Learning analytics collects traces of learner behaviour such as logins, page views, quiz attempts and assignment submissions. Dashboards and reports summarise these patterns and highlight students at risk or topics where many are struggling. Teachers can use this evidence to adjust pacing, provide remedial support or redesign assessments. Thus, its main purpose is to support data-informed improvements in teaching and learning.
Option A:
Randomly assigning grades would undermine fairness and academic standards. Learning analytics is introduced to make evaluation more evidence-based, not less.
Option B:
Deleting all activity records would remove the data needed for analysis and quality assurance. It contradicts the rationale for implementing analytics in the first place.
Option C:
Designing furniture and buildings is an architectural task. While enrolment numbers may influence space planning, this is not the central role of learning analytics in an LMS.
Option D:
This option correctly emphasises that analytics help teachers interpret patterns in student engagement and performance so they can make better pedagogical decisions.
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