The Textbook and the Lecture


Book Description

Machine generated contents note: Preface Part I 1. No More Pencils, No More Books?2. Writing Instruction in the Twenty-First Century Part II 3. Psychology and the Rationalist4. The Romantic Tradition5. Romantic versus Rationalist Reform6. Theorizing Media--by the Book Part III 7. A Textbook Case8. From Translatio Studiorum to "Intelligences Thinking in Unison"9. The Lecture as Postmodern PerformanceConclusionNotesBibliography Index




Feynman's Lost Lecture


Book Description

"Glorious."—Wall Street Journal Rescued from obscurity, Feynman's Lost Lecture is a blessing for all Feynman followers. Most know Richard Feynman for the hilarious anecdotes and exploits in his best-selling books "Surely You're Joking, Mr. Feynman!" and "What Do You Care What Other People Think?" But not always obvious in those stories was his brilliance as a pure scientist—one of the century's greatest physicists. With this book and CD, we hear the voice of the great Feynman in all his ingenuity, insight, and acumen for argument. This breathtaking lecture—"The Motion of the Planets Around the Sun"—uses nothing more advanced than high-school geometry to explain why the planets orbit the sun elliptically rather than in perfect circles, and conclusively demonstrates the astonishing fact that has mystified and intrigued thinkers since Newton: Nature obeys mathematics. David and Judith Goodstein give us a beautifully written short memoir of life with Feynman, provide meticulous commentary on the lecture itself, and relate the exciting story of their effort to chase down one of Feynman's most original and scintillating lectures.




Lectures On Computation


Book Description

Covering the theory of computation, information and communications, the physical aspects of computation, and the physical limits of computers, this text is based on the notes taken by one of its editors, Tony Hey, on a lecture course on computation given b




The Art and Science of Lecture Demonstration


Book Description

As a means of conveying the excitement of science from one generation to the next, the lecture demonstration is one of the most powerful tools at the disposal of the modern science teacher. The interest of the young aspiring scientist is aroused not by dull textbook recitation, but by the enthusiastic lecturer with a range of demonstrations that illustrate the importance of science in the real world. In this lucid and entertaining book, Professor Taylor explores the origins of lecture demonstration and its development to the present day, emphasizing the underlying principles and the lessons to be learned. Set alongside the work of the most eminent of his predecessors, Michael Faraday and Lawrence Bragg, Taylor's book should find a worthy place among the literature of popular science. The Art and Science of Lecture Demonstration will be useful to all those with a serious amateur or professional interest in the teaching of science, from primary school to university and beyond.




Lecture Ready Second Edition 1: Student Book


Book Description

Through the use of realistic and engaging lectures, Lecture Ready Second Edition prepares students for the demands and atmosphere of the higher-education classroom. Note-taking strategies focus on accurate and concise recording of class material. Academic discussion strategies help students participate fully and smoothly in classroom discussions. Students are more competent and confident when they learn how to present using proven strategies for academic success. These strategies help students meet their presentation challenges in and beyond the language classroom.




Effective Study


Book Description




How To Take Good Notes


Book Description

"Why would I need a book on how to take notes? Notes are just notes!" -- FALSE. Scientists have found that note taking can be as mentally demanding as playing chess can be for an expert. While you take notes, you listen carefully to the lecturer, you process the new material, you organize it in your working memory, and you finally write down what you think is most important. All this happens while someone is talking at an average speed of three words per second and someone is writing down at an average speed of one-third of a word per second. It doesn't sound easy now, does it? Notes are an important tool for learning. We don't take notes just to record a few facts so we can review them later. Learning happens as we take notes. Taking notes the right way leads to good study practices, better performance on exams, and long-term retention of information. "Note taking comes naturally." FALSE. Note taking is not obvious or intuitive. Research has shown that students fail to capture 40% of the main points in a typical lecture. First-year students capture only 11%. In some studies, even the best note takers seem to record less than 75% of the important information. People think they take good notes until they're told they don't. Few of us have consciously thought about how we take notes (let alone how to improve the quality of them). We often reproduce the lecturer's phrases verbatim. We don't save time by systematic use of abbreviations. We fail to become a "good psychologist" of our lecturer. We fail to pick up his enthusiasm. We fail to interpret the tone of his voice. We fail to read his body language. And the result is that we fail to take good notes. "Anyway, no one taught me how to take notes in school or in college." TRUE. Educators believe that students are able to assess the quality of their notes and follow good practices. However, studies have shown the exact opposite. The fact that there isn't a course in college dedicated to the art of taking notes (or learning in general) makes students believe that this is a natural skill that they can perfect with practice over the course of their studies. "At the end of the day, everyone has their own way to take notes." TRUE. In this book, you may be surprised to learn that I don't make any references to different types of note-taking systems like those that other books do. The reason is that it's the practices behind the note taking that matter most. For example, you should not copy the lecturer's phrases word for word, but generate the main points in your own words. And you should leave space on your notes for adding comments and testing yourself later. I encourage students to use the Cornell note-taking system because it utilizes most of the principles of effective note taking. No matter which note-taking system you decide to follow, the cognitive effort you will have to expend is equally high. Note taking may not be rocket science, but it's definitely science-cognitive science. And cognitive science has produced a lot of useful insights that we can use now to take better notes. This book presents these insights in simple words, so you can make the most of your notes and use them to study effectively. The title of this book is How to take good notes. However, note taking is just one part of the picture. Note taking is much broader in the context of this book. We take notes so we can interact with them later. What matters most is what we do with our notes after we finish taking them. Notes can do so many good things for you. They hold all your learning efforts. Treat them well. Look after them.




The Algebra of Happiness


Book Description

An unconventional book of wisdom and life advice from renowned business school professor and New York Times bestselling author of The Four Scott Galloway. Scott Galloway teaches brand strategy at NYU's Stern School of Business, but his most popular lectures deal with life strategy, not business. In the classroom, on his blog, and in YouTube videos garnering millions of views, he regularly offers hard-hitting answers to the big questions: What's the formula for a life well lived? How can you have a meaningful career, not just a lucrative one? Is work/life balance possible? What are the elements of a successful relationship? The Algebra of Happiness: Notes on the Pursuit of Success, Love, and Meaning draws on Professor Galloway's mix of anecdotes and no-BS insight to share hard-won wisdom about life's challenges, along with poignant personal stories. Whether it's advice on if you should drop out of school to be an entrepreneur (it might have worked for Steve Jobs, but you're probably not Steve Jobs), ideas on how to position yourself in a crowded job market (do something "boring" and move to a city; passion is for people who are already rich), discovering what the most important decision in your life is (it's not your job, your car, OR your zip code), or arguing that our relationships to others are ultimately all that matter, Galloway entertains, inspires, and provokes. Brash, funny, and surprisingly moving, The Algebra of Happiness represents a refreshing perspective on our need for both professional success and personal fulfillment, and makes the perfect gift for any new graduate, or for anyone who feels adrift.




Deep Learning


Book Description

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.




The Book of Eli


Book Description

The only book you will need to pass the NY state EMT course