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Foundations of Computational Mathematics: Selected Papers of a Conference Held at Rio de Janeiro, January 1997

This book contains a collection of articles corresponding to some of the talks delivered at the Foundations of Computational Mathematics conference held at IMPA in Rio de Janeiro in January 1997. Some ofthe others are published in the December 1996 issue of the Journal of Complexity. Both of these publications were available and distributed at the meeting. Even in this aspect we hope to have achieved a synthesis of the mathematics and computer science cultures as well as of the disciplines. The reaction to the Park City meeting on Mathematics of Numerical Analy­ sis: Real Number Algorithms which was chaired by Steve Smale and had around 275 participants, was very enthusiastic. At the suggestion of Narendra Karmar­ mar a lunch time meeting of Felipe Cucker, Arieh Iserles, Narendra Karmarkar, Jim Renegar, Mike Shub and Steve Smale decided to try to hold a periodic meeting entitled "Foundations of Computational Mathematics" and to form an organization with the same name whose primary purpose will be to hold the meeting. This is then the first edition of FoCM as such. It has been organized around a small collection of workshops, namely - Systems of algebraic equations and computational algebraic geometry - Homotopy methods and real machines - Information-based complexity - Numerical linear algebra - Approximation and PDEs - Optimization - Differential equations and dynamical systems - Relations to computer science - Vision and related computational tools There were also twelve plenary speakers.

Foundations of Computer Security

Anyone with a computer has heard of viruses, had to deal with several, and has been struggling with spam, spyware, and disk crashes. This book is intended as a starting point for those familiar with basic concepts of computers and computations and who would like to extend their knowledge into the realm of computer and network security. Its comprehensive treatment of all the major areas of computer security aims to give readers a complete foundation in the field of Computer Security. Exercises are given throughout the book and are intended to strengthening the reader’s knowledge - answers are also provided. Written in a clear, easy to understand style, aimed towards advanced undergraduates and non-experts who want to know about the security problems confronting them everyday. The technical level of the book is low and requires no mathematics, and only a basic concept of computers and computations. Foundations of Computer Security will be an invaluable tool for students and professionals alike.

Foundations of Computer Software: Modeling, Development, and Verification of Adaptive Systems 16th Monterey Workshop 2010, Redmond, USA, WA, USA, March 31--April 2, Revised Selected Papers (Lecture Notes in Computer Science #6662)

This book presents the thoroughly refereed and revised post-workshop proceedings of the 16th Monterey Workshop, held in Redmond, WA, USA, in March/April 2010. The theme of the workshop was Foundations of Computer Software, with a special focus on Modeling, Development, and Verification of Adaptive Systems. The 13 revised full papers presented were carefully reviewed and selected from numerous submissions for inclusion in the book. The contributions show how the foundations and development techniques of computer software could be adapted even for industrial safety-critical and business-critical applications to improve dependability and robustness and to ensure information privacy and security.

Foundations of Computer Software: 15th Monterey Workshop 2008, Budapest, Hungary, September 24-26, 2008, Revised Selected Papers (Lecture Notes in Computer Science #6028)

Foundations of Computer Technology

Foundations of Computer Technology is an easily accessible introduction to the architecture of computers and peripherals. This textbook clearly and completely explains modern computer systems through an approach that integrates components, systems, software, and design. It provides a succinct, systematic, and readable guide to computers, providing a springboard for students to pursue more detailed technology subjects.This volume focuses on hardware elements within a computer system and the impact of software on its architecture. It discusses practical aspects of computer organization (structure, behavior, and design) delivering the necessary fundamentals for electrical engineering and computer science students. The book not only lists a wide range of terms, but also explains the basic operations of components within a system, aided by many detailed illustrations. Material on modern technologies is combined with a historical perspective, delivering a range of articles on hardware, architecture and software, programming methodologies, and the nature of operating systems. It also includes a unified treatment on the entire computing spectrum, ranging from microcomputers to supercomputers.Each section features learning objectives and chapter outlines. Small glossary entries define technical terms and each chapter ends with an alphabetical list of key terms for reference and review. Review questions also appear at the end of each chapter and project questions inspire readers to research beyond the text. Short, annotated bibliographies direct students to additional useful reading.

Foundations of Computer Technology

Foundations of Computer Technology is an easily accessible introduction to the architecture of computers and peripherals. This textbook clearly and completely explains modern computer systems through an approach that integrates components, systems, software, and design. It provides a succinct, systematic, and readable guide to computers, providing a springboard for students to pursue more detailed technology subjects.This volume focuses on hardware elements within a computer system and the impact of software on its architecture. It discusses practical aspects of computer organization (structure, behavior, and design) delivering the necessary fundamentals for electrical engineering and computer science students. The book not only lists a wide range of terms, but also explains the basic operations of components within a system, aided by many detailed illustrations. Material on modern technologies is combined with a historical perspective, delivering a range of articles on hardware, architecture and software, programming methodologies, and the nature of operating systems. It also includes a unified treatment on the entire computing spectrum, ranging from microcomputers to supercomputers.Each section features learning objectives and chapter outlines. Small glossary entries define technical terms and each chapter ends with an alphabetical list of key terms for reference and review. Review questions also appear at the end of each chapter and project questions inspire readers to research beyond the text. Short, annotated bibliographies direct students to additional useful reading.

Foundations of Computer Vision: Computational Geometry, Visual Image Structures and Object Shape Detection (Intelligent Systems Reference Library #124)

This book introduces the fundamentals of computer vision (CV), with a focus on extracting useful information from digital images and videos. Including a wealth of methods used in detecting and classifying image objects and their shapes, it is the first book to apply a trio of tools (computational geometry, topology and algorithms) in solving CV problems, shape tracking in image object recognition and detecting the repetition of shapes in single images and video frames. Computational geometry provides a visualization of topological structures such as neighborhoods of points embedded in images, while image topology supplies us with structures useful in the analysis and classification of image regions. Algorithms provide a practical, step-by-step means of viewing image structures. The implementations of CV methods in Matlab and Mathematica, classification of chapter problems with the symbols (easily solved) and (challenging) and its extensive glossary of key words, examples and connections with the fabric of CV make the book an invaluable resource for advanced undergraduate and first year graduate students in Engineering, Computer Science or Applied Mathematics. It offers insights into the design of CV experiments, inclusion of image processing methods in CV projects, as well as the reconstruction and interpretation of recorded natural scenes.

Foundations of Constraint Satisfaction: Computation in Cognitive Science

Foundations of Constraint Satisfaction discusses the foundations of constraint satisfaction and presents algorithms for solving constraint satisfaction problems (CSPs). Most of the algorithms described in this book are explained in pseudo code, and sometimes illustrated with Prolog codes (to illustrate how the algorithms could be implemented).Comprised of 10 chapters, this volume begins by defining the standard CSP and the important concepts around it and presenting examples and applications of CSPs. The reader is then introduced to the main features of CSPs and CSP solving techniques (problem reduction, searching, and solution synthesis); some of the most important concepts related to CSP solving; and problem reduction algorithms. Subsequent chapters deal with basic control strategies of searching which are relevant to CSP solving; the significance of ordering the variables, values and compatibility checking in searching; specialized search techniques which gain their efficiency by exploiting problem-specific features; and stochastic search approaches (including hill climbing and connectionist approaches) for CSP solving. The book also considers how solutions can be synthesized rather than searched for before concluding with an analysis of optimization in CSPs.This monograph can be used as a reference by artificial intelligence (AI) researchers or as a textbook by students on advanced AI courses, and should also help knowledge engineers apply existing techniques to solve CSPs or problems which embed CSPs.

Foundations of Data Intensive Applications: Large Scale Data Analytics under the Hood

PEEK “UNDER THE HOOD” OF BIG DATA ANALYTICS The world of big data analytics grows ever more complex. And while many people can work superficially with specific frameworks, far fewer understand the fundamental principles of large-scale, distributed data processing systems and how they operate. In Foundations of Data Intensive Applications: Large Scale Data Analytics under the Hood, renowned big-data experts and computer scientists Drs. Supun Kamburugamuve and Saliya Ekanayake deliver a practical guide to applying the principles of big data to software development for optimal performance. The authors discuss foundational components of large-scale data systems and walk readers through the major software design decisions that define performance, application type, and usability. You???ll learn how to recognize problems in your applications resulting in performance and distributed operation issues, diagnose them, and effectively eliminate them by relying on the bedrock big data principles explained within. Moving beyond individual frameworks and APIs for data processing, this book unlocks the theoretical ideas that operate under the hood of every big data processing system. Ideal for data scientists, data architects, dev-ops engineers, and developers, Foundations of Data Intensive Applications: Large Scale Data Analytics under the Hood shows readers how to: Identify the foundations of large-scale, distributed data processing systems Make major software design decisions that optimize performance Diagnose performance problems and distributed operation issues Understand state-of-the-art research in big data Explain and use the major big data frameworks and understand what underpins them Use big data analytics in the real world to solve practical problems

Foundations of Data Intensive Applications: Large Scale Data Analytics under the Hood

PEEK “UNDER THE HOOD” OF BIG DATA ANALYTICS The world of big data analytics grows ever more complex. And while many people can work superficially with specific frameworks, far fewer understand the fundamental principles of large-scale, distributed data processing systems and how they operate. In Foundations of Data Intensive Applications: Large Scale Data Analytics under the Hood, renowned big-data experts and computer scientists Drs. Supun Kamburugamuve and Saliya Ekanayake deliver a practical guide to applying the principles of big data to software development for optimal performance. The authors discuss foundational components of large-scale data systems and walk readers through the major software design decisions that define performance, application type, and usability. You???ll learn how to recognize problems in your applications resulting in performance and distributed operation issues, diagnose them, and effectively eliminate them by relying on the bedrock big data principles explained within. Moving beyond individual frameworks and APIs for data processing, this book unlocks the theoretical ideas that operate under the hood of every big data processing system. Ideal for data scientists, data architects, dev-ops engineers, and developers, Foundations of Data Intensive Applications: Large Scale Data Analytics under the Hood shows readers how to: Identify the foundations of large-scale, distributed data processing systems Make major software design decisions that optimize performance Diagnose performance problems and distributed operation issues Understand state-of-the-art research in big data Explain and use the major big data frameworks and understand what underpins them Use big data analytics in the real world to solve practical problems

Foundations of Data Quality Management (Synthesis Lectures on Data Management)

Data quality is one of the most important problems in data management. A database system typically aims to support the creation, maintenance, and use of large amount of data, focusing on the quantity of data. However, real-life data are often dirty: inconsistent, duplicated, inaccurate, incomplete, or stale. Dirty data in a database routinely generate misleading or biased analytical results and decisions, and lead to loss of revenues, credibility and customers. With this comes the need for data quality management. In contrast to traditional data management tasks, data quality management enables the detection and correction of errors in the data, syntactic or semantic, in order to improve the quality of the data and hence, add value to business processes. While data quality has been a longstanding problem for decades, the prevalent use of the Web has increased the risks, on an unprecedented scale, of creating and propagating dirty data. This monograph gives an overview of fundamental issues underlying central aspects of data quality, namely, data consistency, data deduplication, data accuracy, data currency, and information completeness. We promote a uniform logical framework for dealing with these issues, based on data quality rules. The text is organized into seven chapters, focusing on relational data. Chapter One introduces data quality issues. A conditional dependency theory is developed in Chapter Two, for capturing data inconsistencies. It is followed by practical techniques in Chapter 2b for discovering conditional dependencies, and for detecting inconsistencies and repairing data based on conditional dependencies. Matching dependencies are introduced in Chapter Three, as matching rules for data deduplication. A theory of relative information completeness is studied in Chapter Four, revising the classical Closed World Assumption and the Open World Assumption, to characterize incomplete information in the real world. A data currency model is presented in Chapter Five, to identify the current values of entities in a database and to answer queries with the current values, in the absence of reliable timestamps. Finally, interactions between these data quality issues are explored in Chapter Six. Important theoretical results and practical algorithms are covered, but formal proofs are omitted. The bibliographical notes contain pointers to papers in which the results were presented and proven, as well as references to materials for further reading. This text is intended for a seminar course at the graduate level. It is also to serve as a useful resource for researchers and practitioners who are interested in the study of data quality. The fundamental research on data quality draws on several areas, including mathematical logic, computational complexity and database theory. It has raised as many questions as it has answered, and is a rich source of questions and vitality. Table of Contents: Data Quality: An Overview / Conditional Dependencies / Cleaning Data with Conditional Dependencies / Data Deduplication / Information Completeness / Data Currency / Interactions between Data Quality Issues

Foundations of Data Science Based Healthcare Internet of Things (SpringerBriefs in Applied Sciences and Technology)

This book offers a basic understanding of the Internet of Things (IoT), its design issues and challenges for healthcare applications. It also provides details of the challenges of healthcare big data, role of big data in healthcare and techniques, and tools for IoT in healthcare. This book offers a strong foundation to a beginner. All technical details that include healthcare data collection unit, technologies and tools used for the big data analytics implementation are explained in a clear and organized format.

Foundations of Data Science for Engineering Problem Solving (Studies in Big Data #94)

This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.

Foundations of Data Visualization

This is the first book that focuses entirely on the fundamental questions in visualization. Unlike other existing books in the field, it contains discussions that go far beyond individual visual representations and individual visualization algorithms. It offers a collection of investigative discourses that probe these questions from different perspectives, including concepts that help frame these questions and their potential answers, mathematical methods that underpin the scientific reasoning of these questions, empirical methods that facilitate the validation and falsification of potential answers, and case studies that stimulate hypotheses about potential answers while providing practical evidence for such hypotheses. Readers are not instructed to follow a specific theory, but their attention is brought to a broad range of schools of thoughts and different ways of investigating fundamental questions. As such, the book represents the by now most significant collective effort for gathering a large collection of discourses on the foundation of data visualization. Data visualization is a relatively young scientific discipline. Over the last three decades, a large collection of computer-supported visualization techniques have been developed, and the merits and benefits of using these techniques have been evidenced by numerous applications in practice. These technical advancements have given rise to the scientific curiosity about some fundamental questions such as why and how visualization works, when it is useful or effective and when it is not, what are the primary factors affecting its usefulness and effectiveness, and so on. This book signifies timely and exciting opportunities to answer such fundamental questions by building on the wealth of knowledge and experience accumulated in developing and deploying visualization technology in practice.

Foundations of Deductive Databases and Logic Programming

Foundations of Deductive Databases and Logic Programming focuses on the foundational issues concerning deductive databases and logic programming.The selection first elaborates on negation in logic programming and towards a theory of declarative knowledge. Discussions focus on model theory of stratified programs, fixed point theory of nonmonotonic operators, stratified programs, semantics for negation in terms of special classes of models, relation between closed world assumption and the completed database, negation as a failure, and closed world assumption. The book then takes a look at negation as failure using tight derivations for general logic programs, declarative semantics of logic programs with negation, and declarative semantics of deductive databases and logic programs.The publication tackles converting AND-control to OR-control by program transformation, optimizing dialog, equivalences of logic programs, unification, and logic programming and parallel complexity. Topics include parallelism and structured and unstructured data, parallel algorithms and complexity, solving equations, most general unifiers, systems of equations and inequations, equivalences of logic programs, and optimizing recursive programs. The selection is a valuable source of data for researchers interested in pursuing further studies on the foundations of deductive databases and logic programming.

Foundations of Dependable Computing: Models and Frameworks for Dependable Systems (The Springer International Series in Engineering and Computer Science #283)

Foundations of Dependable Computing: Models and Frameworks for Dependable Systems presents two comprehensive frameworks for reasoning about system dependability, thereby establishing a context for understanding the roles played by specific approaches presented in this book's two companion volumes. It then explores the range of models and analysis methods necessary to design, validate and analyze dependable systems. A companion to this book (published by Kluwer), subtitled Paradigms for Dependable Applications, presents a variety of specific approaches to achieving dependability at the application level. Driven by the higher level fault models of Models and Frameworks for Dependable Systems, and built on the lower level abstractions implemented in a third companion book subtitled System Implementation, these approaches demonstrate how dependability may be tuned to the requirements of an application, the fault environment, and the characteristics of the target platform. Three classes of paradigms are considered: protocol-based paradigms for distributed applications, algorithm-based paradigms for parallel applications, and approaches to exploiting application semantics in embedded real-time control systems. Another companion book (published by Kluwer) subtitled System Implementation, explores the system infrastructure needed to support the various paradigms of Paradigms for Dependable Applications. Approaches to implementing support mechanisms and to incorporating additional appropriate levels of fault detection and fault tolerance at the processor, network, and operating system level are presented. A primary concern at these levels is balancing cost and performance against coverage and overall dependability. As these chapters demonstrate, low overhead, practical solutions are attainable and not necessarily incompatible with performance considerations. The section on innovative compiler support, in particular, demonstrates how the benefits of application specificity may be obtained while reducing hardware cost and run-time overhead.

Foundations of Dependable Computing: Paradigms for Dependable Applications (The Springer International Series in Engineering and Computer Science #284)

Foundations of Dependable Computing: Paradigms for Dependable Applications, presents a variety of specific approaches to achieving dependability at the application level. Driven by the higher level fault models of Models and Frameworks for Dependable Systems, and built on the lower level abstractions implemented in a third companion book subtitled System Implementation, these approaches demonstrate how dependability may be tuned to the requirements of an application, the fault environment, and the characteristics of the target platform. Three classes of paradigms are considered: protocol-based paradigms for distributed applications, algorithm-based paradigms for parallel applications, and approaches to exploiting application semantics in embedded real-time control systems. The companion volume subtitled Models and Frameworks for Dependable Systems presents two comprehensive frameworks for reasoning about system dependability, thereby establishing a context for understanding the roles played by specific approaches presented in this book's two companion volumes. It then explores the range of models and analysis methods necessary to design, validate and analyze dependable systems. Another companion book (published by Kluwer) subtitled System Implementation, explores the system infrastructure needed to support the various paradigms of Paradigms for Dependable Applications. Approaches to implementing support mechanisms and to incorporating additional appropriate levels of fault detection and fault tolerance at the processor, network, and operating system level are presented. A primary concern at these levels is balancing cost and performance against coverage and overall dependability. As these chapters demonstrate, low overhead, practical solutions are attainable and not necessarily incompatible with performance considerations. The section on innovative compiler support, in particular, demonstrates how the benefits of application specificity may be obtained while reducing hardware cost and run-time overhead.

Foundations of Dependable Computing: System Implementation (The Springer International Series in Engineering and Computer Science #285)

Foundations of Dependable Computing: System Implementation, explores the system infrastructure needed to support the various paradigms of Paradigms for Dependable Applications. Approaches to implementing support mechanisms and to incorporating additional appropriate levels of fault detection and fault tolerance at the processor, network, and operating system level are presented. A primary concern at these levels is balancing cost and performance against coverage and overall dependability. As these chapters demonstrate, low overhead, practical solutions are attainable and not necessarily incompatible with performance considerations. The section on innovative compiler support, in particular, demonstrates how the benefits of application specificity may be obtained while reducing hardware cost and run-time overhead. A companion to this volume (published by Kluwer) subtitled Models and Frameworks for Dependable Systems presents two comprehensive frameworks for reasoning about system dependability, thereby establishing a context for understanding the roles played by specific approaches presented in this book's two companion volumes. It then explores the range of models and analysis methods necessary to design, validate and analyze dependable systems. Another companion to this book (published by Kluwer), subtitled Paradigms for Dependable Applications, presents a variety of specific approaches to achieving dependability at the application level. Driven by the higher level fault models of Models and Frameworks for Dependable Systems, and built on the lower level abstractions implemented in a third companion book subtitled System Implementation, these approaches demonstrate how dependability may be tuned to the requirements of an application, the fault environment, and the characteristics of the target platform. Three classes of paradigms are considered: protocol-based paradigms for distributed applications, algorithm-based paradigms for parallel applications, and approaches to exploiting application semantics in embedded real-time control systems.

Foundations of Digital Government: Leading and Managing in the Digital Era (Springer Texts in Business and Economics)

Digital government consists in the purposeful use of information and communication technologies (ICT), in particular the internet, to transform the relationship between government and society in a positive manner. This book focuses on the current status, prospects and foundations of digital government. Integrating examples and cases from administrative practice, it covers all important aspects of digital government management. Learning outcomes includeUnderstanding the implications of the internet for government and societyGaining deeper insights into the concept and opportunities of digital democracyUnderstanding the challenges of moving public services online

Foundations of Education: Problems and Possibilities in American Education

Foundations of Education is organized around the major problems facing contemporary American education. It offers a thorough, scholarly treatment of these problems from historical, philosophical, and sociological perspectives, bringing together relevant findings from those disciplines to analyze and illuminate a wide range of issues. Each chapter focuses on a core topic (including race, gender, equal opportunities, school governance) to give students a solid overview, providing intellectually sound material that offers real depth and challenges students to think creatively.Packed with exercises, discussion questions, international case studies for comparative purposes and supported by a fully up-to-date companion website, this is a text that responds to current developments, changes, and trends in teacher education. Foundations of Education will prepare a new generation of educators for a globalized and technology-driven society that needs to be aware of its best educational traditions, its current problems and its future possibilities.Â

Foundations of Education: Problems and Possibilities in American Education

Foundations of Education is organized around the major problems facing contemporary American education. It offers a thorough, scholarly treatment of these problems from historical, philosophical, and sociological perspectives, bringing together relevant findings from those disciplines to analyze and illuminate a wide range of issues. Each chapter focuses on a core topic (including race, gender, equal opportunities, school governance) to give students a solid overview, providing intellectually sound material that offers real depth and challenges students to think creatively.Packed with exercises, discussion questions, international case studies for comparative purposes and supported by a fully up-to-date companion website, this is a text that responds to current developments, changes, and trends in teacher education. Foundations of Education will prepare a new generation of educators for a globalized and technology-driven society that needs to be aware of its best educational traditions, its current problems and its future possibilities.

Foundations of Educational Technology: Integrative Approaches and Interdisciplinary Perspectives (Interdisciplinary Approaches to Educational Technology)

Foundations of Educational Technology offers a fresh, interdisciplinary, problem-centered approach to educational technology, learning design, and instructional systems development. As the implementation of online, blended, hybrid, mobile, open, and adaptive learning systems rapidly expands, emerging tools such as learning analytics, artificial intelligence, mixed realities, serious games, and micro-credentialing are promising more complex and personalized learning experiences. This book provides faculty and graduate students with a conceptual, empirical, and practical basis for the effective use of these systems across contexts, integrating essential theories from the fields of human performance, learning and development, information and communications, and instructional design. Key additions to this revised and expanded third edition include coverage of the latest learning technologies, research from educational neuroscience, discussions about security and privacy, new attention to diversity, equity, and inclusion, updated activities, support materials, references, and more.

Foundations of Educational Technology: Integrative Approaches and Interdisciplinary Perspectives (Interdisciplinary Approaches to Educational Technology)

Foundations of Educational Technology offers a fresh, interdisciplinary, problem-centered approach to educational technology, learning design, and instructional systems development. As the implementation of online, blended, hybrid, mobile, open, and adaptive learning systems rapidly expands, emerging tools such as learning analytics, artificial intelligence, mixed realities, serious games, and micro-credentialing are promising more complex and personalized learning experiences. This book provides faculty and graduate students with a conceptual, empirical, and practical basis for the effective use of these systems across contexts, integrating essential theories from the fields of human performance, learning and development, information and communications, and instructional design. Key additions to this revised and expanded third edition include coverage of the latest learning technologies, research from educational neuroscience, discussions about security and privacy, new attention to diversity, equity, and inclusion, updated activities, support materials, references, and more.

Foundations of Educational Technology: Integrative Approaches and Interdisciplinary Perspectives (Interdisciplinary Approaches to Educational Technology)

An engaging book for professional educators and an ideal textbook for certificate, masters, and doctoral programs in educational technology, instructional systems and learning design, Foundations of Educational Technology, Second Edition offers a fresh, interdisciplinary, problem-centered approach to the subject, helping students build extensive notes and an electronic portfolio as they navigate the text. The book addresses fundamental aspects of educational technology theory, research and practice that span various users, contexts and settings; includes a full range of engaging exercises for students that will contribute to their professional growth; and offers the following 4-step pedagogical features inspired by M. D. Merrill’s First Principles of Instruction: TELL: Primary presentations and pointers to major sources of information and resources ASK: Activities that encourage students to critique applications and share their individual interpretations SHOW: Activities that demonstrate the application of key concepts and complex skills with appropriate opportunities for learner responses DO: Activities in which learners apply key concepts and complex skills while working on practice assignments and/or projects to be created for their electronic portfolios The second edition of this textbook covers the core objectives addressed in introductory educational technology courses while adding new sections on mobile learning, MOOCs, open educational resources, "big data," and learning analytics along with suggestions to instructors and appendices on effective writing, professional associations, journal and trade magazines.

Foundations of Educational Technology: Integrative Approaches and Interdisciplinary Perspectives (Interdisciplinary Approaches to Educational Technology)

An engaging book for professional educators and an ideal textbook for certificate, masters, and doctoral programs in educational technology, instructional systems and learning design, Foundations of Educational Technology, Second Edition offers a fresh, interdisciplinary, problem-centered approach to the subject, helping students build extensive notes and an electronic portfolio as they navigate the text. The book addresses fundamental aspects of educational technology theory, research and practice that span various users, contexts and settings; includes a full range of engaging exercises for students that will contribute to their professional growth; and offers the following 4-step pedagogical features inspired by M. D. Merrill’s First Principles of Instruction: TELL: Primary presentations and pointers to major sources of information and resources ASK: Activities that encourage students to critique applications and share their individual interpretations SHOW: Activities that demonstrate the application of key concepts and complex skills with appropriate opportunities for learner responses DO: Activities in which learners apply key concepts and complex skills while working on practice assignments and/or projects to be created for their electronic portfolios The second edition of this textbook covers the core objectives addressed in introductory educational technology courses while adding new sections on mobile learning, MOOCs, open educational resources, "big data," and learning analytics along with suggestions to instructors and appendices on effective writing, professional associations, journal and trade magazines.