The Pedagogical Problem

The transit method is how the majority of confirmed exoplanets have been found. When a planet passes in front of its host star, it blocks a fraction of the star’s light. A sufficiently precise light sensor pointed at the star will record a characteristic dip: a flat-bottomed decrease in flux during the transit, with a precise shape determined by the ratio of the planet’s radius to the star’s radius, the duration of the transit, and the geometry of the orbit.

This is conceptually accessible. The physics is essentially shadow casting — a topic covered in primary school — applied to an astronomically interesting situation. Students understand it quickly and find it genuinely exciting.

The problem is the implementation. How do you actually demonstrate this in a classroom?

Standard approaches divide into three categories, each with limitations:

1. Simulations and database exercises: Students work with real data from Kepler or TESS, or use a software simulation. These are conceptually valid but remote from physical experience. There is no sensor, no measurement, no uncertainty to grapple with.

2. Prefabricated kits: Products like PocketLab or Pasco offer purpose-built transit experiment setups. They work, but they are expensive, closed-source, and require manufacturer-specific software. A school that buys a Pasco sensor is locked into the Pasco ecosystem.

3. DIY benchtop setups: Various published designs use phototransistors, Arduinos, or similar components with a benchtop light source. These are flexible and cheap but require component procurement, assembly, and some technical confidence from the teacher. The barrier to entry is real.

What was missing was an approach that was inexpensive, open-source, required no specialist equipment procurement, and worked at the level of a student experiment rather than a teacher demonstration.

The Smartphone Solution

Modern Android smartphones include an ambient light sensor that is directly accessible via phyphox, the free measurement app developed at RWTH Aachen. Set up the experiment correctly, and the phone records a real-time light curve.

The basic setup requires three things:

• A light source (a standard desk lamp, ideally with a constant-brightness LED bulb to avoid flicker)
• An opaque sphere to act as the “planet” (a tennis ball, a ping-pong ball, anything with a defined circular silhouette)
• A smartphone running phyphox, positioned beneath the lamp at a fixed distance and oriented so the light sensor faces upward

When the sphere is moved across the light path at a controlled height and speed, the light sensor records a transit: a smooth dip in measured illuminance with the flat-bottomed shape characteristic of a planetary transit across a uniformly bright disk.

This is the core experiment. It works. The transit signal is clear enough to measure even with the modest precision of a phone’s ambient light sensor, provided the background illumination is controlled (dark room or at least consistent ambient light).

The iPhoneRoblem and Its Solution

Apple devices do not expose their ambient light sensor through any public software API. An iPhone running phyphox cannot access the sensor that is physically present in the device.

The workaround we recommend: an external Bluetooth light sensor connected to phyphox. Options include the TI SensorTag CC2650, Bluetooth multimeters such as the OWON B35T, or an Arduino Nano 33 BLE Sense. The Arduino option is particularly well-suited to educational contexts: it is open-source, it is inexpensive, and its absence of a built-in operating system makes it more reliable as a pure sensor.

The external sensor approach also has a benefit beyond iPhone compatibility: it produces more consistent data across different devices, since you are measuring at a fixed external point rather than through whatever optical pathway the phone manufacturer chose. For experiments where comparison across student groups matters, this is not trivial.

Video-Aided Light Curve Analysis

The standard approach to a transit experiment is: measure the dip, calculate the planet-to-star radius ratio from the relative depth, done. This works and is pedagogically valid.

The paper introduces a complementary approach: simultaneously recording a video of the “planet” passing in front of the “lamp”, and using the video frames to cross-reference the light curve data.

Why? Because the light curve from a real transit experiment does not look exactly like the idealised textbook version. There is noise. There is baseline drift. The “ingress” and “egress” phases — where the planet is partially in front of the star — are often unclear at smartphone sensor resolution. Students frequently have difficulty connecting the shape of the curve to the physical geometry that produced it.

Video-aided analysis addresses this directly. Frame-by-frame, students can see exactly where the planet was at each moment in the light curve. The ingress becomes visible: when the sphere first touches the lamp’s light cone, the sensor begins to register the dip. The mid-transit flat bottom corresponds to full occultation of a central portion of the lamp. The egress mirrors the ingress. The correspondence between geometry and photometry — which is the conceptual core of the transit method — becomes explicit.

In a teaching context, this turns the error and noise in the light curve from an obstacle into an educational resource. Students can identify specific features of the curve and ask: what was happening in the physical experiment at that moment? The uncertainty is no longer an embarrassment. It is a diagnostic.

Scaffolding Levels

The paper distinguishes three implementation modes, corresponding to different levels of student independence:

Demonstration experiment: Teacher sets up and runs the apparatus. Students observe and discuss. Appropriate as an introduction to the concept before students engage with it independently.

Guided student experiment: Students follow a structured procedure, with specified setup, data collection protocol, and analysis worksheet. Appropriate for students who have not designed their own experiments and for lesson contexts where time is limited.

Open inquiry: Students are given the materials and a research question — “How does the depth of the transit dip depend on the size of the planet?” — and design their own procedure. Appropriate for upper secondary students with experience in experimental design, and for lesson contexts that explicitly address scientific method.

The materials for all three modes are described in the paper. The open inquiry mode is the most demanding but also the most research-authentic: students are not following a protocol but building one, confronting the actual decisions that experimental physicists make.

From the Classroom to the Telescope

A transit experiment with a lamp and a phone is, obviously, not the same as the photometry done by TESS or the James Webb Space Telescope. The planet-star radius ratios measurable in the classroom analog are much larger than for most real exoplanets. The signal-to-noise is worse. The lamp is not a star.

But the method is the same. The measurement principle — flux dip proportional to the square of the radius ratio, duration determined by orbital geometry — is the same physics that Kepler used to find thousands of planets. When students calculate the “radius” of their tennis-ball planet from their light curve, they are doing, in miniature, what professional astronomers do with data from space.

This connection to real research is not incidental to the pedagogy. It is central to it. The transit method works as a classroom experiment not because it is a good demonstration of some abstract physics principle but because it is a genuine slice of how contemporary science actually operates. The question the experiment answers — is there something out there? — is the same question the professional community is asking.

The simulation companion to this work — a browser-based model of transit photometry with full limb darkening, exomoon scenarios, and N-body dynamics — is described in this separate post. The simulation is the place to go when you want to explore parameter space; the physical experiment is the place to go when you want to understand what a measurement actually is.

Connection to the astro-lab

The transit experiment described here grew directly out of the astro-lab project at the University of Cologne, where Alexander Küpper and I had been developing smartphone-based analogy experiments for exoplanet detection since the COVID pivot in 2020. The astro-lab@home established the feasibility of the smartphone approach; the A+R 2022 paper on Analogieexperimente für die Transitmethode explored the design space more systematically; the TPT 2024 paper is the version written for an international teacher audience, with the comparative equipment table, the video-aided analysis technique, and the scaffolding levels made explicit.

If you want to extend the experiment to exomoons — detecting the gravitational wobble that a moon induces in a planet’s transit — that work is described in a later post.

For the curriculum article that places the transit experiment in the NRW Sekundarstufe I context — including the Direct Imaging pre-experiment — see Fremde Welten.

References

Spicker, S. J., & Küpper, A. (2024). Exoplanet hunting in the classroom: An easy-to-implement experiment based on video-aided light curve analysis with smartphones. The Physics Teacher, 62(3). https://doi.org/10.1119/5.0125305

Küpper, A., & Spicker, S. J. (2022). Analogieexperimente zur Transitmethode für den Einsatz in Schule und Hochschule. Astronomie+Raumfahrt im Unterricht, 59(5).

Staacks, S., Hütz, S., Heinke, H., & Stampfer, C. (2018). Advanced tools for smartphone-based experiments: phyphox. Physics Education, 53(4), 045009. https://doi.org/10.1088/1361-6552/aac05e

Changelog

• 2025-10-03: Updated the DOI for Spicker & Küpper (2024) to the correct 10.1119/5.0125305.

The Gap in the Curriculum

Most physics and astronomy teaching units that address the search for extraterrestrial life focus on exoplanets. The transit method gets visualised, a light curve gets plotted, and the lesson ends with: some exoplanets are in the habitable zone. The end.

What tends to get omitted: moons of exoplanets — exomoons — could equally be candidates for extraterrestrial life, particularly if the exoplanet itself sits in the habitable zone. The moon would then be in the habitable zone too, and a large moon could maintain the atmospheric conditions necessary for liquid water. The possibility is taken seriously in the astrophysics community, and survey data consistently shows that students find the question of life in the universe among the most interesting topics in all of science.

The pedagogical gap is this: the transit method is routinely demonstrated in analogy experiments, but the extension to exomoon detection is almost never treated experimentally, even though it is a natural continuation of the same experiment with only minor modifications. This paper is an attempt to close that gap.

What an Exomoon Signal Looks Like

When only a planet transits a star, the resulting light curve shows a characteristic symmetric dip: flux drops as the planet moves in front of the star, holds at a reduced level during full transit, and recovers as the planet exits. The normalised flux during the flat-bottomed phase is:

where the dip depth $\delta = A_p / A_s$ is determined by the ratio of the planet’s cross-sectional area to the star’s.

When the planet has a moon, the situation is more complex. The light curve is now governed by:

where $A_m$ is the moon’s cross-sectional area and $A_{pm}(t)$ is the time-dependent overlap between the planet’s and moon’s projected disks (the moon is orbiting the planet, so this overlap changes during the transit).

The consequence: additional dips and asymmetries appear in the light curve. The moon can transit slightly before the planet (causing a small flux dip before the main transit begins), or slide in front of the planet during the transit (temporarily reducing the combined occulting area, causing a brief flux recovery in the middle of the dip), or emerge from behind the planet on the exit side (causing a small dip after the main transit ends). The exact signature depends on the relative sizes of planet and moon, their orbital period ratio, and the geometry of the particular transit.

These signatures are small. In real astrophysics, this is why no exomoon has been unambiguously confirmed. In a classroom analogy experiment, the signals are large enough to see clearly — which is exactly what makes the experiment pedagogically useful.

The Experimental Setup

The starting point is a standard transit analogy experiment: a sphere (the planet) on a rod, moved slowly around a lamp (the star) by a slowly rotating motor. A light sensor — an Android smartphone running phyphox, or an Arduino with a suitable sensor — records the illuminance over time. The resulting light curve shows the characteristic symmetric transit dip.

The modification is straightforward: attach a small battery-powered motor to the planet sphere, with a smaller sphere (the moon) on the motor’s arm. The motor we used is a disco ball motor — inexpensive, widely available, and with a rotation speed that works well relative to the transit timescale if you choose the geometry appropriately.

The result is a physical system with two independent circular motions:

• The planet orbiting the star (driven by the main slow-rotation motor)
• The moon orbiting the planet (driven by the disco ball motor)

When this system transits the “star” (the lamp), the light sensor records a compound light curve with the exomoon signatures described above.

One technical note on sensors: High sample rate matters here. The exomoon signatures are brief features on top of the transit dip, and a sensor that samples too slowly will average them out. We found that the TI SensorTag CC2650, despite being a reasonable choice for the basic transit experiment, has a light sensor sample rate of only 1.25 Hz — too slow to resolve exomoon signatures reliably. Android smartphones and Arduinos both achieve adequate sample rates. The Pasco light sensor used in the paper samples at up to 20 Hz and resolves the features clearly.

Reading the Light Curves

The paper presents two distinct light curve types that emerge from the experiment, each with a different exomoon orbital configuration.

Type 1: The moon’s orbital period is short relative to the transit duration. Multiple exomoon signatures appear within a single transit. These include:

• A small dip before the main transit begins (moon transiting alone)
• Asymmetric ingress/egress (moon leading or trailing the planet)
• A brief flux recovery midway through the transit (moon passing behind the planet, reducing the total occluding area)
• A small post-transit dip (moon still in front of the star after the planet has exited)

Type 2: Specific orbital phase alignment where the moon moves directly behind the planet at the moment of maximum occultation. In this case, the deepest point of the transit corresponds to planet alone blocking the star (moon hidden behind planet). As the moon emerges from behind the planet, the total occluded area increases again briefly before both planet and moon exit.

This second case is particularly useful for quantitative analysis: if the orbital geometry is right, students can separately determine the planet’s radius from the secondary dip depth and the combined planet-moon radius from the primary dip depth.

Video + Light Curve Together

The paper recommends recording a video of the experiment simultaneously with the light sensor measurement, from the perspective of the sensor (i.e., looking up at the lamp from below). This technique — which is also central to the transit method paper — is even more valuable here.

Without the video, the exomoon signatures in the light curve are easy to misread as noise or experimental error. With the video, students can advance frame by frame through the moments corresponding to the unusual features and see exactly what the physical system was doing: the moon sliding in front of the planet, the moon emerging from the planet’s shadow, the moon transiting alone at the start or end of the main event.

The cognitive load of interpreting an unfamiliar, complex signal drops substantially when the signal can be correlated frame by frame with a visual record of what produced it.

Differentiation and Extensions

The paper suggests the exomoon experiment as an extension for higher-ability students at the end of a unit on exoplanet detection, not as the entry point. The transit method should come first; the exomoon experiment builds on it.

For students who are comfortable with quantitative analysis, the formula above allows a full treatment: given the measured light curve and a known lamp radius, students can derive both the planet radius and the moon radius from the dip depths at the appropriate moments.

Possible further extensions:

1. Noise floor investigation: systematically vary the moon’s size and determine the smallest moon still detectable. This connects directly to the real astrophysical problem — the reason no exomoon has been confirmed is that the signal is buried in noise.
2. Period ratio effects: vary the transit speed (and thus the effective period ratio between moon and planet) to see how the light curve changes.
3. Sensor comparison: test different sensor types and compare their ability to resolve exomoon signatures. This turns the instrumental limitation into an explicit investigation.

For the deeper theoretical connections — transit timing variations, the David Kipping approach to exomoon detection — see the transit simulation post, which models these effects in a browser-based tool.

For the secondary school curriculum context and the Direct Imaging pre-experiment that typically precedes the transit unit, see Fremde Welten.

References

Küpper, A., & Spicker, S. J. (2023). Ein Analogieexperiment zur Suche nach Exomonden. MNU Journal, 76(5).

Sato, M., & Asada, H. (2009). Effects of mutual transits by extrasolar planet-companion systems on light curves. Publications of the Astronomical Society of Japan, 61(4), L29–L34.

Tusnski, L. R. M., & Valio, A. (2011). Transit model of planets with moon and ring systems. The Astrophysical Journal, 743(1), 97.

Heller, R. (2018). On the detection of extrasolar moons and rings. In H. J. Deeg & J. A. Belmonte (Eds.), Handbook of Exoplanets (pp. 835–851). Springer.

Küpper, A., Spicker, S. J., & Schadschneider, A. (2022). Analogieexperimente zur Transitmethode für den Physik- und Astronomieunterricht in der Sekundarstufe I. Astronomie+Raumfahrt im Unterricht, 59(188), 46–50.

Changelog

• 2025-10-03: Updated the Tusnski & Valio (2011) reference to use article number 97, replacing the previous page range “1–16.”

Where Students Start

Before students encounter the transit method, most of them have a clear mental model of how exoplanet detection works: you point a large telescope at a nearby star, and if there is a planet, you see it. “You could see them [the exoplanets] with a telescope/binoculars” and “You can see them with an extremely powerful telescope” are typical responses from year 8–9 students before they work through an actual detection unit.

This is not an unreasonable starting intuition. Telescopes see things far away. Planets are things far away. The inference seems to follow.

What it misses is the contrast ratio problem. A star is not just brighter than its planets — it is overwhelmingly, almost incomprehensibly brighter. In visible light, a star like the Sun outshines Jupiter by roughly a billion to one. Against that glare, the planet is functionally invisible. Direct imaging of exoplanets is possible in special circumstances — young planets far from their stars, imaged in infrared — but for the vast majority of exoplanets, it is not a viable detection method.

The unit described in this article takes that misconception as its entry point and builds from there.

The Direct Imaging Experiment

The first experiment in the unit is a hands-on demonstration of why direct imaging is difficult.

The setup: a student points their smartphone camera at a small light source (a switched-on torch). Directly next to the torch, barely a few centimetres away, is a pin with a coloured head — the “exoplanet”. On the phone’s display, the pinhead is invisible. The torch (star) drowns it out completely.

Students can then investigate what would need to change for the pinhead to become visible. The answer they discover: block the torch with a small disc held in front of the camera at the right distance. With the direct glare suppressed, the illuminated pinhead becomes visible in the image.

This is a coronagraph in miniature. The same principle is used in real direct-imaging instruments like SPHERE on the VLT or the coronagraph in the Nancy Grace Roman Space Telescope. Students discover, experimentally, the essential idea: to see an exoplanet directly, you need to suppress the star’s light without blocking the planet’s.

The experiment also motivates a natural follow-on question: under what conditions does direct imaging work at all? Students can vary the pinhead distance from the torch and its size, exploring qualitatively the conditions under which the “exoplanet” becomes detectable even with partial suppression. The answer — large planets, far from their host star — matches the real observational bias: most directly imaged exoplanets are large, young (still warm from formation), and in wide orbits.

The Transit Experiment

Once the limits of direct imaging are established, the unit introduces the transit method as the primary indirect technique. The pedagogical structure is deliberate: students have already understood that you cannot usually see exoplanets directly, which motivates the question of how else you might detect them.

The transit experiment uses a lamp as the star, a ball moved by hand (approximately periodically) around the lamp, and an Android smartphone running phyphox as the light sensor. When the ball crosses in front of the lamp from the sensor’s perspective, the measured illuminance dips. Students see a real light curve — not a simulation, not a graph from a database, but something they produced themselves from a physical measurement.

Two phyphox experiment files are provided for download (via QR code in the article and at astro-lab.app):

Basic experiment: records the raw illuminance data and displays the light curve. The focus is qualitative — what shape does the dip have? What determines the depth? What determines the period? Students can formulate the relationship between dip depth and planet-to-star size ratio as a qualitative rule (the larger the planet relative to the star, the deeper the dip) without necessarily working through the mathematics.

Extended experiment: adds real-time calculations of the transit depth $\Delta F$, the maximum illuminance $I_*$ and transit illuminance $I_\text{transit}$, the transit duration, and the orbital period. For students who are ready for it, this allows a quantitative derivation of the “planet” radius from the light curve — given a known lamp radius and the measured transit depth:

The extended experiment also invites critical engagement with the model: the radius derived from the analogy experiment will differ from the actual ball radius, because the distance ratios in the tabletop setup are not to scale. Making that discrepancy explicit — and asking students why it arises — is good science practice.

Limits of the Transit Method

A recurring theme in the unit is that every detection method has limits, and understanding those limits is part of understanding the method.

For the transit method, the fundamental limit is inclination. A transit is only observable if the planet’s orbital plane is aligned (nearly edge-on) relative to our line of sight. Most exoplanetary systems, viewed from Earth, will not be aligned in this way. The transit method is therefore a biased sample: it preferentially detects planets in edge-on orbits, and it misses most planets entirely.

Students can explore this experimentally: tilt the plane of the ball’s orbit away from edge-on and observe what happens to the light curve. The dip disappears. This connects naturally to a broader point about how astronomical surveys work: when we report “X% of stars have detectable planets”, we are reporting a fraction that has been corrected for this and other observational biases.

The article includes a differentiation note: the limits investigation works well as an open inquiry task, with students formulating and testing their own hypotheses about what orbital configurations produce detectable transits.

Exoplanets as a Curriculum Bridge

One point the article makes explicitly is that exoplanets are not just an astronomy topic but a context that connects to multiple items in the German physics curriculum for Sekundarstufe I. The cross-connections include:

• Optics: the seeing process (why does the star outshine the planet?), shadow formation, refraction in telescopes
• Mechanics: orbital period, Kepler’s laws at a qualitative level, the habitable zone as a consequence of stellar luminosity and distance
• Thermodynamics: planetary surface temperature, the greenhouse effect, albedo
• Pressure: atmospheric pressure, habitability (a connection developed more fully in the Mission to Mars experiment)

The motivating context — could this planet host life? — sustains student engagement across these topics in a way that treating them in isolation does not.

What Comes After

The transit method is a productive entry point, but the search for extraterrestrial life does not end with planet detection. The article closes by noting that the detected exoplanets need to be analysed for habitability — which depends on orbital radius (habitable zone), stellar temperature, planet radius (mass is not available from transit data alone), atmospheric composition, albedo, and greenhouse effect.

Many of these can be connected back to physics experiment contexts, and the astro-lab project has developed smartphone-based analogy experiments for several of them. Detailed information on these is at astro-lab.app.

For the full pedagogical sequence — from the original astro-lab student laboratory, through the COVID pivot to home experiments, to the return to school — see The Lab Goes Home. For the exomoon extension, which takes the transit experiment further into the question of moon-hosted life, see Can a Planet Have a Moon?.

References

Küpper, A., & Spicker, S. J. (2023). Fremde Welten — Die Suche nach Exoplaneten mit Analogieexperimenten thematisieren. Unterricht Physik, 34(194), 4–9.

Küpper, A., Spicker, S. J., & Schadschneider, A. (2022). Analogieexperimente zur Transitmethode für den Physik- und Astronomieunterricht in der Sekundarstufe I. Astronomie+Raumfahrt im Unterricht, 59(188), 46–50.

Spicker, S. J., & Küpper, A. (2024). Exoplanet hunting in the classroom: An easy-to-implement experiment based on video-aided light curve analysis with smartphones. The Physics Teacher, 62(3). https://doi.org/10.1119/5.0125305

MSB NRW (2019). Kernlehrplan für die Sekundarstufe I — Gymnasium in Nordrhein-Westfalen: Physik. Ministerium für Schule und Bildung NRW.

Changelog

• 2025-10-03: Updated the DOI for Spicker & Küpper (2024) to the correct 10.1119/5.0125305.

What the astro-lab Was

Before the pandemic, the astro-lab at the University of Cologne was a student laboratory focused on extrasolar planets. School groups — mostly secondary school students — came in and worked through a set of analogy experiments: how do you detect a planet you cannot see? How do you infer its size, its orbit, whether it might be habitable?

The pedagogical bet was that exoplanet research, precisely because it is headline-generating and genuinely open-ended, could counteract the motivational slump in physics that tends to set in around middle school. The context — life in the universe, habitable worlds, the possibility of something out there — did a lot of the work that no abstract force diagram could do.

The experiments themselves were analogy experiments: a lamp standing in for a star, a sphere on a track standing in for a planet. The key measurement was the transit: when the “planet” passed in front of the “star”, the light sensor registered a dip. Students measured the dip, estimated the ratio of areas, connected it to radius, and got a number that meant something. The number was not precise. It did not need to be. It was real.

Spring 2020

In March 2020, schools shut down, and the University of Cologne followed. Visits to the astro-lab were cancelled. The question the team faced — Alexander Küpper, André Bresges, and I — was not whether to do something but what was actually feasible.

German distance learning at the time was characterised by worksheet packages delivered to students with minimal interactive contact. Only 16% of German students reported being in video conferences with their teachers; 30% reported no contact at all since the initial shutdown. The infrastructure was not there, the habits were not there, and the expectation that students had the materials and equipment for a physics lab at home was not warranted.

What students did have, almost universally, was a smartphone.

Modern smartphones contain a remarkable array of sensors: ambient light sensors, accelerometers, gyroscopes, barometers, magnetometers. The app phyphox, developed at RWTH Aachen, makes those sensors accessible with a clean interface designed for use in education. If the sensor hardware was already in students’ pockets, the lab setup problem became: what household materials can stand in for the rest of the apparatus?

astro-lab@home: Bringing Science to the Sofa

The astro-lab@home project adapted the original lab experiments for home use with smartphones and everyday materials. The core transit experiment — measuring the dip in light caused by an opaque object passing in front of a lamp — turned out to be reproducible without any specialist equipment. A table lamp, a ball on a string, and a smartphone positioned beneath the lamp gave you the raw data. phyphox recorded the light curve in real time.

We designed the setup to be flexible enough to work with what students actually had. The default used the ambient light sensor in Android devices, which is directly accessible through phyphox. iPhones do not expose their light sensor through software interfaces, so for Apple devices we recommended an external Bluetooth sensor — an inexpensive workaround that also had the advantage of producing more consistent data across device types.

The resulting package was not just an equipment list. We developed accompanying materials that explained the physics (why does a transit produce a specific shape of dip rather than a sharp cutoff?), connected the analogy experiment to the real science (how does this scale up to the actual transit photometry done by TESS and Kepler?), and offered scaffolding at different levels of independence.

The project was published in the IAU’s CAPjournal in 2022 — a journal aimed at communicators and educators in astronomy. The audience was intentionally broad: teachers looking for accessible classroom activities, outreach organisations trying to reach students at home, curious individuals who wanted to do something real with their phone. “Bringing science to the sofa” was the headline, and that was genuine. The experiments worked in a living room.

What Came Next: astro-lab@school

When schools reopened and in-person teaching became possible again, the question was not simply “back to normal” but what the COVID period had actually taught us about the format.

The astro-lab@school, published in Astronomie+Raumfahrt in 2022, addressed that question directly. Some things from the home version had worked better than expected. The smartphone-based setup was cheaper, more portable, and more directly in students’ hands than the original benchtop apparatus. There was something pedagogically valuable about students using their own devices rather than lab equipment provided by someone else.

The astro-lab@school retained the smartphone-centred approach and adapted it for a school context: class sizes, time constraints, the reality of mixed equipment across a room of thirty students. The experiments from the home version were modified for group work and parallel execution. The scaffolding materials were reworked for the paced structure of a school lesson rather than the self-directed format of home use.

The result was not a reversion to the pre-pandemic lab. It was a hybrid: in-person group work, but with tools and methods developed for distributed individual use. The pandemic had, inadvertently, pushed the format toward something more robust.

A Note on What Made This Work

The core technical contribution — smartphones as measurement instruments for analogy experiments in astronomy education — is described in more detail in a later publication in The Physics Teacher, which covers the experimental setups, sensor comparison, and pedagogical progression in a form aimed at an international teaching audience. If you want the how-to, start there.

What I want to note here is something slightly different: the role of context.

The astro-lab bet on exoplanets as a motivational context, and the evidence supports that bet. Exoplanet research remains one of the few areas of physics that generates genuine public enthusiasm, and students' interest in the topic is empirically documented. What the COVID period showed is that the context is robust enough to survive the removal of the lab infrastructure. Students working on transit photometry with a lamp and a smartphone in their kitchen were doing the same thing, conceptually, as students at a benchtop sensor station at the university. The physical setup was different. The question was the same.

That is, I think, a more general lesson. Context-driven education is not dependent on a specific material configuration. The question carries.

For the curriculum unit that places these experiments in the context of the NRW Sekundarstufe I physics syllabus, see Fremde Welten. For the air pressure / Mars experiment that grew from the same lab, see Mission to Mars.

References

Spicker, S. J., Küpper, A., & Bresges, A. (2022). astro-lab@home — bringing science to the sofa. CAPjournal, 31, 12–17.

Küpper, A., & Spicker, S. J. (2022). astro-lab@school. Astronomie+Raumfahrt im Unterricht, 59(6).

Küpper, A., & Schulz, A. (2017). Das Schülerlabor astro-lab an der Universität zu Köln. Astronomie+Raumfahrt im Unterricht, 54(1).

Stampfer, C., & Staacks, S. (2020). phyphox — using smartphones as experimental tools. Physics Education, 55(5), 055007. https://doi.org/10.1088/1361-6552/ab8a2e

The Curriculum Problem

The 2019 revision of the NRW Gymnasium physics curriculum for Sekundarstufe I requires students to be able to describe, in broad outline, the typical stages of stellar evolution. This is new territory for many teachers — it is not a topic that would have appeared in teacher education programmes of ten or twenty years ago, and few teachers have personal experience with it from their own school or university courses.

More fundamentally: stellar evolution is a topic where the usual experimental approach does not work. You cannot compress an interstellar gas cloud in a classroom. You cannot observe a star form in real time. The timescales involved are tens of millions to billions of years; the spatial scales are measured in light-years and astronomical units. The experimental toolkit that works for optics, mechanics, and even much of electromagnetism simply does not apply.

This creates a genuine pedagogical challenge. Students have strong interest in astrophysical topics — the ROSE study documents this consistently — and stellar evolution involves physical concepts that are curriculum-relevant (gravity, pressure, energy, radiation). But the standard path from “concept” to “experiment” to “understanding” is not available in the usual form.

Two approaches are described here. One uses what students do have — smartphones and household materials — to model the physics of stellar formation through analogy. The other accepts that some physics is better learned through structured play, and designs accordingly.

DIY Experiments for Stellar Formation

The physics of star formation starts with an interstellar gas cloud and the competition between gravity and pressure. A cloud collapses when gravity wins: specifically, when the cloud is massive enough (or cold enough) that gravitational attraction overcomes the thermal pressure of the gas. This is the Jeans criterion, and it is the quantitative condition that separates clouds that will form stars from clouds that will disperse.

The qualitative version is accessible to secondary school students: a dense, cold, massive cloud is more likely to collapse than a diffuse, hot, small one. Once collapse begins, it is self-reinforcing — increasing density increases the gravitational attraction, which drives further compression, which increases the density further.

Two DIY experiments were developed to give students a physical encounter with the key concepts, using materials that can be assembled at home or in school without specialist equipment.

Experiment 1: Compression and heating. When a gas is compressed, it heats. This is directly measurable with the temperature sensor in a smartphone (or a separate Bluetooth thermometer connected to phyphox) and a simple compression apparatus — a syringe, a sealed container, or an inflation device. Students observe the temperature rise during compression and temperature drop during expansion, establishing the qualitative relationship. In the stellar formation context: the collapsing gas cloud heats as it compresses, which is why a protostar is hot long before nuclear fusion ignites.

Experiment 2: Self-reinforcing compression. A simple model of the positive feedback loop in gravitational collapse: a weighted ball in a flexible container, which compresses a small spring or air cushion. The more the ball compresses the cushion, the further it falls. Students can explore the threshold conditions under which the system reaches a stable equilibrium versus continues to compress indefinitely — a qualitative model of the Jeans criterion.

Both experiments are designed to be performed with available materials at the DIY/home level. The smartphone’s sensor integration via phyphox provides quantitative data where possible, maintaining the connection to real measurement that is a design principle across all the astro-lab experiments.

Why Stellar Evolution Is Hard to Experiment With

A methodological note worth making explicit: the shift from direct experiment to analogy experiment to board game is not a retreat from rigor. It is a recognition that different kinds of physical and conceptual content require different pedagogical approaches.

For exoplanet detection, we can build a genuine analogy: the physics of a planet blocking a star’s light and a ball blocking a lamp’s light are structurally identical. The analogy experiment produces data whose interpretation follows the same logic as the real scientific data.

For stellar evolution, the analogy is weaker. The compression of a gas syringe models one aspect of the collapse (temperature increase) but not the self-gravitating dynamics, the radiation pressure that eventually halts collapse, or the nuclear ignition that defines the transition from protostar to main sequence star. No tabletop experiment captures the whole process.

This is important to tell students: the experiment models this aspect, and not those aspects. Making the model limits explicit is part of the scientific literacy the unit is supposed to develop.

“Staub und Sterne”: A Board Game for Stellar Evolution

The board game “Staub und Sterne” (Dust and Stars), designed by Miriam Küpper and Alexander Küpper, takes a different route to the same content.

Games have been used in physics education in all phases of a lesson: as entry points (introducing a topic without immediately constraining it to a specific physical question), as vehicles for content acquisition, and as reinforcement and assessment tools. For stellar evolution specifically, the argument for a game is strong: the content involves a branching process with multiple pathways depending on a single initial parameter (mass), it is cyclic (the remnant of stellar death seeds the gas cloud that forms the next generation of stars), and it is inherently dynamic — the drama of a supernova is hard to convey through a diagram but easy to convey through play.

The target audience is years 7–8 (or year 8–9 depending on the school’s internal curriculum placement). The learning objectives:

• Describe the stages of stellar evolution as a function of mass
• Name the possible end states (white dwarf, neutron star, black hole) and the stellar paths that lead to each
• Describe stellar evolution as a cyclic process: the gas cloud produced at the end of a star’s life can, under the right conditions, seed the formation of new stars

The game “Staub und Sterne” (the name translates as “Dust and Stars”) has players navigating a star through its lifecycle, with the key branching decision determined by the star’s initial mass. A low-mass star follows one path; a high-mass star follows another. Both paths end in a stellar remnant and a dispersed gas cloud — raw material for the next cycle.

The game design incorporates the research on flow experience in learning: cooperative or competitive play, immediate feedback on decisions, the kind of engaged attention that is rare in conventional physics lessons and that the ROSE study data suggest is precisely what is missing for many students in physics classrooms.

A Note on What Experiments Cannot Reach

There is a broader point here that the exoplanet posts sidestep because the experiments for exoplanet detection are so unusually good. For most astrophysics — stellar evolution, galactic dynamics, cosmology — there is no analogy experiment that captures the full physics. The observable has been observed, the theory has been developed, but the pedagogical problem of how to give students a physical encounter with that knowledge remains genuinely difficult.

Games, simulations, interactive visualisations, and structural analogies all have a role. Each of them is a partial solution; none of them is what a well-designed experiment is. Knowing which approach fits which content, and being honest with students about the limits of the model you are using, is part of what physics teaching requires.

The experiments described in this post are a start on one small part of that problem.

The exoplanet experiments from the same project are described in the astro-lab@home, Hunting Exoplanets with Your Phone, and Fremde Welten posts.

The misconceptions students bring to stellar evolution — about the Sun, gravity, nucleosynthesis, and the language of astronomy — are documented in detail in Please Stop Saying the Sun Is on Fire, written as a companion to the September 2020 teacher training session that motivated much of this work.

References

Spicker, S. J., & Küpper, A. (submitted). Einfache DIY-Experimente zum Verständnis der Sternentstehung für den Physik- und Astronomieunterricht sowie zu Hause. Astronomie+Raumfahrt im Unterricht.

Küpper, M., & Küpper, A. (2022). Sternentwicklung spielerisch verstehen: Konzeption eines Brettspiels für den Physikunterricht der Sekundarstufe I. Presentation at AG Lehrerfortbildung, Universität zu Köln.

Elster, D. (2008). Was interessiert Jugendliche an den Naturwissenschaften? VFPC Verein zur Förderung des physikalischen und chemischen Unterrichts.

MSB NRW (2019). Kernlehrplan für die Sekundarstufe I — Gymnasium in Nordrhein-Westfalen: Physik. Ministerium für Schule und Bildung NRW.

Ward-Thompson, D., & Whitworth, A. (2011). An Introduction to Star Formation. Cambridge University Press.

The Problem With Air Pressure

Air pressure is one of those topics that students nominally know something about from everyday life and have almost always misconceived. The documented misconceptions are a long list: air is “empty” (nothing in it), air is weightless, air only exerts pressure when it moves (like wind), a vacuum “sucks” rather than being a region where surrounding air pushes in, and pressure increases with height rather than decreasing.

Some of these misconceptions are stubborn precisely because everyday experience seems to support them. Air does not feel like it has weight. A vacuum cleaner does feel like it is pulling. The atmosphere, experienced from inside it, does not announce itself as a pressure source.

The standard approach to this material — explaining atmospheric pressure, defining $p = F/A$, working through barometric altitude formulae — addresses the conceptual gaps at the declarative level. Students can recite that air exerts pressure in all directions. Whether they have actually updated their mental model is a different question.

“Mission to Mars” is a design-based attempt at conceptual change through physical encounter with the consequences of pressure differences.

The Context: Why Mars?

The motivation for choosing the Mars context was empirical, not poetic. The ROSE study — a large international survey of student interests in science — consistently finds that space, astronomy, and human exploration rank among the most motivating contexts for physics learning, for both boys and girls. Physics education research in Germany has known for decades that generic “physics” lessons underperform motivationally compared with context-embedded physics, and astronomy is one of the contexts with the clearest evidence base.

“Mission to Mars” asks students: a crewed mission to Mars would travel through the vacuum of space, with the crew living in a pressurised compartment. The compartment has to maintain atmospheric pressure while surrounded by near-vacuum. What happens if it fails? And how would you design a spacecraft structure to prevent that failure?

The question is concrete. The physics behind it — the difference between the pressure inside the compartment and the near-zero pressure outside, and the forces this pressure difference exerts on any structure — is the content of the lesson.

The Experiment

The full version of the experiment, as we ran it at the astro-lab at the University of Cologne, uses a vacuum pump, a bell jar, and a smartphone running phyphox. The smartphone’s built-in barometric pressure sensor records real-time atmospheric pressure inside the bell jar as the pump evacuates it.

Before building anything, students verify that the smartphone is a functional pressure gauge: they measure the current atmospheric pressure in the room and compare it with a provided reference value. This step matters pedagogically — it establishes that the phone is a real scientific instrument, not just a device for receiving worksheets.

Then comes the design-build-test cycle:

Design: Students are given PVC plumbing pipe sections, empty food containers, resealable bags, rubber bands, clamps, and other household materials. Their task is to build a prototype “spaceship” — a container that will maintain near-atmospheric pressure inside while the bell jar around it is evacuated to low pressure. The phone (or external sensor) goes inside the prototype to measure whether the prototype is holding.

Predict: Before testing, students are asked to state why they think their prototype will or won’t work. This surfaces their preconceptions in a low-stakes way and sets up the next stage.

Test: The prototype goes into the bell jar. The pump runs. The pressure sensor records. The light curve — sorry, the pressure curve — tells the story. Four outcomes are possible:

• Nearly flat line: the prototype is airtight, pressure inside stays near atmospheric. Mission success.
• “Bathtub” curve: a visible failure event — a cap pops off, the pressure inside drops sharply and then equalises. Students hear the pop. They did not expect the pop. This is the moment.
• Gradual decay: the prototype leaks slowly, the pressure inside drops steadily. Invisible failure.
• Noisy signal: something wrong with the setup.

The PVC pipe trap: the PVC pipe is deliberately included because it is the most impressive-looking material and is reliably incorrect. The friction between pipe and lid is insufficient at the pressure differences reached in the bell jar. The lid pops off. Students rebuild.

The Misconceptions, Addressed

The design-test-rebuild cycle forces students to confront the misconceptions listed above in a direct physical way:

Air is empty/weightless: handled in pre-activities with standard demonstrations (the dunked napkin, the deflated-vs-inflated balloon).

Air only exerts pressure when moving: the bell jar demonstration makes this concrete — the sensor shows pressure even in a static, undisturbed volume. When the pump evacuates the jar, the “stillness” of the remaining air doesn’t change its pressure.

A vacuum sucks: this is the crucial one, and the PVC lid pop addresses it more effectively than any explanation. The lid does not get sucked outward. The air inside the prototype at near-atmospheric pressure pushes the lid open against the external near-vacuum. When the lid fails and students hear the rush of air flowing back in after the valve is opened, the direction of the pressure force becomes viscerally clear: it was always the higher-pressure region pushing into the lower-pressure region.

The inquiry is scaffolded through worksheets and index cards, and there is a teaching assistant present in the lab version to catch dangerous situations (the smartphone can be damaged if exposed to too low a pressure — the instructions include a warning about testing pump suction strength before risking the device).

DIY Variants for School and Home

The full lab setup is expensive and not portable. One design principle we wanted to maintain was accessibility: the experiment should work at three budget levels.

Low budget (< $5): empty food containers connected to a household vacuum cleaner through a small hole. Works, no real-time measurement visible to students.

Mid budget ($5–$50): translucent storage containers in nested sizes (large = “space”, small = “spaceship”), a small sealing ring to connect the vacuum source. Students can watch the phone display through the container during evacuation. The vacuum achieved is lower than the lab version, but the qualitative experience — the prototype holding or failing — is the same.

Expensive ($500+): the full lab version with bell jar and diaphragm pump. Best analogy, best data, highest barrier.

The DIY take-home message, as the paper puts it: be creative, fail forward. Anything that creates some vacuum and fits a prototype counts.

The experiment adapts readily to e-learning contexts: each group builds a prototype, tests it (or has a family member film it), and presents the outcome — including why the first prototype failed and how the second was improved — in a shared video conference.

A Note on Where This Fits

“Mission to Mars” grew out of the astro-lab at the University of Cologne, the same student laboratory context as the exoplanet transit experiments. The common thread is not the specific physics topic (air pressure here, photometry there) but the experimental approach: smartphones as real measurement instruments, everyday materials as apparatus, an astronomical context that sustains engagement, and a design-build-test cycle that forces students to encounter the physics physically rather than only propositionally.

The air pressure content connects naturally to the exoplanet unit at a curriculum level: habitability of exoplanets depends partly on atmospheric pressure. In the Fremde Welten article, atmospheric pressure is listed as one of the factors that determine whether a detected exoplanet could support life — an explicit cross-link between the two units.

The astro-lab@home post describes how the broader astro-lab programme — including this experiment — was adapted for home use during the pandemic. The air pressure experiment is among the more challenging to replicate at home, but the low-budget vacuum cleaner variant makes a version of it possible.

The design-build-test structure of this experiment also ended up at the centre of a methodological argument during my thesis work. The short version: everyone told me to use grounded theory instead of design thinking as the research framework, and they were right to do so. That story is in a separate post.

References

Spicker, S. J., Küpper, A., & Bresges, A. (2022). Mission to Mars: Concept and implementation of a design-based (hands-on) smartphone experiment helping students understand the effects caused by differences in air pressure. The Physics Teacher, 60(1), 47–50. https://doi.org/10.1119/10.0009109

Küpper, A., & Schulz, A. (2017). Schülerinnen und Schüler auf der Suche nach der Erde 2.0 im Schülerlabor der Universität zu Köln. Astronomie+Raumfahrt im Unterricht, 54(157), 40–45.

Staacks, S., Hütz, S., Heinke, H., & Stampfer, C. (2018). Advanced tools for smartphone-based experiments: phyphox. Physics Education, 53(4), 045009. https://doi.org/10.1088/1361-6552/aac05e

Sjoberg, S., & Schreiner, C. (2010). The ROSE project: An overview and key findings. University of Oslo.

Changelog

• 2025-10-03: Updated the self-citation to the correct year (2022), volume/issue (60(1)), pages (47–50), and DOI (10.1119/10.0009109).