Middle Stage — Robotics & Coding

Objective: Students can explain a robot as a system, classify inputs and outputs, and describe a simple engineering cycle.

Key concepts: Robotics, automation, input–process–output, sensors, controllers, actuators, engineering cycle.

Materials: Everyday examples; paper; marker; optional Arduino board and sensor kit for demonstration.

Hands-on plan

1. Start with a 3-minute 'spot the robot' challenge: students name three automated machines and identify what they sense and what they do.
2. Draw INPUT → PROCESS → OUTPUT on screen and let students map a smart light, automatic door and robot car.
3. Show Arduino, an ultrasonic sensor, servo and motor; students predict the role of each component before the explanation.
4. Students sketch a Smart Classroom system with at least two inputs and two outputs.
5. Students present the sketch in 30 seconds; mentor asks 'What happens if the sensor gives the wrong reading?' to introduce testing and iteration.

Student challenge: Add one safety feature and one manual override to the Smart Classroom design.

Evidence of learning: Exit ticket: name one sensor, one controller and one actuator; explain one real-world automation.

After class: Bring one real-life problem that could be solved with a sensor and a small controller.

Objective: Students can safely connect an LED, upload a sketch and modify timing without copying blindly.

Key concepts: Arduino UNO, digital pins, 5V/GND, USB, sketch structure, setup(), loop(), digitalWrite().

Materials: Arduino UNO, USB cable, LED, resistor, breadboard, jumper wires.

Hands-on plan

1. Students identify GND, 5V, digital pins and USB on their own board using a labelled reference.
2. Build LED + resistor on the breadboard; check polarity and connection before power.
3. Upload a basic Blink sketch and observe the repeating loop.
4. Students change ON/OFF delays and predict the visual result before uploading.
5. Create three patterns: slow blink, fast blink and SOS-style blink; compare code changes.
6. Students deliberately create one wiring/code mistake, observe the symptom, then correct it using a simple debugging checklist.

Student challenge: Create a 10-second light pattern that communicates a chosen word or signal.

Evidence of learning: Student explains why resistor and GND are used and independently uploads modified code.

After class: Write three different blink patterns in pseudocode.

Objective: Students can read a button and use its state to control an output.

Key concepts: Digital HIGH/LOW, input/output, button logic, pull-up/pull-down idea, if/else.

Materials: Arduino UNO, push button, LED, resistor, breadboard, jumpers.

Hands-on plan

1. Wire the button and LED; first test the button with Serial Monitor or an LED.
2. Explain HIGH/LOW using a simple door-open/door-closed analogy.
3. Write an if/else program: button pressed → LED ON; released → LED OFF.
4. Students test what happens when the input is floating and discuss why stable input is important.
5. Build a two-button version: button A controls LED 1 and button B controls LED 2.
6. Finish with a mini game: one button is 'start', another is 'stop'.

Student challenge: Make one button toggle an LED ON/OFF rather than requiring the button to remain pressed.

Evidence of learning: Student can identify input and output pins and explain the condition used.

After class: Draw the circuit and write the logic in plain English.

Objective: Students can read a changing analog value and use it to control an output.

Key concepts: Analog values, ADC, analogRead(), variables, mapping sensor values to outputs.

Materials: Arduino UNO, potentiometer, LED, resistor, breadboard, jumpers.

Hands-on plan

1. Connect the potentiometer and open Serial Monitor to observe changing readings.
2. Students turn the knob slowly and record low, middle and high values.
3. Create a variable for the sensor reading and print it clearly.
4. Use the reading to control LED brightness with PWM.
5. Create three zones: LOW, MEDIUM and HIGH, each with a different LED behavior.
6. Students change the threshold values and observe how calibration changes the system.

Student challenge: Use the potentiometer to control servo angle instead of LED brightness.

Evidence of learning: Student explains the difference between a digital button reading and an analog sensor reading.

After class: Record five potentiometer values at different positions.

Objective: Students can create a program that makes a decision from a sensor value.

Key concepts: Variables, comparison operators, if/else, thresholds, logical decisions.

Materials: Arduino UNO, potentiometer/LDR, LED, buzzer.

Hands-on plan

1. Create variables for sensorValue and threshold; students predict the result before running.
2. Build a simple warning system: if value exceeds threshold, buzzer ON.
3. Add a second condition for a safe zone.
4. Students change threshold and test at least three input conditions.
5. Introduce && and || through a two-sensor or two-condition example.
6. Students create a 'smart room' logic with light + temperature/simulated input.

Student challenge: Create three levels: SAFE, WARNING and ALERT using LEDs/buzzer.

Evidence of learning: Student explains why a threshold is needed and can modify it without mentor intervention.

After class: Write an if/else decision tree for an automatic fan.

Objective: Students can replace repeated code with loops and functions.

Key concepts: for, while, reusable functions, modular code.

Materials: Arduino UNO, 3 LEDs, resistors, breadboard.

Hands-on plan

1. Build three LEDs and first write a deliberately repetitive sequence.
2. Convert the sequence into a for loop and compare code length.
3. Create functions ledOn(), ledOff() or trafficLight().
4. Build a traffic-light sequence with clear timing.
5. Students modify the function to create a pedestrian signal.
6. Peer challenge: one student describes a sequence; another codes it without seeing the original.

Student challenge: Create a 'robot status' light system: booting, ready, warning and error.

Evidence of learning: Student identifies when a loop and a function are useful.

After class: Create pseudocode for a 4-step light sequence.

Objective: Students can read light level and build an automatic light.

Key concepts: LDR module, light level, threshold calibration, automatic control.

Materials: Arduino UNO, LDR module, LED, resistor, breadboard.

Hands-on plan

1. Observe the LDR value in bright and dark conditions and record a small range.
2. Choose a threshold from actual readings rather than a copied number.
3. Program LED ON in darkness and OFF in bright conditions.
4. Test with hand cover, room light and phone flashlight.
5. Add a short delay/filter so rapid changes do not cause visible flicker.
6. Students create a 'night mode' status message in Serial Monitor.

Student challenge: Add two LEDs: one for 'day' and one for 'night'.

Evidence of learning: Student demonstrates calibration and explains why the threshold may vary by room.

After class: Take five light readings in different locations.

Objective: Students can use a sound event as an input and create a controlled response.

Key concepts: Sound sensor trigger, buzzer, event logic, false triggering.

Materials: Arduino UNO, sound sensor, LED, buzzer, resistor.

Hands-on plan

1. Observe the sensor output during silence, speech and a clap.
2. Set/identify a practical threshold and test it repeatedly.
3. Program a single event to trigger an LED/buzzer response.
4. Add a timing window so continuous noise does not keep retriggering.
5. Students test three environments and note false triggers.
6. Improve the program by adding a short lockout period after a trigger.

Student challenge: Make one clap turn the light ON and the next clap turn it OFF.

Evidence of learning: Student explains one cause of false triggering and one software solution.

After class: List three situations where a sound sensor could be useful.

Objective: Students can measure distance and use it to trigger an output.

Key concepts: HC-SR04, trigger/echo timing, distance calculation, threshold actions.

Materials: Arduino UNO, HC-SR04, breadboard, jumper wires, optional LED/buzzer.

Hands-on plan

1. Identify VCC, GND, Trig and Echo and connect them correctly.
2. Run a distance-reading sketch and compare readings with a ruler.
3. Measure five objects at known distances and record actual vs displayed.
4. Create near/mid/far zones using thresholds.
5. Add LED/buzzer feedback for the near zone.
6. Discuss sources of error: angle, soft surfaces, very close targets.

Student challenge: Create a distance alarm whose beep rate increases as an object gets closer.

Evidence of learning: Student can explain why the sensor needs a trigger and an echo.

After class: Measure three objects and record expected and measured distance.

Objective: Students can control a servo and connect it to a useful mechanism.

Key concepts: SG90 servo, angle control, attach/write, mechanical range.

Materials: Arduino UNO, SG90 servo, potentiometer or ultrasonic sensor.

Hands-on plan

1. Identify servo power, ground and signal; discuss why mechanical loading matters.
2. Move servo through safe test angles such as 0°, 45°, 90° and 135°.
3. Control angle using a potentiometer.
4. Replace the potentiometer with a distance condition.
5. Create an automatic barrier/door sequence.
6. Test repeated movement and adjust timing to avoid unnecessary motion.

Student challenge: Create three positions: closed, opening and fully open.

Evidence of learning: Student explains why a servo is different from a DC motor.

After class: Sketch a mechanism that could use a servo.

Objective: Students combine distance sensing and servo control into a complete automation cycle.

Key concepts: Sensor + actuator integration, state logic, timing.

Materials: Arduino UNO, HC-SR04, SG90 servo, small prototype lid/cardboard.

Hands-on plan

1. Build and test ultrasonic measurement separately.
2. Build and test servo movement separately.
3. Combine: hand/object within threshold → lid opens.
4. Add an open-hold timer, then close.
5. Test different hand distances and adjust threshold.
6. Add a simple status LED or Serial message for OPEN/CLOSED.

Student challenge: Prevent the lid from closing while an object remains in front.

Evidence of learning: Student can explain the two modules separately and as one system.

After class: Draw the state flow: WAIT → DETECT → OPEN → HOLD → CLOSE.

Objective: Build a working automatic door prototype.

Key concepts: Presence detection, servo positions, sequence control.

Materials: Arduino UNO, IR obstacle sensor or ultrasonic, SG90 servo, cardboard door model.

Hands-on plan

1. Test sensor output for detected/not detected.
2. Choose closed and open servo angles.
3. Program sensor-triggered opening.
4. Add delay and closing logic.
5. Test repeated entries and edge cases.
6. Improve the mechanism so the door does not move beyond its safe range.

Student challenge: Add a buzzer that gives a short confirmation when the door opens.

Evidence of learning: Student demonstrates at least five successful open/close cycles.

After class: Design an automatic gate for a school entrance.

Objective: Read and interpret temperature/humidity values.

Key concepts: Temperature, humidity, sensor library, data reading.

Materials: Arduino UNO, DHT11, jumper wires, Serial Monitor.

Hands-on plan

1. Identify sensor pins and library setup.
2. Read temperature and humidity separately.
3. Print values with clear labels and units.
4. Take readings at room conditions, near a fan, and after gently warming the sensor area without touching it.
5. Discuss why measurements change and why sensors need time to stabilize.
6. Create a simple HIGH TEMP warning threshold.

Student challenge: Create three comfort states: COOL, COMFORTABLE, HOT.

Evidence of learning: Student can explain temperature vs humidity and read both values.

After class: Record five readings at different times.

Objective: Students can display meaningful information rather than raw Serial output.

Key concepts: LCD rows/columns, text, cursor, user interface.

Materials: 16×2 LCD, Arduino UNO, jumper wires, optional sensor.

Hands-on plan

1. Identify LCD pins and understand the purpose of RS/EN/data/control lines.
2. Display a welcome message.
3. Create a two-line status screen.
4. Replace fixed text with sensor values.
5. Add a simple alert message when a threshold is crossed.
6. Students redesign the screen for readability.

Student challenge: Create a rotating screen that shows two different sensor messages.

Evidence of learning: Student explains why a display is useful in a standalone project.

After class: Design a two-line screen for a smart plant.

Objective: Use an I2C display to show live sensor data.

Key concepts: I2C, SDA/SCL, compact wiring, display formatting.

Materials: Arduino UNO, I2C LCD, DHT11 or HC-SR04.

Hands-on plan

1. Identify SDA/SCL pins and explain why I2C uses fewer wires.
2. Use a known I2C address/setup and display text.
3. Connect DHT11 or ultrasonic sensor.
4. Format readings into a clean two-line dashboard.
5. Add a rotating page or status indicator.
6. Test display refresh without excessive flicker.

Student challenge: Show sensor value on line 1 and system status on line 2.

Evidence of learning: Student can explain SDA and SCL at a basic level.

After class: Draw the dashboard layout before coding.

Objective: Control a low-voltage pump safely through a relay.

Key concepts: Relay switching, NO/COM/NC, pump control, safety.

Materials: Arduino UNO, relay module, mini water pump, appropriate low-voltage supply, tubing, water container.

Hands-on plan

1. Explain relay contacts and why the controller should not directly drive a pump.
2. Test relay output without connecting the pump first.
3. Connect the low-voltage pump circuit using safe power practices.
4. Program manual ON/OFF control.
5. Add a timed pump cycle.
6. Test for leaks, polarity and stable switching.

Student challenge: Create a 5-second watering cycle with a manual start button.

Evidence of learning: Student identifies NO, COM and NC and explains safe power separation.

After class: Draw the relay and pump block diagram.

Objective: Build a moisture-based watering system.

Key concepts: Soil moisture calibration, closed-loop automation, pump control.

Materials: Soil moisture sensor, Arduino UNO, relay, pump, optional I2C LCD.

Hands-on plan

1. Measure dry soil and moist soil values.
2. Choose a threshold from the student's own readings.
3. Program dry → pump ON and wet → pump OFF.
4. Add a maximum pump runtime as a safety limit.
5. Test with dry and moist samples.
6. Add display/status messages if available.

Student challenge: Add a manual watering button that works only when the pump is safe to run.

Evidence of learning: Student explains calibration and why one fixed value may not work everywhere.

After class: Write three improvements for a real garden version.

Objective: Use an IR sensor as a proximity detector.

Key concepts: IR detection, digital output, reflective surfaces, false triggers.

Materials: Arduino UNO, IR obstacle sensor, LED, buzzer.

Hands-on plan

1. Test sensor output at different distances and surfaces.
2. Identify its adjustable sensitivity if the module provides it.
3. Program LED ON when an obstacle is detected.
4. Add buzzer feedback.
5. Test black, white, shiny and angled surfaces.
6. Discuss why IR is not the same as ultrasonic distance measurement.

Student challenge: Create two states: SAFE and OBSTACLE DETECTED.

Evidence of learning: Student explains one limitation of the IR sensor.

After class: List three applications of IR obstacle detection.

Objective: Display digits and build a simple counter.

Key concepts: Segments, digit patterns, common-anode/cathode concept, counting.

Materials: 7-segment display, Arduino UNO, resistors, breadboard.

Hands-on plan

1. Identify segment pins and discuss current-limiting resistors.
2. Display 0–9 one digit at a time.
3. Create a counting loop.
4. Add a push button to increment the counter.
5. Add a reset action.
6. Discuss how a multi-digit display would differ.

Student challenge: Create a countdown from 9 to 0 and then display DONE.

Evidence of learning: Student can identify why each LED segment needs current limiting.

After class: Create a segment map for digits 0–9.

Objective: Read RFID cards and create a basic access-control system.

Key concepts: RFID UID, reader/tag, SPI, authorization logic.

Materials: RC522 RFID module, tags/cards, Arduino UNO, servo or LED, buzzer.

Hands-on plan

1. Introduce RFID as contactless identification and explain UID.
2. Wire RC522 carefully and run a UID-reading test.
3. Record authorized UID(s) in the program.
4. Create authorized/denied behavior.
5. Add servo/LED/buzzer output.
6. Test multiple cards and document results.

Student challenge: Add a short access log message on Serial Monitor.

Evidence of learning: Student explains authentication vs simple sensor detection.

After class: Design a school-lab RFID access system.

Objective: Control motor direction and speed through a driver.

Key concepts: DC motor, H-bridge, direction, PWM speed, motor driver.

Materials: Arduino UNO, L298N, two DC gear motors, suitable motor supply, chassis optional.

Hands-on plan

1. Explain why a motor driver is used instead of connecting motors directly to Arduino.
2. Identify L298N input, enable and motor terminals.
3. Test one motor forward/reverse.
4. Test two motors together.
5. Add PWM speed control.
6. Create reusable movement functions.

Student challenge: Create three speed levels: slow, medium and fast.

Evidence of learning: Student explains IN pins vs EN pins and why motor power is separate.

After class: Draw the motor-driver block diagram.

Objective: Assemble a stable two-wheel robot and verify basic movement.

Key concepts: Mechanical alignment, wheel direction, caster, balance.

Materials: Robot chassis, two gear motors, wheels, caster, L298N, Arduino, battery holder.

Hands-on plan

1. Identify left/right motor and wheel orientation.
2. Mount motors and wheels; check that both wheels rotate freely.
3. Install caster and balance the chassis.
4. Connect driver and test forward.
5. Test reverse, left and right.
6. Fix mechanical rubbing, loose wires and uneven alignment.

Student challenge: Create a 30-second movement routine with four directions.

Evidence of learning: Robot completes forward/back/left/right without wire interference.

After class: Sketch the robot from top view and label all major parts.

Objective: Control robot movement wirelessly using simple commands.

Key concepts: HC-05, serial commands, wireless control, movement functions.

Materials: Arduino UNO, HC-05, L298N, two motors, robot chassis, phone/controller.

Hands-on plan

1. Test HC-05 communication before connecting motors.
2. Choose and document F/B/L/R/S commands.
3. Connect movement functions to received characters.
4. Test one command at a time.
5. Add a stop command that always has priority.
6. Run a short obstacle-free driving challenge.

Student challenge: Add two speed commands or a headlight command.

Evidence of learning: Student can explain the command flow: phone → Bluetooth → Arduino → driver → motors.

After class: Design five additional robot commands.

Objective: Improve reliability and safety of the robot program.

Key concepts: State machine idea, command validation, emergency stop, modular code.

Materials: Existing Bluetooth robot.

Hands-on plan

1. Review the existing movement functions and identify repeated code.
2. Create a central stop() function.
3. Add command validation so unknown characters do not cause movement.
4. Add an automatic stop after a period without commands if appropriate.
5. Test emergency stop repeatedly.
6. Students refactor code into clean functions and label wiring.

Student challenge: Create a simple 'safe mode' where motors are disabled until a start command is received.

Evidence of learning: Student demonstrates safe stop behavior under at least three test cases.

After class: Write a short debugging checklist for the robot.

Objective: Build a robot that reacts to an obstacle without manual commands.

Key concepts: Autonomy, sensor threshold, stop-turn-move decision.

Materials: Robot chassis, Arduino, ultrasonic sensor, L298N, two motors.

Hands-on plan

1. Mount ultrasonic sensor facing forward.
2. Read distance while robot is stationary.
3. Create a stop threshold.
4. Program: if clear → forward; if blocked → stop and turn.
5. Test on a simple straight obstacle course.
6. Adjust speed and threshold for stable behavior.

Student challenge: Add a reverse step before turning.

Evidence of learning: Robot completes a short obstacle course without manual control.

After class: Draw the decision flowchart.

Objective: Make the robot inspect multiple directions before choosing a turn.

Key concepts: Scanning, left/right comparison, decision-making.

Materials: Robot, ultrasonic sensor, SG90 servo, L298N.

Hands-on plan

1. Mount ultrasonic sensor on servo.
2. Test center, left and right angles while stationary.
3. Record distances and compare.
4. Program a scan sequence.
5. Choose the clearer direction.
6. Integrate with movement and test on a wider obstacle course.

Student challenge: Add a reverse-and-scan routine when both sides are blocked.

Evidence of learning: Student explains how the robot chooses a direction.

After class: Draw the scan decision tree.

Objective: Understand line sensing before attempting autonomous movement.

Key concepts: IR reflectance, black/white response, calibration, sensor placement.

Materials: IR line sensor array or modules, Arduino, black line track, white surface.

Hands-on plan

1. Test one sensor on black and white surfaces.
2. Record HIGH/LOW or analog behavior depending on the module.
3. Test multiple sensors across the line.
4. Map each sensor position to left/center/right.
5. Adjust sensor height and alignment.
6. Create a Serial Monitor sensor-map test.

Student challenge: Make LEDs indicate left/center/right line position.

Evidence of learning: Student can explain why calibration and sensor height matter.

After class: Draw sensor positions for a 3- or 5-sensor robot.

Objective: Build a basic line-following robot using simple logic.

Key concepts: Feedback, left/right correction, sensor combinations.

Materials: Robot chassis, IR sensors, Arduino, L298N, line track.

Hands-on plan

1. Create a sensor truth table for line positions.
2. Write movement rules for left, center and right conditions.
3. Run at low speed first.
4. Test straight sections.
5. Test one curve.
6. Adjust motor speeds and sensor placement.

Student challenge: Improve performance without increasing speed.

Evidence of learning: Robot follows a simple track for one complete run.

After class: Write the sensor truth table used by your robot.

Objective: Improve tracking on curves and junctions.

Key concepts: Multiple sensor states, error, correction strength, tuning.

Materials: Multi-channel IR sensor array, robot, motor driver.

Hands-on plan

1. Read all sensor states and display them for testing.
2. Assign a position/error value to each pattern.
3. Use different correction strengths for small vs large errors.
4. Test on gentle curves.
5. Test on sharper curves.
6. Reduce unnecessary oscillation by tuning speed/correction.

Student challenge: Create a repeatable calibration procedure before every run.

Evidence of learning: Student explains how sensor information becomes a steering decision.

After class: Document the best sensor and speed settings.

Objective: Apply the first 29 classes in a practical challenge.

Key concepts: Testing, debugging, timed challenge, reflection.

Materials: Line track and/or obstacle course; students' robots.

Hands-on plan

1. Students choose obstacle avoidance, line following or Bluetooth control.
2. Plan a 5-minute test strategy.
3. Run a baseline attempt.
4. Record one failure and identify its cause.
5. Make one controlled improvement.
6. Run a second attempt and compare results.
7. Finish with a short oral explanation.

Student challenge: Improve reliability rather than simply increasing speed.

Evidence of learning: Practical score: wiring 20%, code 25%, control 25%, debugging 20%, explanation 10%.

After class: Write three improvements for the next robot build.

Objective: Transition from text-code thinking to visual program structure.

Key concepts: Block coding, sprites, events, variables, broadcasts.

Materials: Computer, PictoBlox, optional Arduino.

Hands-on plan

1. Create a sprite and trigger an event.
2. Build a short interactive story using two sprites.
3. Add a variable such as score or counter.
4. Use broadcast messages to move between scenes.
5. Students debug one intentionally broken sequence.
6. Connect the project to a simple real-world problem.

Student challenge: Build a mini interactive quiz with at least three questions.

Evidence of learning: Student uses events, variables and at least one condition.

After class: Plan a five-scene interactive project.

Objective: Control physical hardware using visual programming.

Key concepts: Block-based hardware control, outputs, events.

Materials: Computer, PictoBlox, Arduino, LED, servo.

Hands-on plan

1. Connect Arduino and verify the hardware connection.
2. Turn an LED on/off from PictoBlox.
3. Use an event or button to control the LED.
4. Control a servo position.
5. Create a two-output interactive system.
6. Students add their own trigger and response.

Student challenge: Build a 'smart traffic signal' using visual code and LEDs.

Evidence of learning: Student can explain the difference between a software event and a physical output.

After class: Design one PictoBlox-controlled device.

Objective: Understand basic AI perception and connect detection to an action.

Key concepts: Computer vision, image input, face detection, AI as an input.

Materials: Computer with camera, PictoBlox/appropriate AI extension.

Hands-on plan

1. Explain that the camera provides image data and the AI model detects patterns.
2. Run a simple face-detection demonstration.
3. Test with one and multiple faces.
4. Create a condition: face detected → on-screen response.
5. Extend to a physical LED/servo output if the setup supports it.
6. Discuss privacy: use classroom test data responsibly and do not store personal images unless appropriate.

Student challenge: Create a 'welcome' response when a face is detected.

Evidence of learning: Student explains detection vs identification in simple terms.

After class: List three useful and three inappropriate uses of face detection.

Objective: Use a recognized gesture as an input for a digital or physical action.

Key concepts: Gesture recognition, visual input, conditions, action mapping.

Materials: Computer with camera, PictoBlox/appropriate AI extension, optional Arduino output.

Hands-on plan

1. Demonstrate supported hand/gesture recognition.
2. Test two gestures and observe recognition reliability.
3. Map gesture A → action A and gesture B → action B.
4. Add a neutral state so random movement does not trigger actions.
5. Connect an LED/servo if available.
6. Test at different distances and lighting conditions.

Student challenge: Create a two-gesture 'virtual remote control'.

Evidence of learning: Student explains one factor that affects recognition accuracy.

After class: Design a gesture-controlled smart-home interface.

Objective: Design a small AI-enabled physical project.

Key concepts: Problem statement, AI input, hardware output, system block diagram.

Materials: Computer, PictoBlox, Arduino/ESP32 optional, available sensor/actuator.

Hands-on plan

1. Choose a real classroom/home problem.
2. Write a one-sentence problem statement.
3. Select an AI input such as face/gesture detection.
4. Select one physical output.
5. Draw Input → AI → Decision → Output.
6. Build a minimum working prototype.
7. Test and record one limitation.

Student challenge: Improve the prototype based on one test result.

Evidence of learning: Student submits problem statement, block diagram and working demo.

After class: Prepare a 60-second project explanation.

Objective: Understand why ESP32 is useful for connected projects.

Key concepts: ESP32-S3, GPIO, Wi-Fi, Arduino vs ESP32, IoT.

Materials: ESP32-S3, USB cable, LED, sensor.

Hands-on plan

1. Compare Arduino UNO and ESP32-S3 at a high level.
2. Identify GPIO, power and USB connection.
3. Upload a basic LED program.
4. Read one sensor.
5. Discuss Wi-Fi as the bridge between device and network.
6. List three IoT examples students encounter daily.

Student challenge: Build a sensor-triggered LED on ESP32.

Evidence of learning: Student explains one reason to choose ESP32 over a basic Arduino for IoT.

After class: Draw an IoT system with device, network and user interface.

Objective: Create a simple local webpage that controls hardware.

Key concepts: Local web server, browser request, control interface.

Materials: ESP32-S3, Wi-Fi network, LED.

Hands-on plan

1. Connect ESP32 to the local Wi-Fi network.
2. Start a simple web server.
3. Open the board's page from a browser on the same network.
4. Create ON/OFF controls.
5. Map webpage actions to LED output.
6. Test from more than one device if the network permits.

Student challenge: Add a second output control.

Evidence of learning: Student can describe the path: browser → network → ESP32 → output.

After class: Sketch a two-button IoT control webpage.

Objective: Display live sensor information on an ESP32 webpage.

Key concepts: Sensor data on webpage, refresh/polling concept, data presentation.

Materials: ESP32-S3, DHT11 and/or ultrasonic sensor, local webpage.

Hands-on plan

1. Read the sensor reliably on ESP32.
2. Create a clean variable for each reading.
3. Send formatted readings to the webpage.
4. Add units and clear labels.
5. Refresh/update the displayed values.
6. Test stability and discuss what happens when the sensor is disconnected.

Student challenge: Add a simple status such as NORMAL/WARNING.

Evidence of learning: Student demonstrates live sensor data and explains where the data originates.

After class: Design a dashboard layout with three cards.

Objective: Build a small smart-home prototype.

Key concepts: Remote control, relay output, automation rules, manual/automatic modes.

Materials: ESP32-S3, relay module, low-voltage loads/LEDs for classroom demonstration, optional PIR/LDR.

Hands-on plan

1. Start with safe low-voltage LED output before any larger load.
2. Create webpage ON/OFF control.
3. Add a sensor trigger such as PIR or LDR.
4. Implement manual mode and automatic mode.
5. Test conflicts between manual and automatic commands.
6. Add a clear status indicator.

Student challenge: Create an automatic light that can also be overridden from the webpage.

Evidence of learning: Student explains manual vs automatic control.

After class: Draw a smart-room block diagram.

Objective: Improve the reliability and safety of an IoT prototype.

Key concepts: Fail-safe, access control basics, input validation, test cases.

Materials: ESP32 IoT project from Class 39.

Hands-on plan

1. List what should happen if Wi-Fi disconnects.
2. Define a safe default output state.
3. Add simple validation for control inputs.
4. Test sensor failure/disconnection.
5. Test repeated webpage commands.
6. Document three failure cases and their handling.

Student challenge: Design a 'safe mode' that activates when the system loses its expected input.

Evidence of learning: Student produces a short test table and demonstrates at least two failure-handling behaviors.

After class: Write five safety rules for a connected device.

Objective: Integrate multiple inputs and outputs into one system.

Key concepts: Multiple sensors, occupancy logic, servo barrier, display.

Materials: IR sensors, ultrasonic sensor, servo, LCD/I2C LCD, Arduino.

Hands-on plan

1. Detect a vehicle/object using IR or ultrasonic.
2. Display FREE/OCCUPIED status.
3. Control a servo barrier.
4. Add a second slot or occupancy indicator if hardware permits.
5. Test entry and exit sequences.
6. Document the state transitions.

Student challenge: Add a simple parking-full condition.

Evidence of learning: Student demonstrates a complete entry/occupancy/exit flow.

After class: Design a two-slot parking layout.

Objective: Build a small access/toll prototype.

Key concepts: RFID authentication, IR detection, servo barrier, LCD feedback.

Materials: RC522, RFID cards/tags, IR sensor, servo, LCD, Arduino.

Hands-on plan

1. Read RFID UID.
2. Define authorized and unauthorized behavior.
3. Use IR to detect a vehicle/object.
4. Open servo barrier for authorized access.
5. Display ACCESS GRANTED/DENIED.
6. Test multiple cards and repeated attempts.

Student challenge: Add a simulated toll amount or user category to the display.

Evidence of learning: Student explains the sequence from detection to authorization to barrier action.

After class: Draw the access flowchart.

Objective: Build a staged security system rather than a single-sensor alarm.

Key concepts: Multi-factor logic, RFID, keypad, PIR, alarm states.

Materials: RFID RC522, keypad, PIR, buzzer, LED, Arduino.

Hands-on plan

1. Test RFID as first-level input.
2. Test keypad as second-level input.
3. Add PIR monitoring after successful access.
4. Create states: LOCKED, VERIFY, UNLOCKED, ALARM.
5. Test correct and incorrect sequences.
6. Add clear user feedback with LEDs/buzzer.

Student challenge: Add a temporary lockout after repeated incorrect attempts.

Evidence of learning: Student explains why multiple independent checks can improve system design.

After class: Design the four-state security diagram.

Objective: Understand and prototype a fire-response robot sequence.

Key concepts: Flame detection, autonomous response, pump, motors, safety.

Materials: Flame sensor, ultrasonic/IR, robot chassis, motors, motor driver, water pump.

Hands-on plan

1. Test flame sensor response safely using an appropriate controlled demonstration.
2. Map flame detection to a robot response.
3. Test motor movement independently.
4. Test pump independently.
5. Combine: search/detect → approach → stop → pump response.
6. Add an obstacle condition so the robot does not blindly approach.
7. Discuss that classroom flame experiments must be controlled and supervised.

Student challenge: Create a decision flow that prioritizes obstacle avoidance and safe stopping.

Evidence of learning: Student can explain the complete response sequence.

After class: Draw the robot's decision flowchart.

Objective: Prepare a complete engineering plan before final construction.

Key concepts: Problem statement, block diagram, BOM, flowchart, modular design.

Materials: Student-selected capstone components, paper/digital design tool.

Hands-on plan

1. Choose one problem worth solving.
2. Write a clear problem statement and measurable objective.
3. Create a block diagram.
4. Prepare component/BOM list using available kit parts.
5. Create a flowchart.
6. Break software into modules/functions.
7. Plan at least three tests before building.

Student challenge: Peer-review another student's design and suggest one improvement.

Evidence of learning: Design must include problem, objective, inputs, controller, outputs, BOM, flowchart and tests.

After class: Finalize capstone design and prepare parts.

Objective: Convert the approved design into a physical prototype.

Key concepts: Mechanical/electrical integration, build discipline, documentation.

Materials: Student-selected capstone components.

Hands-on plan

1. Lay out all components and verify the BOM.
2. Build the mechanical structure first.
3. Create power and ground distribution carefully.
4. Connect one module at a time.
5. Test each module before combining.
6. Photograph/record major build stages.
7. Update the build log with problems and decisions.

Student challenge: Make the first working subsystem operate before the end of class.

Evidence of learning: At least one major subsystem must work independently.

After class: Prepare a list of unfinished connections and next steps.

Objective: Integrate sensors, logic and outputs into the complete system.

Key concepts: Modular code, integration, event/state logic.

Materials: Capstone prototype and computer.

Hands-on plan

1. Test each sensor individually.
2. Test each actuator individually.
3. Combine one input with one output.
4. Add the second subsystem.
5. Move repeated code into functions where appropriate.
6. Run a full system test.
7. Record the first major failure and debug it systematically.

Student challenge: Add one small improvement that was not in the original prototype.

Evidence of learning: Core project flow works from input to output.

After class: Prepare a 1-minute explanation of how the code works.

Objective: Teach students to improve a prototype using evidence rather than random changes.

Key concepts: Test cases, fault isolation, controlled changes, reliability.

Materials: Capstone project, test sheet.

Hands-on plan

1. Write five test cases with expected results.
2. Run tests without changing the code.
3. Record actual results.
4. Identify the highest-priority failure.
5. Change only one variable/code section at a time.
6. Retest and compare.
7. Complete a final reliability run.

Student challenge: Create one failure intentionally and explain how you would diagnose it.

Evidence of learning: Student completes a test table and can explain at least one debugging decision.

After class: Prepare final demo checklist.

Objective: Prepare students to communicate their engineering work clearly.

Key concepts: Problem-solution-impact, technical communication, demonstration skills.

Materials: Capstone, presentation/poster template, camera optional.

Hands-on plan

1. Write a one-sentence problem statement.
2. Explain the solution in simple language.
3. Show the block diagram.
4. Identify the key technology.
5. Demonstrate the prototype.
6. Explain one challenge and how it was solved.
7. State one future improvement.
8. Practice a 2–3 minute presentation.

Student challenge: Explain the project to a younger student without using technical jargon.

Evidence of learning: Student can present problem, solution, technology, working and future scope.

After class: Final rehearsal and project setup.

Objective: Demonstrate technical ability, problem solving and communication.

Key concepts: Demonstration, viva, reflection, engineering portfolio.

Materials: Completed capstone, project notes, test sheet.

Hands-on plan

1. Student gives a 2–3 minute presentation.
2. Student performs a live demonstration.
3. Mentor asks 2–3 questions about sensors, code and decisions.
4. Student explains one failure and improvement.
5. Mentor scores the project using the rubric.
6. Student completes a reflection: what I learned, what I built, what I would improve.
7. Create a next-step roadmap toward advanced robotics/IoT.

Student challenge: Optional: propose one advanced version using ESP32, AI, additional sensors or better control.

Evidence of learning: Final rubric: concept 15, coding 15, electronics 15, functionality 20, problem solving 10, innovation 10, presentation 10, documentation 5.

After class: No regular homework; student receives a personalized next-level recommendation.