{"id":14771,"date":"2024-10-30T15:55:35","date_gmt":"2024-10-30T13:55:35","guid":{"rendered":"https:\/\/oeb.global\/oeb-insights\/?p=14771"},"modified":"2024-10-30T17:56:21","modified_gmt":"2024-10-30T15:56:21","slug":"striking-the-right-balance-big-data-and-educational-data-mining-under-gdpr-and-the-ai-act","status":"publish","type":"post","link":"https:\/\/oeb.global\/oeb-insights\/striking-the-right-balance-big-data-and-educational-data-mining-under-gdpr-and-the-ai-act\/","title":{"rendered":"Striking the Right Balance: Big Data and Educational Data Mining under GDPR and the AI Act"},"content":{"rendered":"
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For over a decade in higher education, I\u2019ve seen first-hand how digitalisation is transforming data governance. From digital assessments and automated grading to sophisticated plagiarism detection, the world of education is increasingly driven by data. Big Data is reshaping how we teach, learn, and manage educational outcomes \u2014 especially in higher education institutions (HEIs)<\/a>. As more institutions integrate Learning Management Systems (LMS) and other digital platforms, an immense volume of data is generated, waiting to be mined for insights that could revolutionise student success and institutional efficiency. Yet, this shift to digital brings with it essential questions: How is this data utilised? Who controls it? And, crucially, how do we explain AI system outputs amid ever-evolving regulations?<\/strong>


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Defining Big Data in Higher Education<\/h2>\n\n\n\n

Today, HEIs handle vast amounts of data, commonly known as \u201cBig Data,\u201d encompassing everything from student demographics and academic records to behavioural data captured through digital learning platforms. What makes Big Data truly impactful are its defining characteristics: volume, velocity, variety, veracity, and value<\/a>.

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