03 February

Rheostat Simulation

Seng Kwang Tan IP4 11 Current Electricity 0 Comments
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A rheostat controls the size of the electric current by changing the resistance in a circuit using a resistive track and a movable slider. Moving the slider changes the length of the resistive path, so a longer path gives a larger resistance and smaller current, while a shorter path gives a smaller resistance and larger current.

This morning, I was watching my students conduct an experiment with a rheostat and saw a few of them connecting the two lower plugs (A and B as shown in the simulation). I had to explain to them why the current would not change no matter how they move the slider. Then it occurred to me that this could be best explained using a simulation. So I created this simple simulation using a little vibe-coding to help my students visualise current flow through a rheostat, hopefully preventing them from connecting it the wrong way.

I used the following prompt on Trae.ai: “Create this html simulation of a rheostat. The canvas should show a realistic image of a rheostat with its three plugs. One above, next to the rod on which the slider is resting. Two on either side of the coil of wire. The user can connect two wires to any of the three plugs. The simulation should show the direction of current flow, from one terminal out to the other terminal. The resistance value will then be shown. Make the maximum resistance 20 ohm.”

It produced a working prototype within one prompt. I then made further prompts changes to refine the app. Trae.ai makes fast iterations much less painful as it only makes the changes to the necessary codes without having to generate the whole set of codes from scratch.

For Singapore teachers, this simulation is optimised for SLS and is directly embeddable to SLS as my github domain is whitelisted. Just paste the URL (https://physicstjc.github.io/sls/rheostat/) after clicking “Embed website”.

Rheostat simulation
Screenshot of the rheostat simulation

02 February

Gorilla Physics

Seng Kwang Tan 05 Projectile Motion 0 Comments
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The Gorilla Physics Lab (created using Gemini Canvas) serves as a dynamic bridge between abstract projectile motion equations and physical intuition, transforming a classic gaming mechanic into a high-fidelity educational tool. By providing real-time relative physics data, such as horizontal displacement ($\Delta x$) and vertical height difference ($\Delta y$), the app encourages students to move beyond “trial and error.” Students are challenged to calculate the precise initial velocity or angle required to hit a target.

Furthermore, the simulation excels at visualizing the fundamental principle of the independence of $x$ and $y$ motion. Through the use of real-time vector arrows, students can observe how the horizontal velocity remains constant while the vertical velocity reacts to gravitational acceleration—shrinking as it approaches the apogee and growing as it falls. By toggling between different planetary gravities, from the light pull of the Moon to the crushing force of Jupiter, students gain a visceral understanding of how acceleration constants influence time of flight and parabolic curvature. Ultimately, the lab turns the classroom into an interactive environment where mathematical predictions are immediately validated by the motion of the projectile, fostering a deeper conceptual grasp of two-dimensional kinematics.

25 January

Scale Drawing Practice for Vector Addition

Seng Kwang Tan IP3 01 Measurement, Simulations 0 Comments
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Bridging the Gap: A Digital Approach to Vector Scale Drawings

Vector addition is a fundamental concept in physics, yet students often struggle to visualize the connection between abstract numbers (magnitude, direction) and their geometric representation. I developed this Vector Scale Drawing App, a lightweight web-based tool designed to scaffold the learning process for vector addition, providing students with a “sandbox” to practice scale drawings with immediate feedback.

This Vector Scale Drawing App is not meant to replace pen and paper, but to complement it. A built-in guide walks novices through the process (Read -> Choose Scale -> Draw -> Measure).

“Pencil Mode”

The pencil mode allows students to make markings, trace angles, or draw reference lines without “committing” to a vector. Crucially, in Pencil Mode, the tools are “transparent” to clicks—you can draw right over the ruler, just like in real life.

This distinction helps students separate the *construction phase* from the *result phase*.

When students submit their answer (Magnitude and Direction), the app checks it against the calculated resultant. We allow for a small margin of error (5%), acknowledging that scale drawing is an estimation skill.

18 January

Base Unit Building Blocks

Seng Kwang Tan 01 Quantities and Measurement, IP3 01 Measurement 0 Comments

Base units are the fundamental building blocks from which all other units of measurement are constructed. In the International System of Units (SI), quantities such as length (metre), mass (kilogram), time (second), electric current (ampere), temperature (kelvin), amount of substance (mole), and luminous intensity (candela) are defined as base units because they cannot be broken down into simpler units. By combining these base units through multiplication, division, and powers, we can form derived units to describe more complex quantities—for example, speed (metres per second), force (newtons), and energy (joules).

This app teaches dimensional analysis by letting learners build derived physical quantities from the seven SI base units. Through an interactive fraction-style canvas, users place base-unit “bricks” into the numerator or denominator to form target dimensions (e.g., kg m⁻³ for density), reinforcing how exponents and unit positions encode physical meaning. Each quantity is accompanied by concise, inline hints that show the unit structure of the terms in its defining equation (for example, mass and volume in density, or force and area in pressure), helping students connect formulas to their base-unit foundations. By checking correctness and exploring more quantities (force, energy, power, electric charge, voltage, resistance, heat capacity, specific heat, latent heat, molar mass), learners develop an intuitive, transferable understanding of how physics equations translate into consistent SI units.

The app (https://physicstjc.github.io/sls/base-units/) can be directly embedded into SLS as the domain is now whitelisted.

06 December

Simulation for Series and Parallel Circuit

Seng Kwang Tan 16 Circuits, IP4 12 DC Circuits, Javascript 0 Comments
2.0 Ω
2.0 Ω
Drag the ammeter (A) or voltmeter (V) onto a bulb to attach. Ammeter measures current inline; voltmeter measures voltage across the bulb.
6V Battery Bulb 1 2Ω Bulb 2 2Ω A V

This interactive simulation helps students compare what happens in series and parallel circuits using two bulbs and a 6 V battery. Learners can switch between series and parallel configurations, adjust the resistance of each bulb, and see how this affects the current, voltage and brightness of the bulbs. By dragging the ammeter (A) into the circuit, they can measure the current through a chosen bulb, and by placing the voltmeter (V) across a bulb, they can measure the potential difference across it. The changing brightness of each bulb represents the power it dissipates, allowing students to visualise ideas such as: in a series circuit the current is the same through all components but the voltage is shared, while in a parallel circuit the voltage across each branch is the same but the currents can be different.

05 December

Simulation of electron drift speed versus temperature

Seng Kwang Tan 15 Currents, IP4 11 Current Electricity 0 Comments
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Metal Lattice Simulation

3.0 V
20 °C
Mean drift speed: 0.0 mm/s
At low temperature, ions vibrate less, so collisions are fewer and drift speed (and current) is higher for 3.0 V.
Your browser does not support the HTML5 canvas tag.

This simulation demonstrates the principle that the resistance of a metal conductor increases with temperature. As temperature rises, the metal ions in the lattice vibrate more vigorously. This increased vibration causes charge carriers (electrons) to collide more frequently with the ions, hindering their movement. As a result, resistance increases and the current flowing through the conductor decreases for the same applied voltage.

At the A-Level, this simulation extends the understanding of current by examining it from a microscopic perspective in terms of mean drift velocity. Instead of viewing current simply as the rate of flow of charge, students learn that electrons in a conductor move slowly on average, with a small net drift in the direction of the electric field. The current depends on how many charge carriers are available and how fast they drift. This is expressed using the equation:

$$I = nAv_dq$$

where II is the current, nn is the number density of charge carriers, AA is the cross-sectional area of the conductor, vdv_dis the mean drift velocity of the electrons, and qq is the charge of each carrier. As temperature increases, more frequent collisions reduce the drift velocity, helping to explain why current decreases even though the charge carriers are still present—linking microscopic behaviour with macroscopic electrical measurements.