Big data analytics in education – UGC NET Question

Big data analytics involves using advanced computational techniques to process high-volume, high-velocity and high-variety data. In education, this can mean analysing records from LMSs, administrative systems and online platforms to detect trends in performance or behaviour. Insights from such analyses can guide policy, resource allocation and personalised interventions. Thus the large-scale analysis described in the stem is big data analytics.

Option A:
Option A is correct because the term big data captures both the size and complexity of datasets that exceed the capacity of traditional tools, requiring specialised methods. Educational technology research increasingly references big data when discussing large-scale learning traces.

Option B:
Option B, manual record, suggests traditional paper-based files maintained by hand and does not imply advanced analytics.

Option C:
Option C, anecdotal, refers to informal, unstructured observations that lack systematic coverage and cannot describe large, complex datasets.

Option D:
Option D, randomised, hints at experimental design but not at the analysis of massive datasets across entire systems.