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[40] explains that there is potential for the use of linked data in Education because of the open educational resources produced by many universities: "... while the content of open educational resources is by definition accessible and reusable, publishing the corresponding metadata as Linked Data can make the content of different repositories more discoverable, accessible and connectable.
Big data in education can be also utilized to observe educational shortages to enhance study curriculums.
Rather than a diabolical plot to sell student data to the highest bidder (as it was often mischaracterised by critics and in the press), inBloom was meant to be a solution to the problem of data in education.
His research focuses on digital technology and education policy, and his latest book is Big Data in Education: The digital future of learning, policy and practice.
Big data in education is generated mainly by collecting data on people (e.g. students, teachers, parents, administrators, and other support personnel), infrastructures (e.g. schools, libraries, computing facilities, educational locations, museums, universities, and other related entities), and information (e.g. courses, books, exams, grades, economic surveys, assessments, reports, and much more).
Big data in education opens new doors also to researchers.
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Another example of an emerging big data system in education is OECD's Education GPS that hosts massive amount of data from education systems around the world.
This paper presents, EwayDataCollect, a tool for online data collection in education system.
Likewise, Levin (2013) and Sellar (2015) both suggest that the development of data infrastructure in education should select a few nonacademic skill measures in conjunction with the standard academic performance measures.
Much like in health, we need a data revolution in education.
Overall, the future progress of educational technology necessitates creating comprehensive standards of data in higher education.
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