Big data in education: pedagogy and research

Author(s)

    • Prodromou, Theodosia

Bibliographic Information

Big data in education: pedagogy and research

Theodosia Prodromou, editor

(Policy implications of research in education, 13)

Springer, c2021

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Note

Includes bibliographical references and index

Description and Table of Contents

Description

This book discusses how Big Data could be implemented in educational settings and research, using empirical data and suggesting both best practices and areas in which to invest future research and development. It also explores: 1) the use of learning analytics to improve learning and teaching; 2) the opportunities and challenges of learning analytics in education. As Big Data becomes a common part of the fabric of our world, education and research are challenged to use this data to improve educational and research systems, and also are tasked with teaching coming generations to deal with Big Data both effectively and ethically. The Big Data era is changing the data landscape for statistical analysis, the ways in which data is captured and presented, and the necessary level of statistical literacy to analyse and interpret data for future decision making. The advent of Big Data accentuates the need to enable citizens to develop statistical skills, thinking and reasoning needed for representing, integrating and exploring complex information. This book offers guidance to researchers who are seeking suitable topics to explore. It presents research into the skills needed by data practitioners (data analysts, data managers, statisticians, and data consumers, academics), and provides insights into the statistical skills, thinking and reasoning needed by educators and researchers in the future to work with Big Data. This book serves as a concise reference for policymakers, who must make critical decisions regarding funding and applications.

Table of Contents

Contents List of Figures and Tables Notes on Contributors Introduction Part 1 Theoretical and ethical concerns 1 Big Data in academic research-Challenges, pitfalls, and opportunities Jacques Raubenheimer Part 2 Teaching people to use Big Data effectively 2 Big Data for Early Learners Peter Howley, Kevin Wang, Ayse Aysin Bilgin 3 Using Big Data in a Master of Applied Statistics unit Ayse Aysin Bilgin, Peter Howley 4 Statistical education as part of the digital transformation of statistical offices Markus Zwick, Sabine Koehler Part 3 Using Big Data to improve teaching 5 Big data, analytics and education: Challenges, opportunities and an example from a large university unit Ron S. Kenett, Theodosia Prodromou 6 Enhancing learning outcomes with 'big data' from pedagogy for conceptual thinking with meaning equivalence reusable learning objects (MERLO) and interactive concept discovery (INCOD) Masha Etkind, Theodosia Prodromou, Uri Shafrir 7 Employing Authentic Analytics for More Authentic Tasks William Billingsley, Peter Fletcher 8 Learning from Learning Analytics: How much do we know about patterns of student engagement? Belinda A. Chiera, Malgorzata W. Korolkiewicz, Lisa J. Schultz Part 4 Educational systems that use Big Data 9 Museum Big Data: Perceptions and practices Georgios Papaioannou 10 Analysing aspects of Brazilian curricula for teaching statistics involving Big Data Carlos Eduardo Ferreira Monteiro, Maria Niedja Pereira Martins, Theodosia Prodromou Part 5 11 Concluding Comments Theodosia Prodromou

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Details

  • NCID
    BC11641333
  • ISBN
    • 9783030768409
  • Country Code
    sz
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    Cham
  • Pages/Volumes
    xii, 247 p.
  • Size
    25 cm
  • Parent Bibliography ID
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