Questions & Import

Question Types

TrueCert supports 8 question types, each suited for different assessment needs:

Scenario-Based Questions

Any question type can include a scenario — a real-world situation presented to the candidate before the question. This is the same format used by AWS, CKA, and HashiCorp certification exams.

Scenarios test practical decision-making and are especially effective for Level 2+ assessments. Add them via the scenario_text field in the question editor or JSON import.

Adding Questions Manually

1. Go to Admin → Questions → Add New
2. Select the target certification
3. Choose the question type
4. Enter the question text (and optional scenario text)
5. Set the topic, difficulty (1-5), and weight
6. Add answer options or configure the type-specific fields
7. Optionally add an image URL for diagrams or screenshots
8. Save

Bulk Import via JSON

For large question sets, use the JSON import tool at Admin → Questions → Import JSON.

Import Modes

• Merge — Updates existing questions (matched by id) and adds new ones. Existing questions not in the import are left unchanged.
• Replace — Deactivates all existing questions for the certification, then imports all questions as new. Use with caution.

JSON Format

The import file must be a JSON object with this structure:

{
  "cert_id": 7,
  "cert_slug": "ansible-l1",
  "version": "March 2026",
  "import_mode": "replace",
  "questions": [
    {
      "id": null,
      "topic": "Inventory",
      "question_text": "Which file format is used for Ansible inventory?",
      "scenario_text": null,
      "type": "mcq",
      "difficulty": 1,
      "weight": 1.0,
      "is_active": true,
      "image_url": null,
      "options": [
        { "text": "INI or YAML", "is_correct": true },
        { "text": "JSON only", "is_correct": false },
        { "text": "XML", "is_correct": false },
        { "text": "CSV", "is_correct": false }
      ]
    }
  ]
}

Field Reference

Type-Specific Examples

Code Output — requires question_config.code and question_config.accepted:

{
  "type": "code_output",
  "question_config": {
    "code": "print(len([1, 2, 3]))",
    "language": "python",
    "accepted": ["3"],
    "case_sensitive": false
  }
}

Ordering — uses opt:N references for correct order:

{
  "type": "ordering",
  "options": [
    { "text": "Plan" },
    { "text": "Build" },
    { "text": "Test" },
    { "text": "Deploy" }
  ],
  "question_config": {
    "correct_order": ["opt:0", "opt:1", "opt:2", "opt:3"]
  }
}

Matching — pairs left column (group 0) with right column (group 1):

{
  "type": "matching",
  "options": [
    { "text": "HTTP",  "display_group": 0 },
    { "text": "SSH",   "display_group": 0 },
    { "text": "Port 80",  "display_group": 1 },
    { "text": "Port 22",  "display_group": 1 }
  ],
  "question_config": {
    "pairs": [["opt:0", "opt:2"], ["opt:1", "opt:3"]]
  }
}

Scenario question — add scenario_text to any type:

{
  "type": "mcq",
  "scenario_text": "Your production Kubernetes cluster is running low on resources...",
  "question_text": "What should you do first?",
  "options": [...]
}

Best Practices

• Pool size: Create 40-60 questions for a 25-question exam to ensure variety across attempts.
• Mix types: Use a variety of question types — MCQ for breadth, code output for depth, scenarios for practical application.
• Weight appropriately: Use weight 1.0 for basic MCQ/true-false, 1.5 for select-multiple and code questions, 2.0 for matching and ordering.
• Topics: Always set the topic field — it drives the strengths analysis on PDF certificates.
• Difficulty spread: Aim for ~40% easy (1-2), ~40% medium (3), ~20% hard (4-5) questions.
• Scenarios: Add scenario_text to 15-20% of questions, especially for Level 2+ exams.
• No file size limit on question count per import (only a 2 MB file size limit). Import as many questions as you need.