Technology

ChatGPT and its use cases for Physics Education

The internet is abuzz recently with news of ChatGPT (Chat Generative Pre-trained Transformer), an AI chatbot developed by OpenAI that is designed to perform well on tasks that involve generating human-like text.

I was interested to find out how it can help in Physics education and found two main use cases. The first is for students’ own self-directed learning through questioning.

For example, I asked the chatbot what the difference between centrifugal and centripetal force is using the following prompt and was given the response which I pasted here:

Prompt: What is the difference between centripetal and centrifugal force

Centripetal force is a force that acts towards the center of a circular path and is responsible for the change in direction of an object moving in a circular path. It is the force that keeps an object moving in a circular path and is perpendicular to the object’s velocity.

Centrifugal force, on the other hand, is an apparent force that is felt by an observer when an object is moving in a circular path. It is the force that appears to push an object away from the center of a circular path. However, it is not a real force and is only perceived by the observer due to the change in direction of the object.

To illustrate the difference between centripetal and centrifugal force, consider an example of a person swinging a ball on a string in a circular path. The person applies a force on the ball towards the center of the circular path (centripetal force) to keep the ball moving in a circular path. The ball, on the other hand, feels a force pushing it away from the center of the circular path (centrifugal force) due to its change in direction. However, this force is not a real force, but is only perceived by the person holding the ball.

In summary, centripetal force is a real force that acts towards the center of a circular path, while centrifugal force is an apparent force that is only perceived by an observer due to the change in direction of an object moving in a circular path.

I found the responses to the questions to be highly relevant, well-structured and easy to understand. This will serve as a good source of reference for students.

GENERATING LEARNING ACTIVITIES

The second use case for teachers is to generate quick question and activity ideas. I found the responses to be very helpful, even if some modification needs to be done to refine it afterwards.

The first test I did with the AI was to ask it to generate instructions for an experiment and this was the prompt and response:

Prompt: Create an experiment on measuring the speed of sound

Here is an experiment for measuring the speed of sound:

Materials:

  • Two meters of string
  • One meter stick
  • One stopwatch or timer
  • Two people

Procedure:

  1. Tie one end of the string to a stationary object, such as a table leg.
  2. Have one person hold the other end of the string, and have the second person stand a few meters away.
  3. The person holding the string should stretch the string taut and make a sharp, loud noise, such as clapping their hands or snapping their fingers.
  4. The second person should start the stopwatch as soon as they hear the noise, and stop it when they feel the vibration from the string on their hand.
  5. Measure the distance between the two people using the meter stick.
  6. Repeat the experiment a few times to ensure accuracy.

To calculate the speed of sound, use the formula: speed = distance / time. The speed of sound is the distance traveled by the sound wave divided by the time it took for the wave to travel that distance.

Note: This experiment is most accurate when performed in a quiet, indoor space with little to no background noise. The string should be stretched taut and not vibrate excessively. It is also important to measure the distance and time accurately to obtain an accurate result.

Not satisfied with the extent of precision and accuracy of the experiment suggested, I decided to give it a more detailed prompt.

Prompt: Create an experiment on measuring the speed of sound in air with the help of a datalogger

Here is an experiment for measuring the speed of sound in air using a datalogger:

Materials:

  • A long, straight tube with a diameter of at least 1 inch
  • Two clamps
  • A datalogger or sound level meter
  • A tuning fork with a known frequency (such as 512 Hz)
  • A meter stick or ruler

Procedure:

  1. Clamp one end of the tube to a stationary object, such as a table.
  2. Clamp the other end of the tube to a stand that is adjustable in height.
  3. Set up the datalogger or sound level meter at the open end of the tube, making sure it is oriented so that it can accurately measure the sound waves reflected off the other end of the tube.
  4. Strike the tuning fork and hold it near the open end of the tube.
  5. Adjust the height of the stand so that the sound waves from the tuning fork are reflected back and forth between the two ends of the tube.
  6. Use the datalogger or sound level meter to measure the time it takes for the sound waves to travel from one end of the tube to the other and back again.
  7. Measure the length of the tube using the meter stick or ruler.
  8. Repeat the experiment a few times to ensure accuracy.

To calculate the speed of sound in air, use the formula: speed = distance / time. The speed of sound in air is the distance traveled by the sound wave (the length of the tube) divided by the time it took for the wave to travel that distance (the time measured by the datalogger or sound level meter).

Note: This experiment is most accurate when performed in a quiet, indoor space with little to no background noise. The tuning fork should be struck firmly and held close to the open end of the tube to ensure that the sound waves are reflected back and forth between the two ends. It is also important to measure the distance and time accurately to obtain an accurate result.

The second test for it was to get it to set a full structured question:

Prompt: Create a data-response question on thermal physics for GCE A-level

Here is a data-response question on thermal physics for GCE A-level:

A student investigates the relationship between the temperature of a substance and its heat capacity. She measures the heat capacity of 50 g of water at several different temperatures, and records her results in the table below:

Temperature (°C)Heat Capacity (J/°C)
204.2
404.5
604.8
805.1

Using the data in the table, answer the following questions:

  1. What is the heat capacity of 50 g of water at a temperature of 60°C?
  2. Is the heat capacity of 50 g of water a constant value, or does it vary with temperature?
  3. Can you determine the heat capacity of 50 g of water at a temperature of 0°C from this data? Why or why not?
  4. The heat capacity of 50 g of water at a temperature of 60°C is 4.8 J/°C.
  5. The heat capacity of 50 g of water varies with temperature.
  6. It is not possible to determine the heat capacity of 50 g of water at a temperature of 0°C from this data. This is because the heat capacity of a substance may change at different temperatures, and the data provided only includes measurements at specific temperatures. To determine the heat capacity at a temperature of 0°C, additional measurements would need to be taken at that temperature.

The quality of the questions and corresponding answers were decent, even though some refinement will still have to be done as in the case of the speed of sound experiment. What impressed me was that the formatting, including the tabulation was done for us. We only had to cut and paste the activities into a Word document or Google Doc for further editing before assigning them to students.

LET CHATGPT TELL YOU

After figuring it out for myself, I thought, why not let ChatGPT tell me what else it can do in the context of physics education and this was its response:

ChatGPT could potentially be used to:

  • Generate explanations and examples of physics concepts: ChatGPT could be trained on a large dataset of physics explanations and examples and used to generate additional explanations and examples on a variety of topics. This could be helpful for students who need additional clarification or examples to understand a concept.
  • Create practice problems and quizzes: ChatGPT could be used to generate practice problems and quizzes on a variety of physics topics. This could be useful for students who want to test their understanding of a concept or prepare for exams.
  • Simulate physics experiments: ChatGPT could be trained on descriptions of physics experiments and used to generate simulations of those experiments. This could be useful for students who want to understand how an experiment works or for instructors who want to demonstrate an experiment without having to physically set it up.
  • Generate personalized tutoring sessions: ChatGPT could be used to create personalized tutoring sessions for students based on their specific needs and interests. For example, ChatGPT could generate customized explanations and examples for a student who is struggling with a particular concept, or create a customized practice quiz for a student who wants to test their understanding of a topic.

It is important to note that while ChatGPT has the potential to be a useful tool for physics education, it is not a replacement for human instructors and should be used in conjunction with other resources and methods of teaching and learning.

Appreciating the least square method of determining best-fit line

This interactive is designed to help students understand the statistical approach underpinning the drawing of a best-fit line for practical work. For context, our national exams have a practical component where students will need to plot their data, often following a linear trend, on graph paper and to draw a best-fit line to determine the gradient and y-intercept.

The instructions to students on how to draw the best-fit line is often procedural without helping students understand the principles behind it. For instance, students are often told to minimise and balance the separation of plots from the best-fit line. However, if there are one or two points that are further from the rest from the best-fit line (but not quite anomalous points that need to be disregarded), students would often neglect that point in an attempt to bring the best fit line as close to the remaining points as possible. This results in a drastic increase in the variance as the differences are squared in order to calculate the “the smallest sum of squares of errors”.

This applet allows students to visualise the changes in the squares, along with the numerical representation of the sum of squares in order to practise “drawing” the best-fit line using a pair of movable dots. A check on how well they have “drawn” the line can be through a comparison with the actual one.

Students can also rearrange the 6 data points to fit any distribution that they have seen before, or teachers can copy and modify the applet in order to provide multiple examples of distribution of points.

Docking with Tides

Did this simple interactive upon request by a colleague who is teaching the JC1 topic of Oscillations.

Based on the following question, this is used as a quick visual to demonstrate why there must be a minimum depth before the boat approaches harbour.

The rise and fall of water in a harbour is simple harmonic. The depth varies between 1.0 m at low tide and 3.0 m at high tide. The time between successive low tides is 12 hours. A boat, which requires a minimum depth of water of 1.5 m, approaches the harbour at low tide. How long will the boat have to wait before entering?

The equation of the depth of water H based on the amplitude of the tide a can be given by $H = H_o + a \cos \omega t$ where $H_o$ is the average depth of the water.

$H = H_o + a \cos \omega t$

When H = 1.5m,

$1.5 = 2.0 – 1.0 \cos (\dfrac{2 \pi}{12}t)$

$\cos (\dfrac{2 \pi}{12}t) = 0.5$

$t = 2.0 h$

Team-Based Learning with Google Form

Team-based learning is a pedagogical approach that facilitates learning through individual testing and group collaboration. Students are first given time to work on answers individually using the Individual Readiness Assurance Test (iRAT). They then work in teams to discuss the same problems in order to arrive at a consensus and check their answers against a pre-filled MCQ scratch card that reveals if their selected answer is correct or wrong, after which an immediate feedback is given. This is known as the Team Readiness Assurance Test (tRAT). If they got the answer wrong, teams get a chance to either appeal their answer or to try the same question again. A clarification session then ensues, with teachers focusing more on questions that teams have difficulty in.

Schools that want to use Team-Based Learning might either subscribe to platforms that allow for repeated attempts such as InteDashboard or purchase the Immediate Feedback Assessment Technique (IF-AT) scratch cards. There are some free options such as that from Cosma Gottardi.

However, I was wondering if a simple one could be done with Google Form, using the quiz mode together with branching options, to achieve the same results. I tested it out immediately last night and came up with this proof-of-concept. It seems possible and easy to edit.

I created a template for anyone who is keen to try:

https://docs.google.com/forms/d/1l2msnjt2ioSWcmz4GpQWgm1_CoFBRQDmBOwZQopnefI/edit?usp=sharing

Centrifuge Toy

I designed this 3D teaching tool using Tinkercad and printed it out so that my colleague can use it to demonstrate the effect of a centrifuge.

As the toy is being spun, the ball bearings will appear to be thrown outwards. The centripetal forces that are meant to keep them in circular motion is made up of friction and any contact force due to the curvature of the base. If the rate of spin is sufficiently high, there will be insufficient contact force keeping the ball bearings in a circular path and hence, they will spiral outward and land into the cups found near the ends when the spinning stops.

Anyone can 3D-print this design as it had been uploaded into Thingiverse. This is my first original submission and can be found here. You will need 4 tiny balls of no more than 8 mm in diameter. The top is to be covered with a clear sheet of plastic cut-out after tracing the shape using a marker. The sheet can be stuck on the top using normal glue. This plastic cover serves to ensure the balls do not fly out if spun too fast.

A centrifuge toy to demonstrate the effects of rotational motion with insufficient centripetal force.

3D printed Meissner tetrahedrons

These are my 3D-printed Meissner tetrahedrons, each maintaining the same height when rolled in any direction. The Meissner tetrahedron is a 3D version of the 2D Reuleaux triangle, which is a triangle with constant width. A flat platform can be placed on top and remain level when pushed around. The STL files can be obtained from Thingiverse. Sliced using Cura (with treelike supports) and printed with my Creality Ender 3.

Not exactly a physics teaching aid, but it demonstrates the affordance of 3D printing, which allows us to produce interesting objects overnight for lessons or if inspiration strikes. I am going to print a Gomboc next, which is an object when resting on a flat surface have just one stable and one unstable point of equilibrium, and is relevant to the topic of turning effects of forces.