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student-success-scorecard skill

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This skill helps institutions monitor student engagement and progression with a KPI-driven scorecard, enabling proactive interventions and leadership reporting.

npx playbooks add skill microck/ordinary-claude-skills --skill student-success-scorecard

Review the files below or copy the command above to add this skill to your agents.

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SKILL.md

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---
name: student-success-scorecard
description: Metrics framework for monitoring engagement, progression, and completion.
---

# Student Success Scorecard Skill

## When to Use
- Setting KPIs for new cohorts or programs.
- Diagnosing retention risks and intervention impact.
- Reporting to leadership, accreditation bodies, or partners.

## Framework
1. **Metric Stack** – inquiry-to-enrollment, onboarding completion, engagement streaks, assignment submissions, completion rate, CSAT/NPS.
2. **Segmentation** – by cohort, modality, persona, geography, instructor, partner.
3. **Risk Signals** – inactivity thresholds, support ticket spikes, sentiment drops.
4. **Intervention Tracker** – log nudges, coaching sessions, community events, results.
5. **Insight Narrative** – highlights, risks, opportunities, recommended actions.

## Templates
- Scorecard dashboard layout (summary + drill-down tabs).
- Risk heatmap template for cohorts/segments.
- Intervention log sheet linking actions to KPI movement.

## Tips
- Automate data pulls from LMS/CRM to reduce manual effort.
- Pair leading indicators (logins, submissions) with lagging outcomes (completion, placement).
- Use with `launch-student-success-program` to define monitoring cadence.

---

Overview

This skill provides a metrics framework for monitoring student engagement, progression, and completion across programs and cohorts. It organizes leading and lagging indicators into a repeatable scorecard, surfaces risk signals, and links interventions to KPI movement. The result is a practical dashboard-ready model you can apply to reporting, diagnostics, and continuous improvement.

How this skill works

The skill defines a Metric Stack (from inquiry to completion) and standard segmentations to measure performance at cohort, modality, and persona levels. It identifies risk signals like inactivity and sentiment drops, logs interventions and outcomes, and generates an Insight Narrative with highlights, risks, and recommended actions. Templates for dashboards, heatmaps, and intervention logs speed implementation and integration with LMS/CRM data sources.

When to use it

Setting KPIs and monitoring cadence for new cohorts or programs
Diagnosing retention risks and prioritizing interventions
Reporting program health to leadership, partners, or accreditation bodies
Evaluating the impact of coaching, nudges, or curriculum changes
Scaling operations across modalities and geographic segments

Best practices

Automate data pulls from LMS, CRM, and support systems to avoid manual errors
Combine leading indicators (logins, submissions) with lagging outcomes (completion, placement)
Segment consistently by cohort, persona, instructor, and partner for comparable trends
Define clear inactivity thresholds and escalation rules to trigger interventions
Record each intervention and outcome to link actions to KPI movement over time

Example use cases

Build a cohort scorecard that highlights at-risk students and the effect of recent nudges
Create a risk heatmap to prioritize coaching resources across instructors and regions
Report monthly completion and engagement trends to accreditation reviewers
Measure whether a new onboarding flow improves early engagement and downstream completion
Track A/B tests of intervention types by mapping interventions to short- and long-term KPIs

FAQ

Can this framework work with minimal data?

Yes — start with core signals (logins, submissions, completion) and add richer sources over time; the templates scale as data improves.

How do I connect data sources?

Automate extracts from LMS and CRM where possible; use ETL scripts or connectors to populate the scorecard and intervention log.