Learning Analytics Cookbook
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Learning Analytics Cookbook
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Author : Roope Jaakonmäki
language : en
Publisher: Springer Nature
Release Date : 2020-06-19
Learning Analytics Cookbook written by Roope Jaakonmäki and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-19 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.
Visualizations And Dashboards For Learning Analytics
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Author : Muhittin Sahin
language : en
Publisher: Springer Nature
Release Date : 2021-12-16
Visualizations And Dashboards For Learning Analytics written by Muhittin Sahin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-16 with Education categories.
This edited volume fills the gaps in existing literature on visualization and dashboard design for learning analytics. To do so, it presents critical tips to stakeholders and acts as guide to efficient implementation. The book covers the following topics: visualization and dashboard design for learning analytics, visualization and dashboard preferences of stakeholders, learners’ patterns on the dashboard, usability of visualization techniques and the dashboard, dashboard and intervention design, learning and instructional design for learning analytics, privacy and security issues about the dashboard, and future directions of visualization and dashboard design. This book will be of interest to researchers with interest in learning analytics and data analytics, teachers and students in higher education institutions and instructional designers, as it includes contributions from a wide variety of educational and psychological researchers, engineers, instructional designers, learning scientists, and computer scientists interested in learning analytics.
Educational Data Science Essentials Approaches And Tendencies
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Author : Alejandro Peña-Ayala
language : en
Publisher: Springer Nature
Release Date : 2023-04-29
Educational Data Science Essentials Approaches And Tendencies written by Alejandro Peña-Ayala and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-29 with Computers categories.
This book describes theoretical elements, practical approaches, and specialized tools that systematically organize, characterize, and analyze big data gathered from educational affairs and settings. Moreover, the book shows several inference criteria to leverage and produce descriptive, explanatory, and predictive closures to study and understand education phenomena at in classroom and online environments. This is why diverse researchers and scholars contribute with valuable chapters to ground with well-–sounded theoretical and methodological constructs in the novel field of Educational Data Science (EDS), which examines academic big data repositories, as well as to introduces systematic reviews, reveals valuable insights, and promotes its application to extend its practice. EDS as a transdisciplinary field relies on statistics, probability, machine learning, data mining, and analytics, in addition to biological, psychological, and neurological knowledge aboutlearning science. With this in mind, the book is devoted to those that are in charge of educational management, educators, pedagogues, academics, computer technologists, researchers, and postgraduate students, who pursue to acquire a conceptual, formal, and practical landscape of how to deploy EDS to build proactive, real- time, and reactive applications that personalize education, enhance teaching, and improve learning! Chapter “Sync Ratio and Cluster Heat Map for Visualizing Student Engagement” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Artificial Intelligence For Education
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Author : Mario Allegra
language : en
Publisher: Frontiers Media SA
Release Date : 2023-11-27
Artificial Intelligence For Education written by Mario Allegra and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-27 with Education categories.
What learning, teaching, and education will be in the next future is an open question. Nevertheless, believing that an increasing prevalence of AI may not influence the education field seems objectively unlikely. In recent years, the new renaissance of AI has stimulated discussion on how advances in AI can influence the educational sector and the future educational policies and the impact of AI on Technology-Enhanced Learning (TEL). On the other side, the attention of the education sector in artificial intelligence is complemented by the consideration that, since the early days of AI, researchers have shown for the education sector, which has often seen education as one of the preferred application areas. The interaction between the AI and TEL research fields led to the investigation of how the advance in AI could support the development of flexible, inclusive, personalized, engaging, and effective learning tools. Besides, research in this area could be a powerful tool to open the "learning black box" by providing a deeper understanding of how learning occurs. The proposed Research Topic aims to gather contributions that provide a comprehensive picture of how AI is changing educational practices and how the key stakeholders in the educational community (i.e., students, teachers, faculty, and families) perceive this ongoing change. Relevant topics include (but are not limited to): ● AI applications in real-world educational settings ● Intelligent Tutoring Systems ● Adaptive learning environments ● Learning design and AI ● Students profiling: definition of the student model and ethical implications ● Intelligent techniques for objective and integrated students evaluation in TEL ● Teachers' competencies for effective integration of AI into Education ● Teachers’ perceptions of AI: prejudices and attitudes ● The role of cognitive architectures in Education ● Serious games and AI ● Social robotics in Education
R Data Analysis Cookbook
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Author : Viswa Viswanathan
language : en
Publisher: Packt Publishing
Release Date : 2015-05-27
R Data Analysis Cookbook written by Viswa Viswanathan and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-27 with Computers categories.
This book is ideal for those who are already exposed to R, but have not yet used it extensively for data analytics and are seeking to get up and running quickly for analytics tasks. This book will help people who aspire to enhance their skills in any of the following ways:• perform advanced analyses and create informative and professional charts• become proficient in acquiring data from many sources• apply supervised and unsupervised data mining techniques• use R's features to present analyses professionally
Analytika U En A Data Mining Ve Vzd L V N V Kontextu Syst M Pro Zen V Uky
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Author : Libor Juhaňák
language : cs
Publisher: Masarykova univerzita
Release Date : 2023-01-01
Analytika U En A Data Mining Ve Vzd L V N V Kontextu Syst M Pro Zen V Uky written by Libor Juhaňák and has been published by Masarykova univerzita this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-01 with Crafts & Hobbies categories.
Analytika učení a data mining ve vzdělávání jsou nově se formující výzkumné oblasti zaměřující se na analýzu dat, která pocházejí z různých typů online vzdělávacích systémů. Tato publikace nabízí základní vhled do obou oblastí včetně jejich detailního představení. Seznamuje čtenáře s původem analytiky učení i data miningu ve vzdělávání, vysvětluje hlavní podobnosti a rozdíly mezi těmito oblastmi, popisuje používané metody a techniky analýzy dat a představuje nejvýznamnější směry výzkumu napříč oběma oblastmi. Kniha navíc obsahuje příklady konkrétních analýz, při kterých byly využity vybrané metody analytiky učení a data miningu ve vzdělávání v kontextu systémů pro řízení výuky.
Python Machine Learning Cookbook
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Author : Giuseppe Ciaburro
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-03-30
Python Machine Learning Cookbook written by Giuseppe Ciaburro and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-30 with Computers categories.
Discover powerful ways to effectively solve real-world machine learning problems using key libraries including scikit-learn, TensorFlow, and PyTorch Key FeaturesLearn and implement machine learning algorithms in a variety of real-life scenariosCover a range of tasks catering to supervised, unsupervised and reinforcement learning techniquesFind easy-to-follow code solutions for tackling common and not-so-common challengesBook Description This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks. With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine learning. By the end of this book, you will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples. What you will learnUse predictive modeling and apply it to real-world problemsExplore data visualization techniques to interact with your dataLearn how to build a recommendation engineUnderstand how to interact with text data and build models to analyze itWork with speech data and recognize spoken words using Hidden Markov ModelsGet well versed with reinforcement learning, automated ML, and transfer learningWork with image data and build systems for image recognition and biometric face recognitionUse deep neural networks to build an optical character recognition systemWho this book is for This book is for data scientists, machine learning developers, deep learning enthusiasts and Python programmers who want to solve real-world challenges using machine-learning techniques and algorithms. If you are facing challenges at work and want ready-to-use code solutions to cover key tasks in machine learning and the deep learning domain, then this book is what you need. Familiarity with Python programming and machine learning concepts will be useful.
The Information Literacy Cookbook
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Author : Jane Secker
language : en
Publisher: Chandos Publishing
Release Date : 2007-09-14
The Information Literacy Cookbook written by Jane Secker and has been published by Chandos Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-14 with Business & Economics categories.
Offers an overview of information literacy (IL) in practice. This book demonstrates how librarians can cultivate a better understanding of IL in their own organisations. It includes an overview of information literacy in higher education, the schools sector, public libraries, the health service and the commercial sector.
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.
R Machine Learning By Example
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Author : Raghav Bali
language : en
Publisher:
Release Date : 2016
R Machine Learning By Example written by Raghav Bali and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Computers categories.
Understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfullyAbout This Book* Get to grips with the concepts of machine learning through exciting real-world examples* Visualize and solve complex problems by using power-packed R constructs and its robust packages for machine learning* Learn to build your own machine learning system with this example-based practical guideWho This Book Is ForIf you are interested in mining useful information from data using state-of-the-art techniques to make data-driven decisions, this is a go-to guide for you. No prior experience with data science is required, although basic knowledge of R is highly desirable. Prior knowledge in machine learning would be helpful but is not necessary.What You Will Learn* Utilize the power of R to handle data extraction, manipulation, and exploration techniques* Use R to visualize data spread across multiple dimensions and extract useful features* Explore the underlying mathematical and logical concepts that drive machine learning algorithms* Dive deep into the world of analytics to predict situations correctly* Implement R machine learning algorithms from scratch and be amazed to see the algorithms in action* Write reusable code and build complete machine learning systems from the ground up* Solve interesting real-world problems using machine learning and R as the journey unfolds* Harness the power of robust and optimized R packages to work on projects that solve real-world problems in machine learning and data scienceIn DetailData science and machine learning are some of the top buzzwords in the technical world today. From retail stores to Fortune 500 companies, everyone is working hard to making machine learning give them data-driven insights to grow their business. With powerful data manipulation features, machine learning packages, and an active developer community, R empowers users to build sophisticated machine learning systems to solve real-world data problems.This book takes you on a data-driven journey that starts with the very basics of R and machine learning and gradually builds upon the concepts to work on projects that tackle real-world problems.You'll begin by getting an understanding of the core concepts and definitions required to appreciate machine learning algorithms and concepts. Building upon the basics, you will then work on three different projects to apply the concepts of machine learning, following current trends and cover major algorithms as well as popular R packages in detail. These projects have been neatly divided into six different chapters covering the worlds of e-commerce, finance, and social-media, which are at the very core of this data-driven revolution. Each of the projects will help you to understand, explore, visualize, and derive insights depending upon the domain and algorithms.Through this book, you will learn to apply the concepts of machine learning to deal with data-related problems and solve them using the powerful yet simple language, R.Style and approachThe book is an enticing journey that starts from the very basics to gradually pick up pace as the story unfolds. Each concept is first defined in the larger context of things succinctly, followed by a detailed explanation of their application. Each topic is explained with the help of a project that solves a real real-world problem involving hands-on work thus giving you a deep insight into the world of machine learning.