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Data Analytics in e-Learning: Approaches and Applications

2022-03-22 Computers
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Release : 2022-03-22
Genre : Computers
Kind : eBook
Book Rating : 445/5 ( reviews)

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Book Synopsis Data Analytics in e-Learning: Approaches and Applications by : Marian Cristian Mihăescu

Download or read book Data Analytics in e-Learning: Approaches and Applications written by Marian Cristian Mihăescu. This book was released on 2022-03-22. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Data Analytics in E-Learning: Approaches and Applications

2022
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Release : 2022
Genre :
Kind : eBook
Book Rating : 454/5 ( reviews)

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Book Synopsis Data Analytics in E-Learning: Approaches and Applications by : Marian Cristian Mihăescu

Download or read book Data Analytics in E-Learning: Approaches and Applications written by Marian Cristian Mihăescu. This book was released on 2022. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Computational Learning Approaches to Data Analytics in Biomedical Applications

2019-11-20 Technology & Engineering
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Release : 2019-11-20
Genre : Technology & Engineering
Kind : eBook
Book Rating : 831/5 ( reviews)

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Book Synopsis Computational Learning Approaches to Data Analytics in Biomedical Applications by : Khalid Al-Jabery

Download or read book Computational Learning Approaches to Data Analytics in Biomedical Applications written by Khalid Al-Jabery. This book was released on 2019-11-20. Available in PDF, EPUB and Kindle. Book excerpt: Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis using varied machine learning and statistical techniques. It presents insights on biomedical data processing, innovative clustering algorithms and techniques, and connections between statistical analysis and clustering. The book introduces and discusses the major problems relating to data analytics, provides a review of influential and state-of-the-art learning algorithms for biomedical applications, reviews cluster validity indices and how to select the appropriate index, and includes an overview of statistical methods that can be applied to increase confidence in the clustering framework and analysis of the results obtained. Includes an overview of data analytics in biomedical applications and current challenges Updates on the latest research in supervised learning algorithms and applications, clustering algorithms and cluster validation indices Provides complete coverage of computational and statistical analysis tools for biomedical data analysis Presents hands-on training on the use of Python libraries, MATLAB® tools, WEKA, SAP-HANA and R/Bioconductor

Data Analytics Applications in Education

2017-09-29 Business & Economics
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Release : 2017-09-29
Genre : Business & Economics
Kind : eBook
Book Rating : 284/5 ( reviews)

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Book Synopsis Data Analytics Applications in Education by : Jan Vanthienen

Download or read book Data Analytics Applications in Education written by Jan Vanthienen. This book was released on 2017-09-29. Available in PDF, EPUB and Kindle. Book excerpt: The abundance of data and the rise of new quantitative and statistical techniques have created a promising area: data analytics. This combination of a culture of data-driven decision making and techniques to include domain knowledge allows organizations to exploit big data analytics in their evaluation and decision processes. Also, in education and learning, big data analytics is being used to enhance the learning process, to evaluate efficiency, to improve feedback, and to enrich the learning experience. As every step a student takes in the online world can be traced, analyzed, and used, there are plenty of opportunities to improve the learning process of students. First, data analytics techniques can be used to enhance the student’ s learning process by providing real-time feedback, or by enriching the learning experience. Second, data analytics can be used to support the instructor or teacher. Using data analytics, the instructor can better trace, and take targeted actions to improve, the learning process of the student. Third, there are possibilities in using data analytics to measure the performance of instructors. Finally, for policy makers, it is often unclear how schools use their available resources to "produce" outcomes. By combining structured and unstructured data from various sources, data analytics might provide a solution for governments that aim to monitor the performance of schools more closely. Data analytics in education should not be the domain of a single discipline. Economists should discuss the possibilities, issues, and normative questions with a multidisciplinary team of pedagogists, philosophers, computer scientists, and sociologists. By bringing together various disciplines, a more comprehensive answer can be formulated to the challenges ahead. This book starts this discussion by highlighting some economic perspectives on the use of data analytics in education. The book begins a rich, multidisciplinary discussion that may make data analytics in education seem as natural as a teacher in front of a classroom.

Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics

2022-03-09 Computers
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Release : 2022-03-09
Genre : Computers
Kind : eBook
Book Rating : 970/5 ( reviews)

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Book Synopsis Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics by : Abhishek Kumar

Download or read book Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics written by Abhishek Kumar. This book was released on 2022-03-09. Available in PDF, EPUB and Kindle. Book excerpt: In the last two decades, machine learning has developed dramatically and is still experiencing a fast and everlasting change in paradigms, methodology, applications and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on their diversity and complexity. Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case studies and a panoramic view of data and machine learning techniques, providing the opportunity for novel insights and discoveries. The book explores the theory and practical applications in healthcare and includes a guided tour of machine learning algorithms, architecture design and interdisciplinary challenges. This book is useful for research scholars and students involved in critical condition analysis and computation models.

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