canvas-outcome-tracker

name	canvas-outcome-tracker
description	Track student mastery of learning outcomes in Canvas. Shows outcome rollups by student, mastery distribution across the class, and which outcomes have the lowest proficiency rates. Built for accreditation reviews, program assessment, and advising. Trigger phrases include "outcome tracker", "learning outcomes", "mastery data", "accreditation report", "outcome mastery", or "who hasn't mastered".

Canvas Outcome Tracker

Surface learning outcome mastery data across a course — by outcome, by student, or by group — to support program assessment and accreditation reporting.

Prerequisites

• Canvas MCP server must be running and connected.
• You must have instructor or admin role in the target course.
• The course must have outcomes aligned to assignments (contact your Canvas admin if outcomes are not visible).

Steps

1. Identify the Target Course

Ask the user which course to analyse. Accept a course name, code, or Canvas ID.

If unclear, call list_courses to let them select.

2. Load the Outcome Structure

Call get_root_outcome_group to get the top-level outcome group for the course. Then call list_outcome_groups to retrieve all outcome groups in the course.

For each group, call list_outcome_group_outcomes to enumerate the individual outcomes. Build a flat list:

• Outcome ID
• Outcome title
• Mastery points threshold

Ask the user if they want to focus on a specific outcome group or review all outcomes.

3. Choose Report Type

Offer three modes:

Mode	Description
Class overview	Mastery distribution for all outcomes at once
Per-student rollup	Which outcomes each student has or hasn't mastered
Single outcome deep-dive	All students' results for one outcome

4A. Class Overview — Mastery Distribution

For each outcome, call get_outcome_mastery_distribution with the course ID and outcome ID. This returns the count of students at each mastery level (exceeds / meets / approaching / not yet).

Summarise as a ranked table, lowest mastery first:

Outcome Mastery Distribution — [Course Name]

LOWEST MASTERY (action needed)
• "Critical Analysis" — 38% not yet mastered (19/50 students)
• "APA Citation" — 24% not yet mastered (12/50 students)

MEETING EXPECTATIONS
• "Thesis Construction" — 82% mastered
• "Research Synthesis" — 79% mastered

4B. Per-Student Rollup

Call get_outcome_rollups with the course ID. This returns each student's rolled-up mastery status per outcome.

Format as a matrix or highlight students with 3+ unmastered outcomes as high-priority advising targets.

4C. Single Outcome Deep-Dive

Call get_outcome_results with the course ID and outcome ID to retrieve individual student result records — score, alignment source, and mastery status.

Call get_outcome_contributing_scores for the detailed score breakdown per student if the user wants to see which assignments contributed to mastery.

5. Present Actionable Recommendations

Based on the data, suggest:

• Outcomes to reteach or remediate
• Students to flag for advising (multiple unmastered outcomes)
• Alignment gaps (outcomes with zero results — may not be linked to assignments)

Ask if the instructor wants to export the data or drill further into any outcome.

Output Format

Outcome Tracker — [Course Name]

SUMMARY
Total outcomes tracked: 12
Students at or above mastery on all outcomes: 31/50 (62%)
Outcomes needing attention (< 70% mastery): 3

AT-RISK STUDENTS (3+ unmastered outcomes)
• Jordan Lee — 5 unmastered outcomes
• Sam Park — 4 unmastered outcomes

OUTCOME HEALTH SNAPSHOT
✗ Critical Analysis        38% mastered  ← reteach recommended
✗ APA Citation            64% mastered
✗ Thesis Construction     68% mastered
✓ Research Synthesis      79% mastered
✓ Source Evaluation       84% mastered

Notes

• This skill is fully read-only — it reports mastery data but does not modify outcomes or grades.
• Outcome results are only available for outcomes that have been aligned to graded assignments. Unaligned outcomes will show zero results.
• For accreditation exports, gather the output from get_outcome_rollups and get_outcome_mastery_distribution — these map directly to standard program assessment formats.
• get_outcome_contributing_scores provides the most granular data and may be slow on large courses; use it selectively.