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10,262 result(s) for "COMPUTER-AIDED LEARNING"
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Design of Technology-Enhanced Learning
This book explains how educational research can inform the design of technology-enhanced learning environments. After laying pedagogical, technological and content foundations, it analyses learning in Web 2.0, Social Networking, Mobile Learning and Virtual Worlds to derive nuanced principles for technology-enhanced learning design.
Digital Personalization in Early Childhood
This book is available as open access through the Bloomsbury Open Access programme and is available on www.bloomsburycollections.com. Digital personalization is an emerging interdisciplinary research field, with application to a variety of areas including design, education and publication industry. This book focuses on children’s education and literacy resources, which have undergone important changes with the ‘personalization revolution’ in the early 21st century. The author develops original insights from educational research and her own studies concerned with digital and non-digital personalization, to discuss in a clear and critical way the thinking, research issues and practical implications of this new field. She scrutinises the character of technology-based personalized education to substantiate the claim that the current models of personalized education tend to be technology- and business-driven, with little pedagogical understanding of the social value of personalization. Research involving touchscreens, personalized books and 2-8-year olds is interrogated for its impact on children’s development of language, creativity, identity, as well as family dynamics and classroom dialogue. The literature available on digital and non-digital personalization is discussed in relation to five key themes of personalized education, the so-called 5As: autonomy, authorship, aesthetics, attachment and authenticity. It is argued that the 5As need to be anchored in humanist principles for a sustainable pedagogy and practice. Based on the insights from research with typically and atypically developing children, Kucirkova proposes personalised pluralisation, as a pedagogical framework of personalized education for the future. The book aims to help scholars and professionals understand the connections between personalization and literacy, personalization and education, and personalization and wider socio-moral issues.
Students' Experiences of E-learning in Higher Education
Students' Experiences of e-learning in Higher Education helps higher education instructors and university managers understand how e-learning relates to, and can be integrated with, other student experiences of learning. Grounded in relevant international research, the book is distinctive in that it foregrounds students' experiences of learning, emphasizing the importance of how students interpret the challenges set before them, along with their conceptions of learning and their approaches to learning. The way students interpret task requirements greatly affects learning outcomes, and those interpretations are in turn influenced by how students read the larger environment in which they study. The authors argue that a systemic understanding is necessary for the effective design and management of modern learning environments, whether lectures, seminars, laboratories or private study. This ecological understanding must also acknowledge, though, the agency of learners as active interpreters of their environment and its culture, values and challenges. Students' Experiences of e-learning in Higher Education reports research outcomes that locate e-learning within the broader ecology of higher education and: Offers a holistic treatment of e-learning in higher education, reflecting the need for integrating e-learning and other aspects of the student learning experience Reports research on students' experiences with e-learning conducted by authors in the United States, Europe, and Australia Synthesizes key themes in recent international research and summarizes their implications for teachers and managers.
Evaluating the performance of a deep learning‐based computer‐aided diagnosis (DL‐CAD) system for detecting and characterizing lung nodules: Comparison with the performance of double reading by radiologists
Background The study was conducted to evaluate the performance of a state‐of‐the‐art commercial deep learning‐based computer‐aided diagnosis (DL‐CAD) system for detecting and characterizing pulmonary nodules. Methods Pulmonary nodules in 346 healthy subjects (male: female = 221:125, mean age 51 years) from a lung cancer screening program conducted from March to November 2017 were screened using a DL‐CAD system and double reading independently, and their performance in nodule detection and characterization were evaluated. An expert panel combined the results of the DL‐CAD system and double reading as the reference standard. Results The DL‐CAD system showed a higher detection rate than double reading, regardless of nodule size (86.2% vs. 79.2%; P < 0.001): nodules ≥ 5 mm (96.5% vs. 88.0%; P = 0.008); nodules < 5 mm (84.3% vs. 77.5%; P < 0.001). However, the false positive rate (per computed tomography scan) of the DL‐CAD system (1.53, 529/346) was considerably higher than that of double reading (0.13, 44/346; P < 0.001). Regarding nodule characterization, the sensitivity and specificity of the DL‐CAD system for distinguishing solid nodules > 5 mm (90.3% and 100.0%, respectively) and ground‐glass nodules (100.0% and 96.1%, respectively) were close to that of double reading, but dropped to 55.5% and 93%, respectively, when discriminating part solid nodules. Conclusion Our DL‐CAD system detected significantly more nodules than double reading. In the future, false positive findings should be further reduced and characterization accuracy improved.
Increasing Student Engagement and Retention Using Classroom Technologies: Classroom Response Systems and Mediated Discourse Technologies
Increasing Student Engagement and Retention Using Classroom Technologies: Classroom Response Systems and Mediated Discourse Technologies examines new research on how classroom response systems are being used in higher education to increase learner engagement in an epoch of increasing globalization and diversity. These enabling technologies are reshaping and reframing the practice of teaching and learning in higher education. Through case studies, surveys, and literature reviews, this volume will examine how classroom response systems are being used to improve collaboration and interactivity between students, to create engaging social learning communities in the classroom, and how these technologies are being used to create more meaningful and authentic learning experiences. This volume will also discuss a framework for adopting and deploying these technologies.
Prediction of Nodal Metastasis in Lung Cancer Using Deep Learning of Endobronchial Ultrasound Images
Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a valid modality for nodal lung cancer staging. The sonographic features of EBUS helps determine suspicious lymph nodes (LNs). To facilitate this use of this method, machine-learning-based computer-aided diagnosis (CAD) of medical imaging has been introduced in clinical practice. This study investigated the feasibility of CAD for the prediction of nodal metastasis in lung cancer using endobronchial ultrasound images. Image data of patients who underwent EBUS-TBNA were collected from a video clip. Xception was used as a convolutional neural network to predict the nodal metastasis of lung cancer. The prediction accuracy of nodal metastasis through deep learning (DL) was evaluated using both the five-fold cross-validation and hold-out methods. Eighty percent of the collected images were used in five-fold cross-validation, and all the images were used for the hold-out method. Ninety-one patients (166 LNs) were enrolled in this study. A total of 5255 and 6444 extracted images from the video clip were analyzed using the five-fold cross-validation and hold-out methods, respectively. The prediction of LN metastasis by CAD using EBUS images showed high diagnostic accuracy with high specificity. CAD during EBUS-TBNA may help improve the diagnostic efficiency and reduce invasiveness of the procedure.
Jacques Rancière
Winner – AERA 2011 Outstanding Book Award Jacques Rancière: Education, Truth, Emancipation demonstrates the importance of Rancières work for educational theory, and in turn, it shows just how central Rancières educational thought is to his work in political theory and aesthetics. Charles Bingham and Gert Biesta illustrate brilliantly how philosophy can benefit from Rancières particular way of thinking about education, and go on to offer their own provocative account of the relationship between education, truth, and emancipation. Including a new essay by Rancière himself, this book is a must-read for scholars of social theory and all who profess to educate.
Digital Technologies in Early Childhood Art
Through art children make sense of their experiences and the world around them.Drawing, painting, collage and modelling are open-ended and playful processes through which children engage in physical exploration, aesthetic decision-making, identity construction and social understanding.
Inventive minds : Marvin Minsky on education
Six essays by artificial intelligence pioneer Marvin Minsky on how education can foster inventiveness, paired with commentary by Minsky's former colleagues and students. Marvin Minsky was a pioneering researcher in artificial intelligence whose work led to both theoretical and practical advances. His work was motivated not only by technological advancement but also by the desire to understand the workings of our own minds. Minsky's insights about the mind provide fresh perspectives on education and how children learn. This book collects for the first time six essays by Minsky on children, learning, and the potential of computers in school to enrich children's development. In these essays Minsky discusses the shortcomings of conventional education (particularly in mathematics) and considers alternative approaches; reflects on the role of mentors; describes higher-level strategies for thinking across domains; and suggests projects for children to pursue. Each essay is paired with commentary by one of Minsky's former colleagues or students, which identifies Minsky's key ideas and connects his writings to current research. Minsky once observed that in traditional teaching, “instead of promoting inventiveness, we focus on preventing mistakes.” These essays offer Minsky's unique insights into how education can foster inventiveness. Commentary by Hal Abelson, Walter Bender, Alan Kay, Margaret Minsky, Brian Silverman, Gary Stager, Mike Travers, Patrick Henry Winston