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Book
Educational Data Analytics for Teachers and School Leaders
Authors: --- --- --- --- --- et al.
ISBN: 3031152662 3031152654 Year: 2023 Publisher: Cham Springer Nature

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Abstract

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.


Book
Software reliability growth models
Authors: ---
ISBN: 9811600252 9811600244 Year: 2021 Publisher: Singapore : Springer,


Book
Statistical learning and modeling in data analysis : methods and applications
Author:
ISBN: 3030699447 3030699439 Year: 2021 Publisher: Cham, Switzerland : Springer,


Book
Methods for the analysis of asymmetric proximity data
Authors: --- ---
ISBN: 9811631727 9811631719 Year: 2021 Publisher: Gateway East, Singapore : Springer,

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Abstract

This book provides an accessible introduction and practical guidelines to apply asymmetric multidimensional scaling, cluster analysis, and related methods to asymmetric one-mode two-way and three-way asymmetric data. A major objective of this book is to present to applied researchers a set of methods and algorithms for graphical representation and clustering of asymmetric relationships. Data frequently concern measurements of asymmetric relationships between pairs of objects from a given set (e.g., subjects, variables, attributes,…), collected in one or more matrices. Examples abound in many different fields such as psychology, sociology, marketing research, and linguistics and more recently several applications have appeared in technological areas including cybernetics, air traffic control, robotics, and network analysis. The capabilities of the presented algorithms are illustrated by carefully chosen examples and supported by extensive data analyses. A review of the specialized statistical software available for the applications is also provided. This monograph is highly recommended to readers who need a complete and up-to-date reference on methods for asymmetric proximity data analysis.


Book
Nonlinear Dimensionality Reduction Techniques
Authors: --- --- ---
ISBN: 9783030810269 Year: 2022 Publisher: Cham Springer International Publishing :Imprint: Springer


Book
Nonlinear dimensionality reduction techniques : a data structure preservation approach
Authors: --- ---
ISBN: 3030810259 3030810267 Year: 2022 Publisher: Cham, Switzerland : Springer,

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