To avoid oversimplifying student performance, LMS analytics should combine quantitative data with what?

• A. Final exam scores only.
• B. Attendance data alone.
• C. Engagement metrics and time-on-task, plus qualitative observations and multiple measures.
• D. A single metric such as quiz results.

Answer: (C)

Learning analytics gain accuracy when we mix numbers with richer signals about how students are engaging and what their work shows over time. The best choice combines engagement metrics and time-on-task with qualitative observations and multiple measures. That approach captures not just what students score, but how they interact with the material, how much effort they invest, and the context or quality of their understanding through teacher notes and other assessments. This fuller picture helps identify where a student might be struggling, recovering, or needing different supports.

Relying on a final exam score alone misses the learning process and context. Attendance data alone ignores actual performance and effort. A single metric like quiz results provides a narrow snapshot and can be misleading if used in isolation.