Big Data, analítica del aprendizaje y educación basada en datos (Big Data, Learning Analytics & Data-driven Education).

Big Data, analítica del aprendizaje y educación basada en datos (Big Data, Learning Analytics & Data-driven Education).
Author: Daniel Domínguez Figaredo
Publisher:
Total Pages: 0
Release: 2018
Genre:
ISBN:

Spanish Abstract: Los procesos relacionados con la enseñanza y el aprendizaje generan una enorme cantidad de datos que pueden utilizarse con múltiples fines, entre los que destacan los de mejora de los propios métodos y prácticas educativas. La información recopilada en procesos como la interacción social entre estudiantes y docentes, la consulta de los recursos de apoyo al estudio o el envío de evidencias de aprendizaje, es de gran valor para los responsables del diseño de cursos, para los gestores de las instituciones educativas y también para los estudiantes. El uso adecuado de esos datos está relacionado con un conjunto de aspectos que abarcan campos diversos como la tecnología, la pedagogía, la ética y el derecho. En este capítulo se propone una aproximación a esos aspectos desde un enfoque mixto que combina lo conceptual y lo aplicado. En un principio se define el campo del big data desde una dimensión social, considerando las numerosas disciplinas que basan su actividad en los datos masivos. A continuación se pone el foco en el campo de la educación y especialmente en la analítica del aprendizaje, ámbito que atiende a la gestión, análisis y búsqueda de soluciones a partir de los datos digitales que se procesan durante la enseñanza. Dada la amplitud y trascendencia del campo de la analítica del aprendizaje, su explicación y dominio están entre los principales objetivos de este texto. El capítulo finaliza con una referencia al conjunto de problemas relacionados con la privacidad de los datos personales. Y por último se discuten algunos de los apriorismos más habituales en el tratamiento del big data y que dan lugar a interpretaciones equivocadas o que no se corresponden con lo que ocurre en realidad. El objetivo es dotar a los estudiantes y profesionales del campo de la educación de un conocimiento básico sobre el uso y gestión de datos masivos en procesos de aprendizaje, así como de herramientas metodológicas para utilizar esos datos en la mejora de sus cursos y prácticas de enseñanza.

Advancing the Power of Learning Analytics and Big Data in Education

Advancing the Power of Learning Analytics and Big Data in Education
Author: Ana Azevedo
Publisher: Information Science Reference
Total Pages:
Release: 2020-11
Genre: Computer-assisted instruction
ISBN: 9781799871033

"This book reports on the role and impact of learning analytics training and development in education, investigating how various stakeholders are engaged in the design, deployment and assessment of successful and sustainable learning analytics"--

Adoption of Data Analytics in Higher Education Learning and Teaching

Adoption of Data Analytics in Higher Education Learning and Teaching
Author: Dirk Ifenthaler
Publisher: Springer Nature
Total Pages: 464
Release: 2020-08-10
Genre: Education
ISBN: 3030473929

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.

Learning Analytics: Fundaments, Applications, and Trends

Learning Analytics: Fundaments, Applications, and Trends
Author: Alejandro Peña-Ayala
Publisher: Springer
Total Pages: 310
Release: 2017-02-17
Genre: Technology & Engineering
ISBN: 3319529773

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.

A Beginner’s Guide to Learning Analytics

A Beginner’s Guide to Learning Analytics
Author: Srinivasa K G
Publisher: Springer Nature
Total Pages: 326
Release: 2021-04-19
Genre: Education
ISBN: 3030702588

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.

Applying Data Science and Learning Analytics Throughout a Learner’s Lifespan

Applying Data Science and Learning Analytics Throughout a Learner’s Lifespan
Author: Trajkovski, Goran
Publisher: IGI Global
Total Pages: 314
Release: 2022-05-06
Genre: Education
ISBN: 1799896463

Research in the domains of learning analytics and educational data mining has prototyped an approach where methodologies from data science and machine learning are used to gain insights into the learning process by using large amounts of data. As many training and academic institutions are maturing in their data-driven decision making, useful, scalable, and interesting trends are emerging. Organizations can benefit from sharing information on those efforts. Applying Data Science and Learning Analytics Throughout a Learner’s Lifespan examines novel and emerging applications of data science and sister disciplines for gaining insights from data to inform interventions into learners’ journeys and interactions with academic institutions. Data is collected at various times and places throughout a learner’s lifecycle, and the learners and the institution should benefit from the insights and knowledge gained from this data. Covering topics such as learning analytics dashboards, text network analysis, and employment recruitment, this book is an indispensable resource for educators, computer scientists, faculty of higher education, government officials, educational administration, students of higher education, pre-service teachers, business professionals, researchers, and academicians.

Learning Analytics Cookbook

Learning Analytics Cookbook
Author: Roope Jaakonmäki
Publisher: Springer Nature
Total Pages: 99
Release: 2020-06-19
Genre: Business & Economics
ISBN: 3030433773

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.

Big Data en Educación

Big Data en Educación
Author: Ben Williamson
Publisher: Ediciones Morata
Total Pages: 315
Release: 2018-09-25
Genre: Education
ISBN: 847112890X

Los macrodatos o la inteligencia de datos tienen el poder de transformar la educación y la investigación educativa. Gobiernos, investigadoras e investigadores y empresas están comprendiendo el potencial que ofrecen para informar ideas, políticas, contribuir al desarrollo de nuevas herramientas educativas y de formas innovadoras de realizar la enseñanza y de llevar a cabo investigaciones. Este libro focaliza en un imaginario poder de los macrodatos en educación que anima las actividades de quienes desarrollan aplicaciones educativas; en las potencialidades del análisis de datos a alta velocidad en tiempo real, en la supuesta objetividad de los algoritmos, en la posibilidad de aprehender una gran diversidad de actividades de aprendizaje, en el potencial para predecir o anticipar eventos futuros y en la posibilidad de poder dar forma al futuro a través de intervenciones tecnológicas específicas. Por tanto, se requieren nuevos tipos de alfabetización para que los datos personales y escolares se utilicen de manera informada y ética, pues entre otros asuntos, la próxima ola de desarrollos está diseñada para extraer datos mucho más íntimos de los cuerpos del alumnado, de sus rostros e incluso sus cerebros. Big Data en Educación pretende ser una introducción crítica a desarrollos tecnológicos para educación basados en macrodatos, en la inteligencia artificial y en el poder algorítmico. Entre los temas clave que aquí se abordan, cabe destacar: •El rol del aprendizaje y de los datos escolares en las instituciones educativas. •Una apreciación crítica del código, de los algoritmos y de las infraestructuras. •El auge de las aulas cognitivas y la aplicación práctica de algoritmos computacionales a entornos de aprendizaje •Los aspectos a tener en cuenta en los métodos de investigación digital. Una lectura esencial para cualquiera que estudie o trabaje en el contexto educativo actual.

Emerging Trends in Learning Analytics

Emerging Trends in Learning Analytics
Author:
Publisher: BRILL
Total Pages: 297
Release: 2019-05-07
Genre: Education
ISBN: 9004399275

This book documents recent attempts to conduct systematic, prodigious and multidisciplinary research in learning analytics and present their findings and identify areas for further research and development. The book also unveils the distinguished and exemplary works by educators and researchers in the field highlighting the current trends, privacy and ethical issues, creative and unique approaches, innovative methods, frameworks, and theoretical and practical aspects of learning analytics.

Data Analytics and Adaptive Learning

Data Analytics and Adaptive Learning
Author: Patsy D. Moskal
Publisher: Taylor & Francis
Total Pages: 364
Release: 2023-08-25
Genre: Education
ISBN: 100092923X

Data Analytics and Adaptive Learning offers new insights into the use of emerging data analysis and adaptive techniques in multiple learning settings. In recent years, both analytics and adaptive learning have helped educators become more responsive to learners in virtual, blended, and personalized environments. This set of rich, illuminating, international studies spans quantitative, qualitative, and mixed-methods research in higher education, K–12, and adult/continuing education contexts. By exploring the issues of definition and pedagogical practice that permeate teaching and learning and concluding with recommendations for the future research and practice necessary to support educators at all levels, this book will prepare researchers, developers, and graduate students of instructional technology to produce evidence for the benefits and challenges of data-driven learning.