Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013)
Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013)

Author: Tutut Herawan

Publisher: Springer Science & Business Media

Published: 2013-12-14

Total Pages: 728

ISBN-13: 9814585181

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The proceeding is a collection of research papers presented at the International Conference on Data Engineering 2013 (DaEng-2013), a conference dedicated to address the challenges in the areas of database, information retrieval, data mining and knowledge management, thereby presenting a consolidated view to the interested researchers in the aforesaid fields. The goal of this conference was to bring together researchers and practitioners from academia and industry to focus on advanced on data engineering concepts and establishing new collaborations in these areas. The topics of interest are as follows but are not limited to: • Database theory • Data management • Data mining and warehousing • Data privacy & security • Information retrieval, integration and visualization • Information system • Knowledge discovery in databases • Mobile, grid and cloud computing • Knowledge-based • Knowledge management • Web data, services and intelligence

Immersive Education
Immersive Education

Author: Martin Ebner

Publisher: Springer

Published: 2015-07-31

Total Pages: 146

ISBN-13: 3319220179

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This book constitutes the refereed proceedings of the 4th European Immersive Education Summit, EiED 2014, held in Vienna, Austria, in November 2014. The 11 revised full papers presented were carefully reviewed and selected from 30 submissions. The papers are organized in topical sections on innovation and technological advancements in e-learning; immersive and emerging technologies for cultural and digital heritage.

Learning Analytics
Learning Analytics

Author: Johann Ari Larusson

Publisher: Springer

Published: 2014-07-04

Total Pages: 203

ISBN-13: 1461433053

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In education today, technology alone doesn't always lead to immediate success for students or institutions. In order to gauge the efficacy of educational technology, we need ways to measure the efficacy of educational practices in their own right. Through a better understanding of how learning takes place, we may work toward establishing best practices for students, educators, and institutions. These goals can be accomplished with learning analytics. Learning Analytics: From Research to Practice updates this emerging field with the latest in theories, findings, strategies, and tools from across education and technological disciplines. Guiding readers through preparation, design, and examples of implementation, this pioneering reference clarifies LA methods as not mere data collection but sophisticated, systems-based analysis with practical applicability inside the classroom and in the larger world. Case studies illustrate applications of LA throughout academic settings (e.g., intervention, advisement, technology design), and their resulting impact on pedagogy and learning. The goal is to bring greater efficiency and deeper engagement to individual students, learning communities, and educators, as chapters show diverse uses of learning analytics to: Enhance student and faculty performance. Improve student understanding of course material. Assess and attend to the needs of struggling learners. Improve accuracy in grading. Allow instructors to assess and develop their own strengths. Encourage more efficient use of resources at the institutional level. Researchers and practitioners in educational technology, IT, and the learning sciences will hail the information in Learning Analytics: From Research to Practice as a springboard to new levels of student, instructor, and institutional success.

Data Mining and Learning Analytics
Data Mining and Learning Analytics

Author: Samira ElAtia

Publisher: John Wiley & Sons

Published: 2016-09-20

Total Pages: 351

ISBN-13: 1118998219

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Addresses the impacts of data mining on education and reviews applications in educational research teaching, and learning This book discusses the insights, challenges, issues, expectations, and practical implementation of data mining (DM) within educational mandates. Initial series of chapters offer a general overview of DM, Learning Analytics (LA), and data collection models in the context of educational research, while also defining and discussing data mining’s four guiding principles— prediction, clustering, rule association, and outlier detection. The next series of chapters showcase the pedagogical applications of Educational Data Mining (EDM) and feature case studies drawn from Business, Humanities, Health Sciences, Linguistics, and Physical Sciences education that serve to highlight the successes and some of the limitations of data mining research applications in educational settings. The remaining chapters focus exclusively on EDM’s emerging role in helping to advance educational research—from identifying at-risk students and closing socioeconomic gaps in achievement to aiding in teacher evaluation and facilitating peer conferencing. This book features contributions from international experts in a variety of fields. Includes case studies where data mining techniques have been effectively applied to advance teaching and learning Addresses applications of data mining in educational research, including: social networking and education; policy and legislation in the classroom; and identification of at-risk students Explores Massive Open Online Courses (MOOCs) to study the effectiveness of online networks in promoting learning and understanding the communication patterns among users and students Features supplementary resources including a primer on foundational aspects of educational mining and learning analytics Data Mining and Learning Analytics: Applications in Educational Research is written for both scientists in EDM and educators interested in using and integrating DM and LA to improve education and advance educational research.

Learning Analytics: Fundaments, Applications, and Trends
Learning Analytics: Fundaments, Applications, and Trends

Author: Alejandro Peña-Ayala

Publisher: Springer

Published: 2017-02-17

Total Pages: 310

ISBN-13: 3319529773

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This book provides a conceptual and empirical perspective on learning analytics, its goal being to disseminate the core concepts, research, and outcomes of this emergent field. Divided into nine chapters, it offers reviews oriented on selected topics, recent advances, and innovative applications. It presents the broad learning analytics landscape and in-depth studies on higher education, adaptive assessment, teaching and learning. In addition, it discusses valuable approaches to coping with personalization and huge data, as well as conceptual topics and specialized applications that have shaped the current state of the art. By identifying fundamentals, highlighting applications, and pointing out current trends, the book offers an essential overview of learning analytics to enhance learning achievement in diverse educational settings. As such, it represents a valuable resource for researchers, practitioners, and students interested in updating their knowledge and finding inspirations for their future work.

Experimental Studies in Learning Technology and Child–Computer Interaction
Experimental Studies in Learning Technology and Child–Computer Interaction

Author: Michail Giannakos

Publisher: Springer Nature

Published: 2022-09-30

Total Pages: 120

ISBN-13: 3031143507

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This book is about the ways in which experiments can be employed in the context of research on learning technologies and child–computer interaction (CCI). It is directed at researchers, supporting them to employ experimental studies while increasing their quality and rigor. The book provides a complete and comprehensive description on how to design, implement, and report experiments, with a focus on and examples from CCI and learning technology research. The topics covered include an introduction to CCI and learning technologies as interdisciplinary fields of research, how to design educational interfaces and visualizations that support experimental studies, the advantages and disadvantages of a variety of experiments, methodological decisions in designing and conducting experiments (e.g. devising hypotheses and selecting measures), and the reporting of results. As well, a brief introduction on how contemporary advances in data science, artificial intelligence, and sensor data have impacted learning technology and CCI research is presented. The book details three important issues that a learning technology and CCI researcher needs to be aware of: the importance of the context, ethical considerations, and working with children. The motivation behind and emphasis of this book is helping prospective CCI and learning technology researchers (a) to evaluate the circumstances that favor (or do not favor) the use of experiments, (b) to make the necessary methodological decisions about the type and features of the experiment, (c) to design the necessary “artifacts” (e.g., prototype systems, interfaces, materials, and procedures), (d) to operationalize and conduct experimental procedures to minimize potential bias, and (e) to report the results of their studies for successful dissemination in top-tier venues (such as journals and conferences). This book is an open access publication.

Computational Intelligence in Data Mining
Computational Intelligence in Data Mining

Author: Himansu Sekhar Behera

Publisher: Springer

Published: 2018-07-03

Total Pages: 896

ISBN-13: 9811080550

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The International Conference on “Computational Intelligence in Data Mining” (ICCIDM), after three successful versions, has reached to its fourth version with a lot of aspiration. The best selected conference papers are reviewed and compiled to form this volume. The proceedings discusses the latest solutions, scientific results and methods in solving intriguing problems in the fields of data mining, computational intelligence, big data analytics, and soft computing. The volume presents a sneak preview into the strengths and weakness of trending applications and research findings in the field of computational intelligence and data mining along with related field.

International Handbook of Computer-Supported Collaborative Learning
International Handbook of Computer-Supported Collaborative Learning

Author: Ulrike Cress

Publisher: Springer Nature

Published: 2021-10-08

Total Pages: 669

ISBN-13: 3030652912

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CSCL has in the past 15 years (and often in conjunction with Springer) grown into a thriving and active community. Yet, lacking is a comprehensive CSCL handbook that displays the range of research being done in this area. This handbook will provide an overview of the diverse aspects of the field, allowing newcomers to develop a sense of the entirety of CSCL research and for existing community members to become more deeply aware of work outside their direct area. The handbook will also serve as a ready reference for foundational concepts, methods, and approaches in the field. The chapters are written in such a way that each of them can be used in a stand-alone fashion while also serving as introductory readings in relevant study courses or in teacher education. While some CSCL-relevant topics are addressed in the International Handbook of the Learning Sciences and the International Handbook of Collaborative Learning, these books do not aim to present an integrated and comprehensive view of CSCL. The International Handbook of Computer- Supported Collaborative Learning covers all relevant topics in CSCL, particularly recent developments in the field, such as the rise of computational approaches and learning analytics.

Handbook of Big Data and Analytics in Accounting and Auditing
Handbook of Big Data and Analytics in Accounting and Auditing

Author: Tarek Rana

Publisher: Springer Nature

Published: 2023-02-03

Total Pages: 564

ISBN-13: 9811944601

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This handbook collects the most up-to-date scholarship, knowledge, and new developments of big data and data analytics by bringing together many strands of contextual and disciplinary research. In recent times, while there has been considerable research in exploring the role of big data, data analytics, and textual analytics in accounting, and auditing, we still lack evidence on what kinds of best practices academics, practitioners, and organizations can implement and use. To achieve this aim, the handbook focuses on both conventional and contemporary issues facing by academics, practitioners, and organizations particularly when technology and business environments are changing faster than ever. All the chapters in this handbook provide both retrospective and contemporary views and commentaries by leading and knowledgeable scholars in the field, who offer unique insights on the changing role of accounting and auditing in today’s data and analytics driven environment. Aimed at academics, practitioners, students, and consultants in the areas of accounting, auditing, and other business disciplines, the handbook provides high-level insight into the design, implementation, and working of big data and data analytics practices for all types of organizations worldwide. The leading scholars in the field provide critical evaluations and guidance on big data and data analytics by illustrating issues related to various sectors such as public, private, not-for-profit, and social enterprises. The handbook’s content will be highly desirable and accessible to accounting and non-accounting audiences across the globe.

Learning and Performance Assessment: Concepts, Methodologies, Tools, and Applications
Learning and Performance Assessment: Concepts, Methodologies, Tools, and Applications

Author: Management Association, Information Resources

Publisher: IGI Global

Published: 2019-10-11

Total Pages: 1792

ISBN-13: 1799804216

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As teaching strategies continue to change and evolve, and technology use in classrooms continues to increase, it is imperative that their impact on student learning is monitored and assessed. New practices are being developed to enhance students’ participation, especially in their own assessment, be it through peer-review, reflective assessment, the introduction of new technologies, or other novel solutions. Educators must remain up-to-date on the latest methods of evaluation and performance measurement techniques to ensure that their students excel. Learning and Performance Assessment: Concepts, Methodologies, Tools, and Applications is a vital reference source that examines emerging perspectives on the theoretical and practical aspects of learning and performance-based assessment techniques and applications within educational settings. Highlighting a range of topics such as learning outcomes, assessment design, and peer assessment, this multi-volume book is ideally designed for educators, administrative officials, principals, deans, instructional designers, school boards, academicians, researchers, and education students seeking coverage on an educator’s role in evaluation design and analyses of evaluation methods and outcomes.