[PDF] Intelligent Systems And Learning Data Analytics In Online Education eBook

Author : Santi Caballé
Publisher : Academic Press
Page : 427 pages
File Size : 15,54 MB
Release : 2021-06-15
Category : Computers
ISBN : 0128231270

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Intelligent Systems and Learning Data Analytics in Online Education provides novel artificial intelligence (AI) and analytics-based methods to improve online teaching and learning. This book addresses key problems such as attrition and lack of engagement in MOOCs and online learning in general. This book explores the state of the art of artificial intelligence, software tools and innovative learning strategies to provide better understanding and solutions to the various challenges of current e-learning in general and MOOC education. In particular, Intelligent Systems and Learning Data Analytics in Online Education shares stimulating theoretical and practical research from leading international experts. This publication provides useful references for educational institutions, industry, academic researchers, professionals, developers, and practitioners to evaluate and apply. Presents the application of innovative AI techniques to collaborative learning activities Offers strategies to provide automatic and effective tutoring to students’ activities Offers methods to collect, analyze and correctly visualize learning data in educational environments

Author : Santi Caballé
Publisher : Morgan Kaufmann
Page : 384 pages
File Size : 37,29 MB
Release : 2016-05-10
Category : Education
ISBN : 0128036672

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Formative Assessment, Learning Data Analytics and Gamification: An ICT Education discusses the challenges associated with assessing student progress given the explosion of e-learning environments, such as MOOCs and online courses that incorporate activities such as design and modeling. This book shows educators how to effectively garner intelligent data from online educational environments that combine assessment and gamification. This data, when used effectively, can have a positive impact on learning environments and be used for building learner profiles, community building, and as a tactic to create a collaborative team. Using numerous illustrative examples and theoretical and practical results, leading international experts discuss application of automatic techniques for e-assessment of learning activities, methods to collect, analyze, and correctly visualize learning data in educational environments, applications, benefits and challenges of using gamification techniques in academic contexts, and solutions and strategies for increasing student participation and performance. Discusses application of automatic techniques for e-assessment of learning activities Presents strategies to provide immediate and useful feedback on students’ activities Provides methods to collect, analyze, and correctly visualize learning data in educational environments Explains the applications, benefits, and challenges of using gamification techniques in academic contexts Offers solutions to increase students’ participation and performance while lowering drop-out rates and retention levels

Author : Marian Cristian Mihăescu
Publisher : Springer Nature
Page : 167 pages
File Size : 19,88 MB
Release : 2022-03-22
Category : Computers
ISBN : 3030966445

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This book focuses on research and development aspects of building data analytics workflows that address various challenges of e-learning applications. This book represents a guideline for building a data analysis workflow from scratch. Each chapter presents a step of the entire workflow, starting from an available dataset and continuing with building interpretable models, enhancing models, and tackling aspects of evaluating engagement and usability. The related work shows that many papers have focused on machine learning usage and advancement within e-learning systems. However, limited discussions have been found on presenting a detailed complete roadmap from the raw dataset up to the engagement and usability issues. Practical examples and guidelines are provided for designing and implementing new algorithms that address specific problems or functionalities. This roadmap represents a potential resource for various advances of researchers and practitioners in educational data mining and learning analytics.

Author : David Niemi
Publisher : IAP
Page : 268 pages
File Size : 26,35 MB
Release : 2018-08-01
Category : Education
ISBN : 1641133716

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This book provides a comprehensive introduction by an extraordinary range of experts to the recent and rapidly developing field of learning analytics. Some of the finest current thinkers about ways to interpret and benefit from the increasing amount of evidence from learners’ experiences have taken time to explain their methods, describe examples, and point out new underpinnings for the field. Together, they show how this new field has the potential to dramatically increase learner success through deeper understanding of the academic, social-emotional, motivational, identity and meta-cognitive context each learner uniquely brings. Learning analytics is much more than “analyzing learning data”—it is about deeply understanding what learning activities work well, for whom, and when. Learning Analytics in Education provides an essential framework, as well as guidance and examples, for a wide range of professionals interested in the future of learning. If you are already involved in learning analytics, or otherwise trying to use an increasing density of evidence to understand learners’ progress, these leading thinkers in the field may give you new insights. If you are engaged in teaching at any level, or training future teachers/faculty for this new, increasingly technology-enhanced learning world, and want some sense of the potential opportunities (and pitfalls) of what technology can bring to your teaching and students, these forward-thinking leaders can spark your imagination. If you are involved in research around uses of technology, improving learning measurements, better ways to use evidence to improve learning, or in more deeply understanding human learning itself, you will find additional ideas and insights from some of the best thinkers in the field here. If you are involved in making administrative or policy decisions about learning, you will find new ideas (and dilemmas) coming your way from inevitable changes in how we design and deliver instruction, how we measure the outcomes, and how we provide feedback to students, teachers, developers, administrators, and policy-makers. For all these players, the trick will be to get the most out of all the new developments to efficiently and effectively improve learning performance, without getting distracted by “shiny” technologies that are disconnected from how human learning and development actually work.

Author : Tavis D. Jules
Publisher : Emerald Group Publishing
Page : 325 pages
File Size : 42,8 MB
Release : 2019-11-25
Category : Education
ISBN : 1787548546

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This book examines, from a comparative perspective, the impact of the movement from the so-called knowledge-based economy towards the Intelligent Economy, which is premised upon the application of knowledge. This volume links the advent of this new technological revolution to the world of governance and policy formulation in education.

Author : Bhatia, Madhulika
Publisher : IGI Global
Page : 357 pages
File Size : 15,41 MB
Release : 2024-03-04
Category : Education
ISBN :

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In the dynamic environment of education, the traditional methods employed by educators are struggling to keep pace with the evolving needs of students in the 21st century. The challenge lies in fostering an environment that not only engages students but also equips them with the skills essential for the modern world. Teachers find themselves navigating a complex terrain where outdated pedagogical approaches fall short of unlocking the full potential of diverse learning styles and unique talents within their classrooms. Enhancing Education With Intelligent Systems and Data-Driven Instruction is a groundbreaking book that goes beyond the constraints of conventional teaching methods, offering a comprehensive guide that inspires and equips educators with innovative tools and approaches. From integrating innovative technology to cultivating collaborative learning environments, the book provides a roadmap for educators to reimagine their teaching practices. By embracing student-centered approaches, fostering diversity, and utilizing digital tools effectively, this book empowers teachers to transform their classrooms into dynamic hubs of inspiration, motivation, and empowerment.

Author : Jay Liebowitz
Publisher : CRC Press
Page : 248 pages
File Size : 22,32 MB
Release : 2021-12-13
Category : Education
ISBN : 1000539008

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"In our increasingly digitally enabled education world, analytics used ethically, strategically, and with care holds the potential to help more and more diverse students be more successful on higher education journeys than ever before. Jay Liebowitz and a cadre of the fields best ‘good trouble’ makers in this space help shine a light on the possibilities, potential challenges, and the power of learning together in this work." —Mark David Milliron, Ph.D., Senior Vice President and Executive Dean of the Teachers College, Western Governors University Due to the COVID-19 pandemic and its aftereffects, we have begun to enter the "new normal" of education. Instead of online learning being an "added feature" of K–12 schools and universities worldwide, it will be incorporated as an essential feature in education. There are many questions and concerns from parents, students, teachers, professors, administrators, staff, accrediting bodies, and others regarding the quality of virtual learning and its impact on student learning outcomes. Online Learning Analytics is conceived on trying to answer the questions of those who may be skeptical about online learning. Through better understanding and applying learning analytics, we can assess how successful learning and student/faculty engagement, as examples, can contribute towards producing the educational outcomes needed to advance student learning for future generations. Learning analytics has proven to be successful in many areas, such as the impact of using learning analytics in asynchronous online discussions in higher education. To prepare for a future where online learning plays a major role, this book examines: Data insights for improving curriculum design, teaching practice, and learning Scaling up learning analytics in an evidence-informed way The role of trust in online learning. Online learning faces very real philosophical and operational challenges. This book addresses areas of concern about the future of education and learning. It also energizes the field of learning analytics by presenting research on a range of topics that is broad and recognizes the humanness and depth of educating and learning.

Author : Azevedo, Ana
Publisher : IGI Global
Page : 296 pages
File Size : 33,22 MB
Release : 2021-03-19
Category : Education
ISBN : 1799871045

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The term learning analytics is used in the context of the use of analytics in e-learning environments. Learning analytics is used to improve quality. It uses data about students and their activities to provide better understanding and to improve student learning. The use of learning management systems, where the activity of the students can be easily accessed, potentiated the use of learning analytics to understand their route during the learning process, help students be aware of their progress, and detect situations where students can give up the course before its completion, which is a growing problem in e-learning environments. Advancing the Power of Learning Analytics and Big Data in Education provides insights concerning the use of learning analytics, the role and impact of analytics on education, and how learning analytics are designed, employed, and assessed. The chapters will discuss factors affecting learning analytics such as human factors, geographical factors, technological factors, and ethical and legal factors. This book is ideal for teachers, administrators, teacher educators, practitioners, stakeholders, researchers, academicians, and students interested in the use of big data and learning analytics for improved student success and educational environments.

Author : Johann Ari Larusson
Publisher : Springer
Page : 203 pages
File Size : 31,86 MB
Release : 2014-07-04
Category : Education
ISBN : 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.

Author : Jorge Miguel
Publisher : Morgan Kaufmann
Page : 194 pages
File Size : 45,19 MB
Release : 2016-09-06
Category : Education
ISBN : 0128045450

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Intelligent Data Analysis for e-Learning: Enhancing Security and Trustworthiness in Online Learning Systems addresses information security within e-Learning based on trustworthiness assessment and prediction. Over the past decade, many learning management systems have appeared in the education market. Security in these systems is essential for protecting against unfair and dishonest conduct—most notably cheating—however, e-Learning services are often designed and implemented without considering security requirements. This book provides functional approaches of trustworthiness analysis, modeling, assessment, and prediction for stronger security and support in online learning, highlighting the security deficiencies found in most online collaborative learning systems. The book explores trustworthiness methodologies based on collective intelligence than can overcome these deficiencies. It examines trustworthiness analysis that utilizes the large amounts of data-learning activities generate. In addition, as processing this data is costly, the book offers a parallel processing paradigm that can support learning activities in real-time. The book discusses data visualization methods for managing e-Learning, providing the tools needed to analyze the data collected. Using a case-based approach, the book concludes with models and methodologies for evaluating and validating security in e-Learning systems. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS Provides guidelines for anomaly detection, security analysis, and trustworthiness of data processing Incorporates state-of-the-art, multidisciplinary research on online collaborative learning, social networks, information security, learning management systems, and trustworthiness prediction Proposes a parallel processing approach that decreases the cost of expensive data processing Offers strategies for ensuring against unfair and dishonest assessments Demonstrates solutions using a real-life e-Learning context