Lesson Plan

• Describe the concepts of pixel, resolution, colour depth and palette.
• Explain the difference between direct (true‑colour) and indexed (palette‑based) encoding.
• Calculate the data size of a bitmap image using width, height and bits‑per‑pixel.
• Compare the advantages of various colour depths and common file formats.
• Apply encoding knowledge to choose an appropriate format for a given scenario.

• Projector and screen
• Computer with image‑editing software (e.g., GIMP)
• Sample bitmap images (1‑bpp, 8‑bpp, 24‑bpp)
• Worksheet with calculation exercises
• Printed handout summarising colour‑encoding methods
• Calculators (or calculator app)

Begin by displaying two versions of the same picture—one 2‑bpp indexed and one 24‑bpp true‑colour—and ask students what differences they notice. Connect this observation to their prior knowledge of binary representation and pixel data. Explain that by the end of the lesson they will be able to describe how bitmap images are encoded and compute their file sizes.

1. Do‑now (5'): Quick quiz on pixels, resolution and colour depth.
2. Mini‑lecture (10'): Key concepts and encoding methods (direct vs indexed) with slide examples.
3. Guided example (10'): Walk through the 640 × 480 × 8 bpp calculation from the notes.
4. Hands‑on activity (15'): In pairs, students calculate image sizes for several given dimensions and bpp, recording answers on the worksheet.
5. Software demonstration (10'): Show BMP, GIF and PNG files of the same image and compare file sizes and colour depth.
6. Check for understanding (5'): Exit ticket – write one advantage of indexed encoding over true‑colour encoding.

Summarise how colour depth and encoding choice affect file size, colour fidelity and processing speed. Collect the exit tickets to gauge understanding, and remind students of the success criteria. For homework, ask them to research a bitmap file format not covered in class (e.g., TIFF) and prepare a brief summary of its encoding characteristics.