Lesson Plan

• Describe the definition and purpose of test data in the systems life cycle.
• Identify the characteristics of good test data (relevance, representativeness, traceability, repeatability, clarity).
• Differentiate between normal, abnormal, and extreme test data and provide appropriate examples.
• Apply the process of selecting and documenting test data for a given requirement.
• Evaluate test results and report defects based on the type of test data used.

• Projector or interactive whiteboard
• Slide presentation on test data concepts
• Sample test‑case worksheets
• Laptops with a simple application (e.g., mock payroll form)
• Printed handouts of test‑data tables
• Markers and flip chart for group discussion

Start with a quick poll: “What happens when you enter an incorrect value into an online form?” Connect this to students’ prior experience with input validation. Explain that today they will explore how test data—normal, abnormal, and extreme—are used to verify software behaviour. Success criteria: students will be able to classify test data types, create examples, and explain why each type is needed.

1. Do‑now (5 minutes): Short quiz on common input‑validation errors.
2. Teacher input (10 minutes): Define test data, outline its characteristics, and introduce the three categories using slides.
3. Guided activity (15 minutes): In pairs, students receive a sample requirement and generate normal, abnormal, and extreme data, recording them on the worksheet.
4. Whole‑class discussion (10 minutes): Groups share their examples; teacher completes a comparison table on the board, highlighting key differences.
5. Practical demo (15 minutes): Teacher runs the mock application, inputs each data type, and observes system responses, linking back to characteristics.
6. Consolidation (5 minutes): Exit ticket – each student writes one key difference between abnormal and extreme data.

Recap the purpose of test data and the three categories, emphasizing how they ensure functional correctness, robust error handling, and boundary validation. Collect exit tickets to gauge understanding, and assign homework: create a complete set of normal, abnormal, and extreme test data for a new scenario (e.g., an online registration form).