Learning Analytics Information Systems For Higher Education
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Big Data And Learning Analytics In Higher Education
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Author : Ben Kei Daniel
language : en
Publisher: Springer
Release Date : 2016-08-27
Big Data And Learning Analytics In Higher Education written by Ben Kei Daniel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-27 with Education categories.
This book focuses on the uses of big data in the context of higher education. The book describes a wide range of administrative and operational data gathering processes aimed at assessing institutional performance and progress in order to predict future performance, and identifies potential issues related to academic programming, research, teaching and learning. Big data refers to data which is fundamentally too big and complex and moves too fast for the processing capacity of conventional database systems. The value of big data is the ability to identify useful data and turn it into useable information by identifying patterns and deviations from patterns.
Design Principles For Learning Analytics Information Systems In Higher Education
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Author : Andy Nguyen
language : en
Publisher:
Release Date : 2021
Design Principles For Learning Analytics Information Systems In Higher Education written by Andy Nguyen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
This paper reports a design science research (DSR) study that develops, demonstrates and evaluates a set of design principles for information systems (IS) that utilise learning analytics to support learning and teaching in higher education. The initial set of design principles is created from theory-inspired conceptualisation based on the literature, and they are evaluated and revised through a DSR process of demonstration and evaluation. We evaluated the developed artefact in four courses with a total enrolment of 1,173 students. The developed design principles for learning analytics information systems (LAIS) to establish a foundation for further development and implementation of learning analytics to support learning and teaching in higher education. Full paper available at https://doi.org/10.1080/0960085X.2020.1816144.
Learning Analytics Information Systems For Higher Education
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Author : Xuân Khánh Nguyễn
language : en
Publisher:
Release Date : 2019
Learning Analytics Information Systems For Higher Education written by Xuân Khánh Nguyễn and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Education, Higher categories.
Information Systems (IS) and technology has long transformed the landscape of education. Recently, learning analytics (LA) has emerged as a new educational technology and drawn the attention of academics, researchers, and administrators. LA can offer educational stakeholders useful feedback and insights about the process of learning and teaching. LA is rapidly being applied in different educational settings including higher education, often as an ad-hoc analysis without the guidance of a research. Although the literature has revealed a substantial base of LA techniques for analysing discourse, social interactions, and descriptive and predictive models, few institutions have been able to provide evidence around successful implementation of learning analytics information systems (LAIS). Despite the currently limited understanding of underlying information systems that support learning analytics, existing reports on LAIS implementations indicate their significant potential for improving learning and teaching. This research aims to examine the development and implementation of LAIS in the context of higher education. Notably, it attempts to address two overarching research questions: 1) What are the fundamentals of learning analytics and their applications? And 2) How to design underlying information systems that support learning analytics? First, the study investigates and contributes to better understanding of the concepts around data analytics in higher education, i.e., learning analytics (LA), academic analytics (AA), and educational data mining (EDM). This study is then focused on LA which centres around learning and teaching. The key dimensions of LA are determined to establish a multi-layered taxonomy of LA applications and a domain-specific ontology. Furthermore, the study proposes conceptual frameworks and roadmaps for applying LA in different learning environments. The study establishes a foundation for the development and implementation of LAIS by creating a set of design principles. Moreover, LAIS architecture is proposed for managing processes and technologies. An operational LAIS is developed and implemented at a university for demonstration and evaluation. The research offers not only several conceptual and system artefacts, but also empirical evidence of the opportunities and challenges facing the implementation of LAIS in higher education. This study was guided by the ontology-based design science research (ODSR) approach. The research proposes ODSR as an approach combining the forces of design science research (DSR) and ontology studies for knowledge accumulation and evolution. ODSR offers a semantic view of the research domain, and the use of ontologies provides considerable help throughout the process of creating and evaluating research artefacts in DSR. The ontologies are also considered as research artefacts created and evaluated through DSR cycles. As a DSR methodology, ODSR is multi-methodological and involves multiple iterations of observation, theory building, artefact design, development, demonstration, and evaluation. This thesis follows the “Ph.D. with publications” approach and contains six original research articles. The first article describes the research approach that was used in this study. The second article reviews the literature on learning analytics and related concepts in the context of higher education to provide a holistic view of the domain. The third article examines the critical dimensions of learning analytics and constructs a multi-layered taxonomy of learning analytics applications. The fourth article builds a domain-specific ontology of learning analytics to offer a semantic view. The fifth article derives the proposed conceptual framework for developing learning analytics and demonstrates its application in a specific context, i.e., educational games for learners with intellectual disabilities. The sixth paper develops a set of design principles for LAIS then demonstrates and evaluates them in a case study.
Learning Analytics Explained
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Author : Niall Sclater
language : en
Publisher: Routledge
Release Date : 2017-02-17
Learning Analytics Explained written by Niall Sclater and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-17 with Education categories.
Learning Analytics Explained draws extensively from case studies and interviews with experts in order to discuss emerging applications of the new field of learning analytics. Educational institutions increasingly collect data on students and their learning experiences, a practice that helps enhance courses, identify learners who require support, and provide a more personalized learning experience. There is, however, a corresponding need for guidance on how to carry out institutional projects, intervene effectively with students, and assess legal and ethical issues. This book provides that guidance while also covering the evolving technical architectures, standards, and products within the field.
Learning Analytics In Higher Education
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Author : Jaime Lester
language : en
Publisher: Routledge
Release Date : 2018-08-06
Learning Analytics In Higher Education written by Jaime Lester and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-06 with Education categories.
Learning Analytics in Higher Education provides a foundational understanding of how learning analytics is defined, what barriers and opportunities exist, and how it can be used to improve practice, including strategic planning, course development, teaching pedagogy, and student assessment. Well-known contributors provide empirical, theoretical, and practical perspectives on the current use and future potential of learning analytics for student learning and data-driven decision-making, ways to effectively evaluate and research learning analytics, integration of learning analytics into practice, organizational barriers and opportunities for harnessing Big Data to create and support use of these tools, and ethical considerations related to privacy and consent. Designed to give readers a practical and theoretical foundation in learning analytics and how data can support student success in higher education, this book is a valuable resource for scholars and administrators.
Learning Analytics Fundaments Applications And Trends
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Author : Alejandro Peña-Ayala
language : en
Publisher: Springer
Release Date : 2017-02-17
Learning Analytics Fundaments Applications And Trends written by Alejandro Peña-Ayala and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-17 with Technology & Engineering categories.
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.
Educational Data Mining
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Author : Alejandro Peña-Ayala
language : en
Publisher: Springer
Release Date : 2013-11-08
Educational Data Mining written by Alejandro Peña-Ayala and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-08 with Technology & Engineering categories.
This book is devoted to the Educational Data Mining arena. It highlights works that show relevant proposals, developments, and achievements that shape trends and inspire future research. After a rigorous revision process sixteen manuscripts were accepted and organized into four parts as follows: · Profile: The first part embraces three chapters oriented to: 1) describe the nature of educational data mining (EDM); 2) describe how to pre-process raw data to facilitate data mining (DM); 3) explain how EDM supports government policies to enhance education. · Student modeling: The second part contains five chapters concerned with: 4) explore the factors having an impact on the student's academic success; 5) detect student's personality and behaviors in an educational game; 6) predict students performance to adjust content and strategies; 7) identify students who will most benefit from tutor support; 8) hypothesize the student answer correctness based on eye metrics and mouse click. · Assessment: The third part has four chapters related to: 9) analyze the coherence of student research proposals; 10) automatically generate tests based on competences; 11) recognize students activities and visualize these activities for being presented to teachers; 12) find the most dependent test items in students response data. · Trends: The fourth part encompasses four chapters about how to: 13) mine text for assessing students productions and supporting teachers; 14) scan student comments by statistical and text mining techniques; 15) sketch a social network analysis (SNA) to discover student behavior profiles and depict models about their collaboration; 16) evaluate the structure of interactions between the students in social networks. This volume will be a source of interest to researchers, practitioners, professors, and postgraduate students aimed at updating their knowledge and find targets for future work in the field of educational data mining.
Intelligent Systems And Learning Data Analytics In Online Education
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Author : Santi Caballé
language : en
Publisher: Academic Press
Release Date : 2021-06-15
Intelligent Systems And Learning Data Analytics In Online Education written by Santi Caballé and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-15 with Computers categories.
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
Emerging Issues In Smart Learning
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Author : Guang Chen
language : en
Publisher: Springer
Release Date : 2014-09-10
Emerging Issues In Smart Learning written by Guang Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-10 with Social Science categories.
This book provides an archival forum for researchers, academics, practitioners and industry professionals interested and/or engaged in the reform of the ways of teaching and learning through advancing current learning environments towards smart learning environments. The contributions of this book are submitted to the International Conference on Smart Learning Environments (ICSLE 2014). The focus of this proceeding is on the interplay of pedagogy, technology and their fusion towards the advancement of smart learning environments. Various components of this interplay include but are not limited to: Pedagogy- learning paradigms, assessment paradigms, social factors, policy; Technology- emerging technologies, innovative uses of mature technologies, adoption, usability, standards and emerging/new technological paradigms (open educational resources, cloud computing, etc.)
Handbook Of Digital Higher Education
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Author : Sharpe, Rhona
language : en
Publisher: Edward Elgar Publishing
Release Date : 2022-06-10
Handbook Of Digital Higher Education written by Sharpe, Rhona and has been published by Edward Elgar Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-10 with Education categories.
With the COVID-19 pandemic rapidly escalating higher education’s move online, this timely Handbook offers holistic conceptualisations of digital higher education which consider personal, pedagogic, and organisational level change. Key findings from digital education research are aligned with case studies of institutional practices, to consider the current and future role of digital technologies in higher education.