UGC NET Questions (Paper – 1)

Learning analytics involves collecting and analysing data about learners and their contexts to understand and optimise learning. Metrics such as logins, resource views and assessment results are typical inputs for such analysis. They help educators identify patterns of engagement, at-risk students and effective materials. Hence the reports described in the stem are examples of learning analytics data.

Option A:
Option A is correct because LMS-generated activity and performance indicators are central sources for learning analytics dashboards and research. These data are explicitly used to improve teaching strategies and student support.

Option B:
Option B, random noise, suggests meaningless or unstructured data, which is not accurate here because the metrics are systematically recorded and interpretable.

Option C:
Option C, fiscal accounting, pertains to financial transactions and budgets rather than learner behaviours and outcomes.

Option D:
Option D, biometric surveillance, would involve physical or physiological measurements like fingerprints or facial recognition, which are not mentioned in the stem.