The Order Of Learning
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The Order of Learning considers the problems facing higher education by focusing on main underlying factors: the relationship of higher education to government, academic freedom, and the responsibilities of the academic profession, among others. Edward Shils argues that higher education has a central role in society, and that distractions, such as pressures from government, disinterest of students and faculty in education, and involvement of institutions of higher learning in social questions, have damaged higher education by deflecting it from its commitment to teaching, learning, and research. Shils believes that the modern university must be steadfast in its commitment to the pursuit of truth, the education of students, and the provision of research. Universities should not be all things to all people. On one hand, the academic community must understand the essential mission of the university and resist distractions. On the other, government must provide the necessary support to higher education, even when the immediate "pay-off" is not self-evident. This book provides a refreshing new perspective precisely by taking a traditional stance on the role of higher education in modern society. It includes carefully researched and elegantly written essays on many of the central issues facing education today. This work will be of great interest to educators and students alike, as well as those interested in the future of higher education in the United States.
Order affects the results you get: Different orders of presenting material can lead to qualitatively and quantitatively different learning outcomes. These differences occur in both natural and artificial learning systems. In Order to Learn shows how order effects are crucial in human learning, instructional design, machine learning, and both symbolic and connectionist cognitive models. Each chapter explains a different aspect of how the order in which material is presented can strongly influence what is learned by humans and theoretical models of learning in a variety of domains. In addition to data, models are provided that predict and describe order effects and analyze how and when they will occur. The introductory and concluding chapters compile suggestions for improving learning through better sequences of learning materials, including how to take advantage of order effects that encourage learning and how to avoid order effects that discourage learning. Each chapter also highlights questions that may inspire further research. Taken together, these chapters show how order effects in different areas can and do inform each other. In Order to Learn will be of interest to researchers and students in cognitive science, education, machine learning.
proposed Legislative Competence Order in Council on additional learning Needs : Second report of Session 2007-08, report, together with formal minutes, oral and written Evidence
This book examines current advances in the role of interactional feedback in second language (L2) teaching and learning. Drawing on recent theory and research in both classroom and laboratory contexts, the book explores a wide range of issues regarding interactional feedback and their relevance for both theory and practice, including how interactional feedback is used, processed, and contributes to L2 acquisition. This book will provide a useful resource for applied linguistics students and academics as well as language teachers and teacher educators who would like to gain insight into the role of interactional feedback and how it can be used as a means of integrating form and meaning in classroom contexts.
This book examines the various ways in which age affects the process and the product of foreign language learning in a school setting. It presents studies that cover a wide range of topics, from phonetics to learning strategies. It will be of interest to students and researchers working in SLA research, language planning and language teaching.
Web-based training, known as e-learning, has experienced a great evolution and growth in recent years, as the capacity for education is no longer limited by physical and time constraints. The emergence of such a prized learning tool mandates a comprehensive evaluation of the effectiveness and implications of e-learning. Advances in E-Learning: Experiences and Methodologies explores the technical, pedagogical, methodological, tutorial, legal, and emotional aspects of e-learning, considering and analyzing its different application contexts, and providing researchers and practitioners with an innovative view of e-learning as a lifelong learning tool for scholars in both academic and professional spheres.
Highlighting the best in management learning theory and practices, the authors provide a comprehensive approach to leadership from a learning perspective. This exciting new book, from award-winning authorities on learning, describes how leaders gain the advantage when they cultivate learning in themselves and others.
Updated Edition of Bestseller Madeline Hunter’s authoritative guide to effective instruction, newly updated and expanded for today’s learners! This classic resource is the best-selling guide to rigorous standards-based instruction that covers teaching to both sides of the brain, teaching for meaning and retention, and teaching to real-life situations. This exciting new edition features: Instruction, learning, motivation, guided practice, and behavior integrated into a comprehensive and effective model for classroom teaching Newly updated and expanded content to encompass teaching for independent learning Teaching tips, classroom examples, recommended readings, a new comprehensive index, and a discussion guide for each chapter
For teachers in higher education who haven’t been able to catch up with developments in teaching and learning, James Davis and Bridget Arend offer an introduction that focuses on seven coherent and proven evidence-based strategies. The underlying rationale is to provide a framework to match teaching goals to distinct ways of learning, based on well-established theories of learning. The authors present approaches that readers can readily and safely experiment with to achieve desired learning outcomes, and build confidence in changing their methods of teaching. Research on learning clearly demonstrates that learning is not one thing, but many. The learning associated with developing a skill is different from the learning associated with understanding and remembering information, which in turn is different from thinking critically and creatively, solving problems, making decisions, or change paradigms in the light of evidence. Differing outcomes involve different ways of learning and teaching strategies. The authors provide the reader with a conceptual approach for selecting appropriate teaching strategies for different types of content, and for achieving specific learning objectives. They demonstrate through examples how a focused and purposeful selection of activities improves student performance, and in the process makes for a more effective and satisfying teaching experience. The core of the book presents a chapter on each of the seven ways of learning. Each chapter offers a full description of the process, illustrates its application with examples from different academic fields and types of institutions, clearly describes the teacher’s facilitation role, and covers assessment and online use. The seven ways of learning are: Behavioral Learning; Cognitive Learning; Learning through Inquiry; Learning with Mental Models; Learning through Groups and Teams; Learning through Virtual Realities; and Experiential Learning. Along the way, the authors provide the reader with a basis for evaluating other approaches to teaching and other learning methodologies so that she or he can confidently go beyond the “seven ways” to adapt or adopt further strategies. This is the ideal companion for teachers who are beginning to explore new ways of teaching, and want to do some serious independent thinking about learning. The book can also be used to prepare graduate students for teaching, and will be welcomed by centers for teaching and learning to help continuing faculty re-examine a particular aspect of their teaching.
Experiments in Second-Language Learning focuses on the application of mathematical learning models in learning the Russian language as a second language. The book first discusses remarks on stimulus-response theories of language learning. Psychology and second-language instruction; psychological theory; linguistic theory and second-language learning; and remarks on theories of conditioning are discussed. The text also focuses on learning to discriminate Russian phonemes; learning the orthographic representations of Russian sounds; and vocabulary and morphology learning. Learning exercises are presented; these focused on inflection, semantics, and phonemic transcriptions. The book also looks at grammar learning as influenced by translations, vocabulary, and presentation order; training on negative instances or on isolated words; overview of Russian grammar experiments; and related research. Suggestions for future research are presented. The text is highly valuable for readers interested in studying how mathematical learning models can be used in learning one particular language as a second language.
Handbook of Research on Learning Design and Learning Objects: Issues, Applications, and Technologies
"This book provides an overview of current research and development activity in the area of learning designs"--Provided by publisher.
Translating brain research into best practice, this book offers teachers a concise Strategic Learning Model for the active transfer of knowledge to students' long-term memory.
Writing allows people to convey information to others who are remote in time and space, vastly increasing the range over which people can cooperate and the amount they can learn. Mastering the writing system of one's language is crucial for success in a modern society. This book examines how children learn to write words. It provides a theoretical framework that integrates findings from a wide range of age groups--from children who are producing their first scribbles to experienced spellers who are writing complex words. To set the stage for these discussions, early chapters of the book consider the nature of writing systems and the nature of learning itself. The following chapters review various aspects of orthographic development, including the learning of symbol shapes and punctuation. Each chapter reviews research with learners of a variety of languages and writing systems, revealing underlying similarities. Discussions of how orthography is and should be taught are incorporated into each chapter, making the book of interest to educators as well as to psychologists, cognitive scientists, and linguists. This book is unique in the range of topics and languages that it covers and the degree to which it integrates linguistic insights about the nature of writing systems with discussions of how people learn to use these systems. It is written in a scholarly yet accessible manner, making it suited for a wide audience.
This volume contains the proceedings of the Eurpoean Conference on Machine Learning (ECML-93), continuing the tradition of the five earlier EWSLs (European Working Sessions on Learning). The aim of these conferences is to provide a platform for presenting the latest results in the area of machine learning. The ECML-93 programme included invited talks, selected papers, and the presentation of ongoing work in poster sessions. The programme was completed by several workshops on specific topics. The volume contains papers related to all these activities. The first chapter of the proceedings contains two invited papers, one by Ross Quinlan and one by Stephen Muggleton on inductive logic programming. The second chapter contains 18 scientific papers accepted for the main sessions of the conference. The third chapter contains 18 shorter position papers. The final chapter includes three overview papers related to the ECML-93 workshops.
Part of a series of textbooks which have been written to support A levels in psychology. The books use real life applications to help teach students what they need to know. Readers are encouraged to use aims, methods, results and conclusions of the key studies to support their own arguments.
The majority of information on the Internet is expressed in written text. Understanding and extracting this information is crucial to building intelligent systems that can organize this knowledge, but most algorithms focus on learning atomic facts and relations. For instance, we can reliably extract facts like "Stanford is a University" and "Professors teach Science" by observing redundant word patterns across a corpus. However, these facts do not capture richer knowledge like the way detonating a bomb is related to destroying a building, or that the perpetrator who was convicted must have been arrested. A structured model of these events and entities is needed to understand language across many genres, including news, blogs, and even social media. This dissertation describes a new approach to knowledge acquisition and extraction that learns rich structures of events (e.g., plant, detonate, destroy) and participants (e.g., suspect, target, victim) over a large corpus of news articles, beginning from scratch and without human involvement. As opposed to early event models in Natural Language Processing (NLP) such as scripts and frames, modern statistical approaches and advances in NLP now enable new representations and large-scale learning over many domains. This dissertation begins by describing a new model of events and entities called Narrative Event Schemas. A Narrative Event Schema is a collection of events that occur together in the real world, linked by the typical entities involved. I describe the representation itself, followed by a statistical learning algorithm that observes chains of entities repeatedly connecting the same sets of events within documents. The learning process extracts thousands of verbs within schemas from 14 years of newspaper data. I present novel contributions in the ﬁeld of temporal ordering to build classiﬁers that order the events and infer likely schema orderings. I then present several new evaluations for the extracted knowledge. Finally, I apply Narrative Event Schemas to the ﬁeld of Information Extraction, learning templates of events with sets of semantic roles. Most Information Extraction approaches assume foreknowledge of the domain's templates, but I instead start from scratch and learn schemas as templates, and then extract the entities from text as in a standard extraction task. My algorithm is the ﬁrst to learn templates without human guidance, and its results approach those of supervised algorithms.
This book provides a versatile and lucid treatment of classic as well as modern probability theory, while integrating them with core topics in statistical theory and also some key tools in machine learning. It is written in an extremely accessible style, with elaborate motivating discussions and numerous worked out examples and exercises. The book has 20 chapters on a wide range of topics, 423 worked out examples, and 808 exercises. It is unique in its unification of probability and statistics, its coverage and its superb exercise sets, detailed bibliography, and in its substantive treatment of many topics of current importance. This book can be used as a text for a year long graduate course in statistics, computer science, or mathematics, for self-study, and as an invaluable research reference on probabiliity and its applications. Particularly worth mentioning are the treatments of distribution theory, asymptotics, simulation and Markov Chain Monte Carlo, Markov chains and martingales, Gaussian processes, VC theory, probability metrics, large deviations, bootstrap, the EM algorithm, confidence intervals, maximum likelihood and Bayes estimates, exponential families, kernels, and Hilbert spaces, and a self contained complete review of univariate probability.
First Published in 2000. Routledge is an imprint of Taylor & Francis, an informa company.