It is surprising that there is so little research on textbooks, given their centrality to teaching and learning in elementary and secondary schools. Textbooks have become a focus of political and cultural controversy, advocating a multicultural curriculum that has sparked some vigorous protests. Research is absent in this debate; therefore, questions of legitimate knowledge, the role of textbooks, textbook design, policy selection issues, and economic issues concerning the marketplace are not part of the current debate. Without insights of research on considerate text, mentioning, illustrations and so forth, the current controversy will result in publishers responding to demands for more content not less; thus, textbooks will become compendia of information that on the surface satisfy everyone. This volume demonstrates how research on important issues relative to textbook design can advance our knowledge about what makes textbooks effective learning tools, and thus inform policymakers, publishers, and those involved in textbook selection. Representing pure and applied approaches, researchers present papers on the quality of writing, the role of questions, the role of pictures and illustrations, and the role of auxiliary materials in the design of effective textbooks. The chapters provide insight into research and its application to textbook design and improvement -- stimulating others to follow this lead.

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.

Come and explore the world under your feet with the Dirtmeister and friends! Part graphic novel, part fun guidebook, this very cool, rocky journey introduces both eager and reluctant readers to the basic geologic processes that shape our Earth. Clear and concise explanations of the various geologic processes reveal the comprehensive science behind each fascinating topic. Fun facts and simple DIY experiments reinforce the concepts while short biographies of important scientists inspire future geo-scientists.

In Powerful Learning, Linda Darling-Hammond and an impressive list of co-authors offer a clear, comprehensive, and engaging exploration of the most effective classroom practices. They review, in practical terms, teaching strategies that generate meaningful K–2 student understanding, and occur both within the classroom walls and beyond. The book includes rich stories, as well as online videos of innovative classrooms and schools, that show how students who are taught well are able to think critically, employ flexible problem-solving, and apply learned skills and knowledge to new situations.