Data Analytics And Learning
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Adoption Of Data Analytics In Higher Education Learning And Teaching
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Author : Dirk Ifenthaler
language : en
Publisher: Springer Nature
Release Date : 2020-08-10
Adoption Of Data Analytics In Higher Education Learning And Teaching written by Dirk Ifenthaler and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-10 with Education categories.
The book aims to advance global knowledge and practice in applying data science to transform higher education learning and teaching to improve personalization, access and effectiveness of education for all. Currently, higher education institutions and involved stakeholders can derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative, real-time, and predictive or prescriptive insights and recommendations. Educational data mining refers to the process of extracting useful information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms. This volume provides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education.
Data Analytics For Absolute Beginners A Deconstructed Guide To Data Literacy
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Author : Oliver Theobald
language : en
Publisher:
Release Date : 2019-07-21
Data Analytics For Absolute Beginners A Deconstructed Guide To Data Literacy written by Oliver Theobald and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-21 with categories.
While exposure to data has become more or less a daily ritual for the rank-and-file knowledge worker, true understanding-treated in this book as data literacy-resides in knowing what lies behind the data. Everything from the data's source to the specific choice of input variables, algorithmic transformations, and visual representation shape the accuracy, relevance, and value of the data and mark its journey from raw data to business insight. It's also important to grasp the terminology and basic concepts of data analytics as much as it is to have the financial literacy to be successful as a decisionmaker in the business world. In this book, we make sense of data analytics without the assumption that you understand specific data science terminology or advanced programming languages to set you on your path. Topics covered in this book: Data Mining Big Data Machine Learning Alternative Data Data Management Web Scraping Regression Analysis Clustering Analysis Association Analysis Data Visualization Business Intelligence
Learn Data Analytics For Beginners To Core Advance
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Author : Janani Sathish
language : en
Publisher: Independently Published
Release Date : 2021-05
Learn Data Analytics For Beginners To Core Advance written by Janani Sathish and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05 with categories.
Data science has taken the planet by storm. Every field of study and area of business has been affected as people increasingly realize the worth of the incredible quantities of knowledge being generated. But to extract value from those data, one must be trained within the proper data science skills. The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it a useful tool for data scientists round the world. This book is about the basics of R programming. you'll start with the fundamentals of the language, find out how to control datasets, the way to write functions, and the way to debug and optimize code. With the basics provided during this book, you'll have a solid foundation on which to create your data science toolbox. during this book you'll learn what you would like to understand to start assembling and leading a knowledge science enterprise, albeit you've got never worked in data science before. You'll get a crash program in data science in order that you'll be familiar with the sector and understand your role as a pacesetter . You'll also find out how to recruit, assemble, evaluate, and develop a team with complementary skill sets and roles. You'll learn the structure of the info science pipeline, the goals of every stage, and the way to stay your team on track throughout. Finally, you'll learn some down-to-earth practical skills which will assist you overcome the common challenges that regularly derail data science projects Reproducibility is that the concept data analyses should be published or made available with their data and software code in order that others may verify the findings and repose on them.
Deep Learning In Data Analytics
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Author : Debi Prasanna Acharjya
language : en
Publisher: Springer Nature
Release Date : 2021-08-11
Deep Learning In Data Analytics written by Debi Prasanna Acharjya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-11 with Technology & Engineering categories.
This book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various deep learning applications. The book discusses significant issues relating to deep learning in data analytics. Further in-depth reading can be done from the detailed bibliography presented at the end of each chapter. Besides, this book's material includes concepts, algorithms, figures, graphs, and tables in guiding researchers through deep learning in data science and its applications for society. Deep learning approaches prevent loss of information and hence enhance the performance of data analysis and learning techniques. It brings up many research issues in the industry and research community to capture and access data effectively. The book provides the conceptual basis of deep learning required to achieve in-depth knowledge in computer and data science. It has been done to make the book more flexible and to stimulate further interest in topics. All these help researchers motivate towards learning and implementing the concepts in real-life applications.
Data Analytics Applications In Education
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Author : Jan Vanthienen
language : en
Publisher: CRC Press
Release Date : 2017-09-29
Data Analytics Applications In Education written by Jan Vanthienen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-29 with Business & Economics categories.
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.
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.
Learn Data Analytics For Beginners
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Author : Landon Adrian
language : en
Publisher:
Release Date : 2019-08-11
Learn Data Analytics For Beginners written by Landon Adrian and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-11 with categories.
Data science has taken the world by storm. Every field of study and area of business has been affected as people increasingly realize the value of the incredible quantities of data being generated. But to extract value from those data, one needs to be trained in the proper data science skills. The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it an invaluable tool for data scientists around the world. This book is about the fundamentals of R programming.Finally, you'll learn some down-to-earth practical skills that will help you overcome the common challenges that frequently derail data science projects Reproducibility is the idea that data analyses should be published or made available with their data and software code so that others may verify the findings and build upon them. The need for reproducible report writing is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations. Reproducibility allows for people to focus on the actual content of a data analysis, rather than on superficial details reported in a written summary. In addition, reproducibility makes an analysis more useful to others because the data and code that actually conducted the analysis are available.
Educational Data Analytics For Teachers And School Leaders
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Author : Sofia Mougiakou
language : en
Publisher: Springer Nature
Release Date : 2022-10-28
Educational Data Analytics For Teachers And School Leaders written by Sofia Mougiakou and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-28 with Education categories.
Educational Data Analytics (EDA) have been attributed with significant benefits for enhancing on-demand personalized educational support of individual learners as well as reflective course (re)design for achieving more authentic teaching, learning and assessment experiences integrated into real work-oriented tasks. This open access textbook is a tutorial for developing, practicing and self-assessing core competences on educational data analytics for digital teaching and learning. It combines theoretical knowledge on core issues related to collecting, analyzing, interpreting and using educational data, including ethics and privacy concerns. The textbook provides questions and teaching materials/ learning activities as quiz tests of multiple types of questions, added after each section, related to the topic studied or the video(s) referenced. These activities reproduce real-life contexts by using a suitable use case scenario (storytelling), encouraging learners to link theory with practice; self-assessed assignments enabling learners to apply their attained knowledge and acquired competences on EDL. By studying this book, you will know where to locate useful educational data in different sources and understand their limitations; know the basics for managing educational data to make them useful; understand relevant methods; and be able to use relevant tools; know the basics for organising, analysing, interpreting and presenting learner-generated data within their learning context, understand relevant learning analytics methods and be able to use relevant learning analytics tools; know the basics for analysing and interpreting educational data to facilitate educational decision making, including course and curricula design, understand relevant teaching analytics methods and be able to use relevant teaching analytics tools; understand issues related with educational data ethics and privacy. This book is intended for school leaders and teachers engaged in blended (using the flipped classroom model) and online (during COVID-19 crisis and beyond) teaching and learning; e-learning professionals (such as, instructional designers and e-tutors) of online and blended courses; instructional technologists; researchers as well as undergraduate and postgraduate university students studying education, educational technology and relevant fields.
Data Analytics
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Author : Shuai Huang
language : en
Publisher: CRC Press
Release Date : 2021-04-15
Data Analytics written by Shuai Huang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-15 with Mathematics categories.
Data Analytics: A Small Data Approach is suitable for an introductory data analytics course to help students understand some main statistical learning models. It has many small datasets to guide students to work out pencil solutions of the models and then compare with results obtained from established R packages. Also, as data science practice is a process that should be told as a story, in this book there are many course materials about exploratory data analysis, residual analysis, and flowcharts to develop and validate models and data pipelines. The main models covered in this book include linear regression, logistic regression, tree models and random forests, ensemble learning, sparse learning, principal component analysis, kernel methods including the support vector machine and kernel regression, and deep learning. Each chapter introduces two or three techniques. For each technique, the book highlights the intuition and rationale first, then shows how mathematics is used to articulate the intuition and formulate the learning problem. R is used to implement the techniques on both simulated and real-world dataset. Python code is also available at the book’s website: http://dataanalyticsbook.info.
Learning Analytics Cookbook
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Author : Roope Jaakonmäki
language : en
Publisher: Springer
Release Date : 2020-06-20
Learning Analytics Cookbook written by Roope Jaakonmäki and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-20 with Business & Economics categories.
This book offers an introduction and hands-on examples that demonstrate how Learning Analytics (LA) can be used to enhance digital learning, teaching and training at various levels. While the majority of existing literature on the subject focuses on its application at large corporations, this book develops and showcases approaches that bring LA closer to smaller organizations, and to educational institutions that lack sufficient resources to implement a full-fledged LA infrastructure. In closing, the book introduces a set of software tools for data analytics and visualization, and explains how they can be employed in several LA scenarios.