Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, with the aim of understanding and improving learning. Sources include logins, time on task, quiz results, assignment submissions and forum activity from an LMS or other tools.
Why it matters
It helps instructors spot struggling learners early, identify confusing questions or modules, and see which resources are used. It also requires care: raw activity numbers, such as clicks, do not equal understanding, models can be biased, and learner data is personal data that needs consent, transparency and secure handling under rules such as GDPR. It overlaps with general data analytics but with a focus on education.
Example
An instructor's dashboard flags:
- Learners with no login for 10 days
- A quiz question that 85% of learners answer incorrectly
- A video that most viewers stop at the 2-minute mark
The instructor then contacts inactive learners, rewrites the question, and splits the video, instead of guessing where the problems are.
Common mistakes
- Treating time spent as a proxy for learning.
- Labeling learners automatically as "at risk" without human review.
- Collecting more data than needed with no clear question.
Related
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यह पेज सामान्य जानकारी है, जिसे हमारी संपादकीय टीम ने लिखा है और दस्तावेज़ीकरण बदलने पर अपडेट किया जाता है। सर्वर और प्रदाता अलग-अलग होते हैं, इसलिए बदलाव पहले सुरक्षित तरीके से जाँचें। देखें: संपादकीय नीति और अस्वीकरण.