Learner Activity
Introduction
A Learner Activity gives a high-level snapshot of how a particular learner is progressing through the LDM. It can reflect which curriculum, pathway, course, module, or assessment they’re engaged with, plus store segmentation info like “At Risk” or “On Track.” AI or data analysis can update these fields periodically.
Key highlights:
Summary of Engagement: See a quick overview of a learner’s status in each chunk of the hierarchy.
Segment: Identify learners who might need extra help vs. those who are excelling.
Custom Metadata: Store JSON or other detailed info to tailor AI or advanced analytics.
Properties
ContactId
The learner in question. Links directly to the individual’s record so you can consolidate their progress.
LearningCurriculumId / LearningPathwayId / LearningCourseId / LearningModuleId / LearningAssessmentId
Various optional references indicating which part of the LDM this activity record focuses on. For instance, you might track how a learner is doing specifically in “Module 2” or across an entire “Curriculum.”
Name
A short label for the activity record, e.g., “John Doe’s Progress in Module 2” or “Sarah’s Summative Assessment Performance.”
Description
Explains the state or goals of the learner’s activity, possibly their achievements or upcoming tasks. This can be general or quite detailed if you want an at-a-glance summary.
Segment
A text-based classification like “At Risk,” “On Track,” “Exceeding Expectations.” In AI-driven systems, this might be auto-assigned based on performance or engagement.
MetaData
A long text area intended for JSON or structured data that AI and other integrations can interpret. This might include hints about the learner’s study patterns, schedules, or recommended resources.
ECLearnerProgramRqmtProgressId
If integrated with Education Cloud, you can link the progress in a program requirement context.
CreatedDate
System-managed date/time of when this record was created.
ModifiedDate
Automatically updated date/time whenever fields change.
Example
You have a record named “Alice’s Advanced Marketing Progress” referencing the “Advanced Marketing Module.” The Segment is set to “On Track,” while MetaData stores AI notes: {"quizScores": [85, 90, 88], "recommendation": "Focus on reading #3"}. Instructors can quickly see she’s performing well and view the recommended material.
Use Case
A predictive analytics engine runs nightly, updating “Learner Activity” for each student. Those who missed multiple deadlines or scored poorly might get Segment = “At Risk,” prompting the system to send them additional resources or nudge notifications. Conversely, top performers might see “Exceeding Expectations,” unlocking advanced tasks or leadership roles in group projects.
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