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Cited by 883Online Learning and AnalyticsDigital Education and SocietyEducational and Technological Research

Big Data in Education: The digital future of learning, policy and practice

Williamson, Ben·2017·SAGE Publications Ltd eBooks
DOI 10.4135/9781529714920
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Abstract

Big data has the power to transform education and educational research. Governments, researchers and commercial companies are only beginning to understand the potential that big data offers in informing policy ideas, contributing to the development of new educational tools and innovative ways of conducting research. This cutting-edge overview explores the current state-of-play, looking at big data and the related topic of computer code to examine the implications for education and schooling for today and the near future. Key topics include: • The role of learning analytics and educational data science in schools • A critical appreciation of code, algorithms and infrastructures • The rise of 'cognitive classrooms', and the practical application of computational algorithms to learning environments • Important digital research methods issues for researchers This is essential reading for anyone studying or working in today's education environment!

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Crossref · 10.4135/9781529714920

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Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • When embedded in the prompt sequence, ChatGPT generated six references, five of which were hallucinated references, and one genuine reference cited with the correct year.

    “When embedded in the prompt sequence, however, ChatGPT generated six references, five of which were hallucinated references. One, however, was genuine and was cited with the correct year ('Big Data in Education: The Digital Future of Learning, Policy and Practice' 2027) (Williamson, 2017).”

    From How Unique Are Hallucinated Citations Offered by Generative Artificial Intelligence Models? (2026) · cites this paper as Williamson, 2017

  • ChatGPT offered to provide a list of actual titles, two of which were genuine [26,27] and three were hallucinated.

    “It offered to provide a list of actual titles, two of which were genuine [26,27] and three were hallucinated.”

    From How unique are hallucinated citations offered by generative Artificial Intelligence models? (2026) · cites this paper as [26]

  • One of the six references generated by ChatGPT was genuine and was cited with the correct year ('Big Data in Education: The Digital Future of Learning, Policy and Practice' 2027).

    “One, however, was genuine and was cited with the correct year ('Big Data in Education: The Digital Future of Learning, Policy and Practice' 2027). [26]”

    From How unique are hallucinated citations offered by generative Artificial Intelligence models? (2026) · cites this paper as [26]

  • This perspective aligns with sociological analyses of AI in education that emphasize the redistribution of agency and the reconfiguration of pedagogical power.

    “This perspective aligns with sociological analyses of AI in education that emphasize the redistribution of agency and the reconfiguration of pedagogical power [34,41].”

    From Who speaks when machines read scripture: boundary-making and interpretive authority in AI-mediated religious knowledge (2026) · cites this paper as [41]

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Authors
Williamson, B.
Affiliations
University of Edinburgh (GB)
Corresponding author
Williamson, Ben
ORCID
Williamson, Ben
Venue
SAGE Publications Ltd eBooks
Publisher
SAGE Publications Ltd
Published
2017
DOI
10.4135/9781529714920
OpenAlex
W2999199799
Cited by
883
References
0
Citations by year
2026: 310 · 2025: 141 · 2024: 89 · 2023: 79 · 2022: 66 · 2021: 70 · 2020: 69 · 2019: 43 · 2018: 15 · 2017: 1
FWCI
42.47
Type
book
Language
en
Open access
closed
Locations
SAGE Publications Ltd eBooks (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
  • Physical Sciences › Computer Science › Information Systems › Digital Education and Society
  • Physical Sciences › Computer Science › Information Systems › Educational and Technological Research
Keywords
big data in education, learning analytics, educational data science, digital research methods, education policy, schools

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