Impact of Learning Analytics on Curriculum Design and Student Performance


Book Description

The quality of students’ learning experiences is a critical concern for all educational institutions. With the assistance of modern technological advances, educational establishments have the capability to better understand the strengths and weaknesses of their learning programs. Impact of Learning Analytics on Curriculum Design and Student Performance is a critical scholarly resource that examines the connection between learning analytics and evaluations and their impact on curriculum design and student performance in educational institutions. Featuring coverage on a broad range of topics, such as academic support, large scale assessment, and educational research methods, this book is geared towards educators, professionals, school administrators, researchers, and practitioners in the field of education.




Learning Analytics


Book Description

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.




Utilizing Educational Data Mining Techniques for Improved Learning: Emerging Research and Opportunities


Book Description

Modern education has increased its reach through ICT tools and techniques. To manage educational data with the help of modern artificial intelligence, data and web mining techniques on dedicated cloud or grid platforms for educational institutes can be used. By utilizing data science techniques to manage educational data, the safekeeping, delivery, and use of knowledge can be increased for better quality education. Utilizing Educational Data Mining Techniques for Improved Learning: Emerging Research and Opportunities is a critical scholarly resource that explores data mining and management techniques that promote the improvement and optimization of educational data systems. The book intends to provide new models, platforms, tools, and protocols in data science for educational data analysis and introduces innovative hybrid system models dedicated to data science. Including topics such as automatic assessment, educational analytics, and machine learning, this book is essential for IT specialists, data analysts, computer engineers, education professionals, administrators, policymakers, researchers, academicians, and technology experts.




Online Learning Analytics


Book Description

"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.




A Conceptual Framework for SMART Applications in Higher Education: Emerging Research and Opportunities


Book Description

With the rapid availability of information, it becomes essential to keep pace with this availability as well as process the information into knowledge that has real-world applications. Neuroscientific methods allow an approach to this problem based on the way that the human brain already operates. Over the centuries and through observation and trial and error, we already know a great deal about how we can teach and learn, but now we can verify this with scientific fact and discover previously unknown aspects of brain physiology. These observations of brain functioning have produced many learning theories, all of which have varying degrees of validity. These theories, in turn, give birth to theories and models of instructional design, which also have varying degrees of validity. A Conceptual Framework for SMART Applications in Higher Education: Emerging Research and Opportunities is a critical scholarly publication that explores how the brain acquires and processes information to turn information into knowledge and the role of SMART technology and how it combines and integrates visual and aural data to facilitate learning. The book also discusses ways to apply what is known about teaching to how the brain operates and how to incorporate instructional design models into the teaching and learning process. Highlighting various topics such as neurogenesis, smart technologies, and behaviorism, this book is essential for instructional designers, online instruction managers, teachers, academicians, administrators, researchers, knowledge managers, and students.




Contemporary Technologies in Education


Book Description

This edited volume provides a critical discussion of theoretical, methodological, and practical developments of contemporary forms of educational technologies. Specifically, the book discusses the use of contemporary technologies such as the Flipped Classroom (FC), Massive Open Online Course (MOOC), Social Media, Serious Educational Games (SEG), Wikis, innovative learning software tools, and learning analytic approach for making sense of big data. While some of these contemporary educational technologies have been touted as panaceas, researchers and developers have been faced with enormous challenges in enhancing the use of these technologies to arouse student attention and improve persistent motivation, engagement, and learning. Hence, the book examines how contemporary technologies can engender student motivation and result in improved engagement and learning. Each chapter also discusses the road ahead and where appropriate, uses the current trend to predict future affordances of technologies.




Data Mining and Learning Analytics


Book Description

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.




Curriculum Landscapes and Trends


Book Description

Curriculum problems are everywhere: alert observers with a practiced eye and educated mind will find it almost impossible to read a newspaper without discovering curricular issues. The media often report about educational reforms or even about curriculum wars with opposing parties fiercely debating the aims, content and organization of learning. Few people analyze these trends and discussions from a curricular conceptual framework. In addition, people sometimes think that their curriculum approaches and problems are unique and context-specific. However, international experience shows us that we can learn a lot from curriculum issues elsewhere. This book aims to sharpen the eyes and minds of a broader audience in identifying, understanding, addressing and reflecting upon curriculum problems. It also aims to contribute to the increased exchange, discussion and reflection on all the current curriculum problems that form such a crucial part of learning worldwide.




A Beginner’s Guide to Learning Analytics


Book Description

This book A Beginner’s Guide to Learning Analytics is designed to meet modern educational trends’ needs. It is addressed to readers who have no prior knowledge of learning analytics and functions as an introductory text to learning analytics for those who want to do more with evaluation/assessment in their organizations. The book is useful to all who need to evaluate their learning and teaching strategies. It aims to bring greater efficiency and deeper engagement to individual students, learning communities, and educators. Covered here are the key concepts linked to learning analytics for researchers and practitioners interested in learning analytics. This book helps those who want to apply analytics to learning and development programs and helps educational institutions to identify learners who require support and provide a more personalized learning experience. Like chapters show diverse uses of learning analytics to enhance student and faculty performance. It presents a coherent framework for the effective translation of learning analytics research for educational practice to its practical application in different educational domains. This book provides educators and researchers with the tools and frameworks to effectively make sense of and use data and analytics in their everyday practice. This book will be a valuable addition to researchers’ bookshelves.




Perspectives on Learning Analytics for Maximizing Student Outcomes


Book Description

Maximizing student outcomes in education presents a significant challenge, as traditional assessment methods often fall short in providing actionable insights for improvement. Perspectives on Learning Analytics for Maximizing Student Outcomes addresses this challenge by offering a comprehensive solution. Edited by esteemed scholars Gürhan Durak and Serkan Çankaya, this book provides innovative knowledge and practical experiences on emerging technologies and processes in learning analytics. It covers topics such as data collection, visualization, predictive analytics, and ethical considerations, serving as a guide for academic scholars, technology enthusiasts, and educational institutions. This book empowers professionals and researchers to leverage learning analytics effectively, enabling data-informed decision-making, improved teaching practices, and tailored educational programs. By presenting best practices and future directions, it equips readers with the necessary tools to optimize learning environments and drive student success. With a focus on the transformative potential of learning analytics, this book propels education toward a more efficient and effective system that prioritizes student outcomes.