and in the study of classroom instruction. Because these two research programs usually have been conducted individually, it is generally agreed now that there is an increasing need for an integrated research program. This book represents initial discussions and development of a unified paradigm for studying teaching in mathematics that builds upon both cognitive as well as instructional research.
This book examines the hows and whys of writing in mathematics.
This book examines the beliefs, attitudes, values and emotions of students in Years 5 to 8 (aged 10 to 14 years) about mathematics and mathematics education. Fundamentally, this book focuses on the development of affective views and responses towards mathematics and mathematics learning. Furthermore, it seems that students develop their more negative views of mathematics during the middle school years (Years 5 to 8), and so here we concentrate on students in this critical period. The book is based on a number of empirical studies, including an enquiry undertaken with 45 children in Years 5 and 6 in one school; a large-scale quantitative study undertaken with students from a range of schools across diverse communities in New Zealand; and two related small-scale studies with junior secondary students in Australia. This book brings substantial, empirically-based evidence to the widely held perception that many students have negative views of mathematics, and these affective responses develop during the middle years of school. The data for this book were collected with school students, and students who were actually engaged in learning mathematics in their crucial middle school years. The findings reported and discussed here are relevant for researchers and mathematics educators, policy makers and curriculum developers, and teachers and school principals engaged in the teaching of mathematics.
This topical survey focuses on research in tertiary mathematics education, a field that has experienced considerable growth over the last 10 years. Drawing on the most recent journal publications as well as the latest advances from recent high-quality conference proceedings, our review culls out the following five emergent areas of interest: mathematics teaching at the tertiary level; the role of mathematics in other disciplines; textbooks, assessment and students’ studying practices; transition to the tertiary level; and theoretical-methodological advances. We conclude the survey with a discussion of some potential directions for future research in this new and rapidly evolving domain of inquiry.
Selected as the Michigan Council of Teachers of Mathematics winter book club book! Rich tasks, collaborative work, number talks, problem-based learning, direct instruction...with so many possible approaches, how do we know which ones work the best? In Visible Learning for Mathematics, six acclaimed educators assert it’s not about which one—it’s about when—and show you how to design high-impact instruction so all students demonstrate more than a year’s worth of mathematics learning for a year spent in school. That’s a high bar, but with the amazing K-12 framework here, you choose the right approach at the right time, depending upon where learners are within three phases of learning: surface, deep, and transfer. This results in "visible" learning because the effect is tangible. The framework is forged out of current research in mathematics combined with John Hattie’s synthesis of more than 15 years of education research involving 300 million students. Chapter by chapter, and equipped with video clips, planning tools, rubrics, and templates, you get the inside track on which instructional strategies to use at each phase of the learning cycle: Surface learning phase: When—through carefully constructed experiences—students explore new concepts and make connections to procedural skills and vocabulary that give shape to developing conceptual understandings. Deep learning phase: When—through the solving of rich high-cognitive tasks and rigorous discussion—students make connections among conceptual ideas, form mathematical generalizations, and apply and practice procedural skills with fluency. Transfer phase: When students can independently think through more complex mathematics, and can plan, investigate, and elaborate as they apply what they know to new mathematical situations. To equip students for higher-level mathematics learning, we have to be clear about where students are, where they need to go, and what it looks like when they get there. Visible Learning for Math brings about powerful, precision teaching for K-12 through intentionally designed guided, collaborative, and independent learning.
Studies of teachers in the U.S. often document insufficient subject matter knowledge in mathematics. Yet, these studies give few examples of the knowledge teachers need to support teaching, particularly the kind of teaching demanded by recent reforms in mathematics education. Knowing and Teaching Elementary Mathematics describes the nature and development of the knowledge that elementary teachers need to become accomplished mathematics teachers, and suggests why such knowledge seems more common in China than in the United States, despite the fact that Chinese teachers have less formal education than their U.S. counterparts. The anniversary edition of this bestselling volume includes the original studies that compare U.S and Chinese elementary school teachers’ mathematical understanding and offers a powerful framework for grasping the mathematical content necessary to understand and develop the thinking of school children. Highlighting notable changes in the field and the author’s work, this new edition includes an updated preface, introduction, and key journal articles that frame and contextualize this seminal work.