TAILIEUCHUNG - Instructional Engineering in Networked Environments

FOR THE PAST SEVERAL DECADES instructors in the field of educational technology have focused on training instructional designers. A quick survey of graduate programs in this area indicates that the majority of the classes are geared toward instructional design from the viewpoint of learning psychology or from the viewpoint of using multimedia tools for the latest technological advances. Courses have emphasized a systematic approach to the development of instructional products usually consisting of various approaches to analysis, design, development, implementation, and evaluation. The assumption, especially at the master’s degree level, is that the graduates of these programs will find jobs that require these newly acquired skills in developing instructional products | Wei f for fssential resources for training and Hi Instructional Technology Training Series Instructional Engineering in Networked Environments GILBERT PAQUETTE About This Book Why is this topic important The Internet now ubiquitously present in our lives gives us all access to a major part of human knowledge. With a simple click of a mouse we can obtain materials from libraries museums newspapers television and radio programs and universities and schools located all around the world. Formal e-learning is quickly becoming popular and thousands of courses offering instruction at many levels and in many areas are now available on the Internet. This book describes new techniques for distance learning or e-learning and for constructing knowledge from remote information sources. What can you achieve with this book The main thesis of this book is that instructional design or instructional engineering particularly in an e-learning context must be based on knowledge engineering and is most effective when it employs graphic models representing the knowledge and competencies learners are to acquire. Furthermore this book demonstrates why instructional engineering needs to move beyond information management to become knowledge management. This book will revolutionize your thinking showing you effective new approaches to e-learning methodologies. How is this book organized The eight chapters in this book take you from theory to practice. Chapter One defines the forthcoming context in which all training will take place the knowledge society and economy. Chapter Two describes the virtual learning center and the instructional engineering questions that occur in this environment. Chapter Three discusses the foundations of instructional engineering in scientific instructional design software engineering and knowledge engineering. Chapter Four introduces a specific instructional engineering method based on knowledge representation and Chapter Five introduces a Web-based support .

• Môi trường
• Learning Models
• Development Tools
• Platforms and Portals
• Learning System
• Learning Event
• Flexible Architecture
• Handbook of research on hybrid learning models
• Hybrid learning models
• Distance education
• Blended learning
• Virtual reality in education
• Ebook E Learning concepts and techniques
• E Learning concepts and techniques
• Instructional design models
• Instructional design models for E Learning
• E Learning tools
• Instructional strategies for E learning
• Computer assisted instruction
• Educational technology
• Quantitative analysis
• The students’ perceptions
• The use of 3D electronic models
• Problembased learning
• Blended problem based learning
• Introduction to machine learning
• Machine learning
• Linear discrimination
• Multilayer perceptrons
• Local models
• Kernel machines
• Hidden markov models
• Pretest post test
• Two treatment design
• Problem Based Learning
• Inquiry learning models
• Physical education learning
• Learning Syntactic Verb Frames
• Graphical Models
• Thomas Lippincott
• báo cáo khoa học
• báo cáo ngôn ngữ
• ngôn ngữ tự nhiên
• Learning Phrase Based
• Spelling Error Models
• Clickthrough Data
• PCFGs Topic Models
• Adaptor Grammars and Learning Topical Collocations
• the Structure of Proper Names
• Phrase based Statistical Language Generation
• Active Learning
• Learning Lexicalized Reordering Models
• Reordering Graphs
• Long Papers
• Confidence Weighted Learning
• Factored Discriminative Language Models
• Viet Ha Thuc
• Typed Graph Models
• Semi Supervised Learning
• Name Ethnicity
• Hierarchical Reinforcement Learning and Hidden Markov Models
• Task Oriented Natura
• l Language Generation
• A Decoder Alignment and Learning Framework
• Finite State
• Context Free Translation Models
• Learning Expressive Models
• Word Sense Disambiguation
• Lucia Specia
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Unsupervised Learning
• Field Segmentation Models
• Information Extraction
• Large Margin Learning
• Submodular Summarization Models
• Thorsten Joachims
• scientific reports
• model language
• process natural language
• Deriving prior distributions
• Bayesian models used
• Achieve adaptive e learning
• Group profile and performance data
• Prior distribution
• Luận án Tiến sĩ
• Công nghệ thông tin
• Semantic relation extraction
• Khoa học máy tính
• Advanced deep learning models
• Computer science
• Relation extraction
• Shortest dependency path
• Risk model
• Statistical risk models
• Cluster number
• Risk factor
• Factor loadings
• Principal component
• Biological trials
• Cheminformatic models
• Pyruvate kinase inhibitors
• Leishmania mexicana
• Machine learning methods
• Dimension Reduction
• Data Clustering Techniques
• Max Margin Classifications
• Discriminative Graphical Models
• Generative Graphical Models
• Approaches toward widening
• The open access to learning
• Open access to education
• Open learning
• Higher education