Lesson Plan

Lesson Plan
Grade: Date: 25/02/2026
Subject: Physics
Lesson Topic: derive, using C = Q / V, formulae for the combined capacitance of capacitors in series and in parallel
Learning Objective/s:
  • Describe the definition of capacitance and its relationship to charge and voltage.
  • Derive the series equivalent‑capacitance formula using C = Q/V.
  • Derive the parallel equivalent‑capacitance formula using C = Q/V.
  • Apply both formulae to solve A‑Level style circuit problems.
  • Check derived results for correct units and limiting behaviour.
Materials Needed:
  • Projector or interactive whiteboard
  • PowerPoint slides with derivations and diagrams
  • Worksheets containing practice problems
  • Physical capacitors, battery and connecting wires for a brief demo
  • Calculators or PhET Capacitor Lab simulation
Introduction:

Begin with a quick question about the meaning of C = Q/V to activate prior knowledge. Remind students that they have already explored single‑capacitor behaviour. Explain that by the end of the lesson they will be able to derive and use the combined‑capacitance formulae for series and parallel networks, which is the success criterion for today.

Lesson Structure:
  1. Do‑now (5'): Short written question on the definition of capacitance; teacher reviews answers.
  2. Mini‑lecture (10'): Review single‑capacitor concepts, introduce series connection, derive V_i = Q/C_i.
  3. Guided derivation (12'): Sum voltages, obtain 1/C_eq = Σ(1/C_i); students complete steps on worksheet.
  4. Parallel configuration (10'): Demonstrate equal voltage across capacitors, derive C_eq = ΣC_i with class participation.
  5. Application practice (12'): Pairs solve mixed‑network problems; teacher circulates with probing questions.
  6. Quick check (5'): Exit ticket – write both formulae and state one key condition for each.
Conclusion:

Summarise the two combined‑capacitance expressions and highlight when each applies. Collect the exit tickets to gauge understanding, and assign a short homework set of three mixed‑network problems for reinforcement.