Educational Analytics¶

NØMAD Edu bridges the gap between infrastructure monitoring and educational outcomes, helping instructors, mentors, and users track the development of computational proficiency.

Overview¶

Traditional HPC metrics tell you what happened. NØMAD Edu tells you how well users are learning to use HPC effectively.

Use cases:

Instructors: Track class-wide skill development, identify struggling students
Research mentors: Monitor graduate student onboarding progress
HPC staff: Evaluate workshop and training effectiveness
Users: Self-assess and improve HPC practices

Quick Start¶

# Explain a job with proficiency scores and recommendations
nomad edu explain 12345

# Track a user's improvement over time
nomad edu trajectory alice

# Generate a report for a course or research group
nomad edu report cs301

Commands¶

`nomad edu explain`¶

Analyze a single job with proficiency scores and actionable recommendations.

nomad edu explain <job_id> [options]

Options:

Option	Description
`--db PATH`	Database path (default: configured DB)
`--json`	Output as JSON
`--no-progress`	Skip historical comparison

Example output:

  NØMAD Job Analysis — 1104
  ────────────────────────────────────────────────────────
  User: alice    Partition: compute    Node: node03
  State: COMPLETED    Runtime: 33h 38m / 48h 00m requested

  Proficiency Scores
  ────────────────────────────────────────────────────────
    CPU Efficiency       ██░░░░░░░░   22.6%   Needs Work
    Memory Efficiency    █████████░   90.4%   Excellent
    Time Estimation      ██████████   97.4%   Excellent
    I/O Awareness        ███████░░░   68.8%   Good
    ────────────────────────────────────────────────────
    Overall Score        ███████░░░   69.8%   Good

  Recommendations
  ────────────────────────────────────────────────────────
    CPU Efficiency:
      Very low CPU utilization at 21% — requested 4
      cores but used ~1. This wastes resources and
      may delay other users' jobs.
      Try: #SBATCH --ntasks=1
          If your code is single-threaded, request 1 core.

  Your Progress (last 30 jobs)
  ────────────────────────────────────────────────────────
    CPU Efficiency        53.7% →  22.6%  ↓ declining
    Memory Efficiency     90.0% →  90.4%  → stable
    Time Estimation       88.4% →  97.4%  ↑ improving
    I/O Awareness         91.8% →  68.8%  ↓ declining

`nomad edu trajectory`¶

Track a user's proficiency development over time.

nomad edu trajectory <username> [options]

Options:

Option	Description
`--db PATH`	Database path
`--days N`	Lookback period (default: 90)
`--json`	Output as JSON

Example output:

  NØMAD Proficiency Trajectory — alice
  ────────────────────────────────────────────────────────
  Jobs analyzed: 173    Period: 2026-02-04 → 2026-02-15
  Stable proficiency

  Score Progression
  ────────────────────────────────────────────────────────
    2026-01-29    ████████░░   78.6%  (21 jobs)
    2026-02-05    █████████░   78.9%  (144 jobs)

  Dimension Changes
  ────────────────────────────────────────────────────────
    I/O Awareness         90.6%  → +4.6%
    Memory Efficiency     85.9%  → +0.2%
    GPU Utilization       85.0%  → +0.0%
    CPU Efficiency        51.9%  → -1.2%
    Time Estimation       81.3%  → -2.1%

`nomad edu report`¶

Generate aggregate reports for courses, research groups, or any Linux group.

nomad edu report <group_name> [options]

Options:

Option	Description
`--db PATH`	Database path
`--days N`	Lookback period (default: 90)
`--json`	Output as JSON

Example output:

  NØMAD Group Report — cs101
  ────────────────────────────────────────────────────────
  Members: 4     Jobs: 602
  Period: 2026-02-04 → 2026-02-16

  Key Insight
  ────────────────────────────────────────────────────────
    0/4 students improved overall proficiency

  Group Proficiency
  ────────────────────────────────────────────────────────
    Memory Efficiency    █████████░   85.2%  → -0.8%
    GPU Utilization      █████████░   85.0%  → +0.0%
    I/O Awareness        ████████░░   80.2%  → -1.5%
    Time Estimation      ████████░░   78.9%  → -1.1%
    CPU Efficiency       █████░░░░░   51.9%  → -2.4%

    Weakest area:   cpu   |   Strongest: memory

  Student Breakdown
  ────────────────────────────────────────────────────────
    Improving:   0
    Stable:      4
    Declining:   0

  Per-Student Summary
  ────────────────────────────────────────────────────────
    User        Jobs    Overall   Change    Trend
    charlie      136     73.2%    +0.7%       →
    alice        173     78.9%    +0.3%       →
    diana        147     76.8%    +0.1%       →
    bob          146     76.1%    -3.0%       →

Setting Up Groups¶

NØMAD uses Linux groups for course/lab membership. To track a class:

Option 1: Use existing Linux groups¶

If your users are already in groups (e.g., bio301, cs101):

# Collect group membership
nomad collect -C groups --once

# Generate report
nomad edu report bio301

Option 2: Create dedicated groups¶

# Create group for course
sudo groupadd cs301

# Add students
sudo usermod -aG cs301 student01
sudo usermod -aG cs301 student02
# ...

# Collect and report
nomad collect -C groups --once
nomad edu report cs301

Option 3: Manual group file¶

Create a CSV file and import:

username,group_name,gid,cluster
alice,cs301,3001,spydur
bob,cs301,3001,spydur

nomad edu import-groups groups.csv

Dashboard Integration¶

The dashboard includes an Education tab showing:

Class-wide proficiency distributions
Individual student progress
Common problem areas
Improvement trends over time

Access via: nomad dashboard → Education tab

Best Practices¶

For Instructors¶

Baseline early: Collect data from the first week to establish starting points
Check weekly: Review group reports to identify struggling students early
Focus on trends: Individual job scores vary; trajectories matter more
Share reports: Let students see class-wide (anonymized) progress

For Mentors¶

Onboarding checkpoint: Review trajectory after first 10 jobs
Specific feedback: Use explain output to guide discussions
Celebrate improvement: Recognize when dimensions improve

For Users¶

Review failed jobs: Use explain to understand what went wrong
Track your trajectory: Check weekly to see improvement
Act on recommendations: The suggestions are data-driven

Technical Details¶

For detailed information on how proficiency is computed:

Proficiency Scoring — Formulas, dimensions, and scoring rubrics
Database Schema — How scores are stored

Troubleshooting¶

"Job not found in database"¶

Job 12345 not found in database.

Hint: Specify a database with --db or run 'nomad init' to configure.
  Example: nomad edu explain 12345 --db ~/nomad_demo.db

Solutions:

Specify the database: nomad edu explain 12345 --db /path/to/db
Run nomad init to configure the default database
Ensure data collection is running: nomad collect

"Not enough data for user"¶

The user needs at least 3 completed jobs for trajectory analysis.

"No data found for group"¶

Ensure group membership data has been collected:

nomad collect -C groups --once

Educational Analytics¶

Overview¶

Quick Start¶

Commands¶

nomad edu explain¶

nomad edu trajectory¶

nomad edu report¶

Setting Up Groups¶

Option 1: Use existing Linux groups¶

Option 2: Create dedicated groups¶

Option 3: Manual group file¶

Dashboard Integration¶

Best Practices¶

For Instructors¶

For Mentors¶

For Users¶

Technical Details¶

Troubleshooting¶

"Job not found in database"¶

"Not enough data for user"¶

"No data found for group"¶

`nomad edu explain`¶

`nomad edu trajectory`¶

`nomad edu report`¶