13 of 13 ideas
A.1 Kinematics: 13 ideas
Launch angle and range with a calibrated launcher
Research question. How does the horizontal range of a steel ball fired from a spring launcher at 15° to 75° in 5° steps compare with the ideal prediction, allowing for launch height?
- A.1 Kinematics
- SL and HL
- Easy data
- Overdone: on 5 sites
My take. Overdone (listed on 5 sites) and easily seen as a textbook exercise. Only worth it if you test the model with launch height and speed checks, or use the fitted speed to challenge the ideal model.
Method, physics and where marks are lost+
- Independent variable
- Launch angle, 15° to 75° in 5° steps (13 values), with 5 shots per angle.
- What you measure
- Landing point on carbon paper over white paper, read with a metre rule. The launch speed is found separately with light gates or from a video of a horizontal shot. Range compared with the calculated theoretical range.
- Controlled variables
- Same launcher setting and spring compression, so speed stays fixed and is checked at several angles. Launch height measured and kept the same. Same ball mass. Landing surface at a fixed height, or the height difference corrected in the theory.
- Physics and graph
- For launch and landing at the same height R = v² sin 2θ / g. With a launch height h, R = (v cos θ / g)(v sin θ + √(v² sin²θ + 2gh)). Plot R against sin 2θ for a near-linear graph when h is small; the gradient is v²/g. Compare the angle of maximum range with 45°.
- SL and HL
- SL students plot R against sin 2θ and find v from the gradient. To reach the top band, include launch height in the model and show why the best angle is below 45°, with residuals against the model. HL can add air resistance in a numerical simulation.
- Where marks are lost
- Research design: launch speed changing with angle, or with the launch height ignored. Data analysis: only checking the maximum, with no fit. Conclusion: saying it proves 45° with no comparison of the data with the model. Evaluation: angle reading error and air resistance not discussed.
- Data
- Needs a spring launcher, carbon paper, a ruler and a protractor; the launch angle reading (about ±1°) and speed variation are the main uncertainty.
Deceleration of a rolling ball on different surfaces
Research question. How does the surface roughness, measured as the grit number of sandpaper from 60 to 400, affect the deceleration of a steel ball rolling on a horizontal board?
- A.1 Kinematics
- SL and HL
- Needs care
- Rarely listed
My take. Good as long as roughness gets a number, such as grit or a measured particle size. Twist: add a second, varied normal force by using balls of different mass, and test whether Crr is truly independent of load.
Method, physics and where marks are lost+
- Independent variable
- Surface, given by sandpaper grit: 60, 80, 120, 240, 320, 400, plus smooth board (7 values). Each is tested with 5 rolls, launched from a ramp release height that is kept fixed.
- What you measure
- Position against time of the ball, from a phone video at 240 fps, analysed frame by frame in software such as Tracker. Deceleration is the gradient of a velocity against time graph, taken from the same clip.
- Controlled variables
- Same ball and same release point on a ramp, so that starting speed is the same. Board levelled with a spirit level. Same length of surface in the field of view. Air temperature and humidity are not expected to change, but the same dust-free surface is used each time by replacing the sandpaper.
- Physics and graph
- For constant deceleration a, v = u − a t, so the gradient of the v against t graph gives −a. Rolling resistance force is F = Crr × m g, so a = Crr g and the coefficient can be found for each surface. Plot a against grit number, or Crr against average particle size.
- SL and HL
- SL: find a for each surface from velocity time graphs and describe how it changes with grit. Top band: convert to Crr, check that a is constant along the run, and discuss whether roughness is a suitable numerical measure. HL depth is not needed, though the energy view with rotational kinetic energy can be added.
- Where marks are lost
- Research design: surface roughness described only qualitatively, or grit numbers used with no justification. Data analysis: assuming a constant deceleration without checking it. Conclusion: overstating the pattern from small differences. Evaluation: ignoring that a ball may slip at the start, and small board tilts.
- Data
- Needs a ramp, steel ball, sandpaper of various grits, a phone at high frame rate and free tracking software; the main uncertainty is a small tilt of the board.
Does measured g depend on release height?
Research question. How does the release height of a steel ball, from 0.40 m to 2.00 m in steps of 0.20 m, affect the value of g calculated from its fall time?
- A.1 Kinematics
- SL and HL
- Needs care
- Rarely listed
My take. Good if you accept that the honest answer may be no measurable dependence, and then say so with numbers. The residual analysis makes the difference between an average and a top mark.
Method, physics and where marks are lost+
- Independent variable
- Release height from 0.40 m to 2.00 m in 9 values, each repeated 5 times, measured with a metre rule or tape and a plumb line.
- What you measure
- Fall time with an electromagnet release and a trapdoor switch or light gate timer, then g = 2h/t² calculated for each height. Alternatively, video analysis at 240 fps.
- Controlled variables
- Same steel ball of one diameter and mass; same release mechanism to avoid initial speed; height measured from the bottom of the ball to the trap; room conditions unchanged.
- Physics and graph
- For constant acceleration, h = ½gt², so plot h against t² and check that the gradient is g/2 with a straight line through the origin. With drag, gapparent falls slowly with height. Plot g against h and look at residuals for a trend beyond the error bars.
- SL and HL
- An SL student can plot h against t², find g and compare with 9.81 m/s². Top band work checks the residuals and a fit with an offset, and models drag to predict the expected size of any systematic drift.
- Where marks are lost
- Research design: only 3 heights, so no meaningful trend can be seen. Data analysis: g averaged without checking for the trend, and uncertainty in t not propagated. Conclusion: claiming a dependence on height when the difference lies within the error bars.
- Data
- Needs an electromagnet timer or light gates; a steel ball's drag effect is under 0.1% at 2 m, so timing precision to 1 ms is needed to see any drift.
Golf ball flight with drag from video tracking
Research question. How does the horizontal range of a golf ball launched at angles from 15° to 60° compare with a model with no air resistance and one including quadratic drag?
- A.1 Kinematics
- SL and HL
- Needs care
- Rarely listed
My take. Only a real idea once the models and how to test them are fixed, as usually stated online it is too vague. Best done indoors with a table tennis or golf ball and a numerical model.
Method, physics and where marks are lost+
- Independent variable
- Launch angle from 15° to 60° in 5° steps, eight values, with three launches at each angle using a fixed launcher speed.
- What you measure
- Ball positions from slow motion video filmed with a phone against a metre grid, analysed with Tracker software. Calculate range and peak height, then compare with modelled values.
- Controlled variables
- Same launcher setting (a spring loaded launcher or a fixed ramp release) so the speed is measured and fixed. Same ball and same room with no draughts. Camera placed on a tripod perpendicular to the flight. Launch height kept constant.
- Physics and graph
- With no drag, R = v² sin 2θ / g. With drag, integrate numerically in a spreadsheet using a = −kv v. Plot range against angle for the data and both models, and compare the residuals.
- SL and HL
- SL can compare the data with the no-drag model and find where it fails. A top answer builds a step by step numerical model with a fitted drag constant and says how well it works. HL depth could add the Magnus effect from backspin.
- Where marks are lost
- Research design: the question is vague about which models are compared and how the launch speed is set. Data analysis: no uncertainties in the position from video and not measuring the launch speed. Evaluation: not addressing lens distortion and the camera angle.
- Data
- Needs a launcher, a phone camera at 120 fps or more, and Tracker; the main uncertainty is calibration and parallax in the video.
Launch angle and range of a golf ball from a putter or wedge
Research question. How does the launch angle θ (10°, 20°, 30°, 40°, 50°, 60°, 70°) of a golf ball fired by a spring or pendulum launcher affect its horizontal range, in m, when launched from the same height?
- A.1 Kinematics
- SL and HL
- Easy data
- Rarely listed
My take. Very standard projectile work, so it will look ordinary unless you add drag modelling or a real launch height. Personalise by using the golf ball of a sport you play and testing the model in Tracker.
Method, physics and where marks are lost+
- Independent variable
- Launch angle, 7 values from 10° to 70°, set with a protractor or an angle scale on a spring launcher. 5 shots per angle.
- What you measure
- Horizontal range from a tape measure with sand or carbon paper to mark landings, and the launch speed from video analysis in Tracker to compare with theory.
- Controlled variables
- Launch speed: same spring compression or same pendulum release height each shot. Launch height: launcher on the floor or measured above the landing level. Ball: the same golf ball, kept clean. Wind: indoors or in a still sports hall.
- Physics and graph
- With no drag and equal heights R = v² sin2θ / g. Plot R against sin2θ: a line through the origin with gradient v²/g, so v can be found and compared with the video value. The maximum should be at 45°, but drag and launch height shift the best angle a little lower, which can be explained.
- SL and HL
- SL: show R against sin2θ and identify the best angle. Top band: a launch speed check by video, drag correction, and a simulation of the trajectory with drag to explain a peak below 45°.
- Where marks are lost
- Research design: a real golf club is impossible to keep at a set speed, so the launcher is a must. Data analysis: identical repeats show spread from ball spin. Conclusion: saying the peak is at 45° without evidence of the shape. Evaluation: ignoring the height offset and drag.
- Data
- A launcher, tape measure and protractor are enough; the main uncertainty is angle setting and launch speed consistency.
Measuring g from a falling ball's impact speed
Research question. What value of g results from measuring the speed of a steel ball with a light gate after it falls from heights between 0.20 m and 1.20 m?
- A.1 Kinematics
- SL and HL
- Needs care
- Rarely listed
My take. Precise and clean but heavily used, so treat it as a test of method. Worth it only if you add a real twist, such as quantifying drag with a light ball versus a heavy one.
Method, physics and where marks are lost+
- Independent variable
- Drop height h, 6 values from 0.20 m to 1.20 m in 0.20 m steps, 5 drops each.
- What you measure
- Speed at the bottom from a light gate reading the transit time of the ball, v = d/t, using the ball diameter measured with a micrometer. g comes from the graph of v2 against h.
- Controlled variables
- Same steel ball, with its diameter and mass recorded. Release by electromagnet or a thread cut to avoid an initial push. Light gate positioned just above the floor, at the same place for all drops. Ball passes through the centre of the beam.
- Physics and graph
- Energy conservation gives 1/2 m v2 = m g h, so v2 = 2 g h. Plot v2 (y) against h (x): gradient = 2g. Air resistance makes the gradient slightly lower.
- SL and HL
- SL students get g with an uncertainty and a percentage difference from 9.81 m/s2. Higher marks come from correcting for the finite gate width (speed is the mean over the ball's diameter) and estimating the effect of drag. HL depth can include a drag model.
- Where marks are lost
- Research design: no way to release the ball without imparting speed. Data analysis: ignoring the height offset (measuring from the bottom of the ball vs the gate). Evaluation: not testing whether the systematic offset is in the intercept.
- Data
- Needs a light gate with timer, ball, clamp stand and metre rule; main uncertainty is the position of the beam and the timer resolution.
Projectile drag from tracked video trajectories
Research question. How does the frontal cross-sectional area of a light projectile (discs of diameter 2.0 to 10.0 cm, 5 values, equal mass) affect the drop in its horizontal range compared with the vacuum prediction, at a fixed launch speed of about 5 m/s?
- A.1 Kinematics
- SL and HL
- Needs care
- Rarely listed
My take. A good choice if you like video analysis and want something beyond a standard drop test. Use light discs, or the drag effect will vanish in your error bars.
Method, physics and where marks are lost+
- Independent variable
- Frontal area of a card or foam disc, from 3 to 80 cm² using 6 diameters, each launched at least 5 times.
- What you measure
- Video of each flight at 240 fps filmed with a phone against a metre scale, digitised in Tracker. The measured range is subtracted from the no-drag range calculated from the measured launch velocity, giving a range deficit in cm.
- Controlled variables
- Launch speed: use the same spring launcher compression and check the speed from the first frames. Mass: add plasticine to equalise. Launch angle: fixed with a clamped protractor. Shape and surface: same material cut to size.
- Physics and graph
- Vacuum motion has x = v cosθ t and y = v sinθ t − ½gt². Drag F ≈ ½CρAv² is expected to make the range deficit grow with A. Plot range deficit against A and test for a straight line through the origin. Its gradient links to C and ρ, which can be compared with a literature value.
- SL and HL
- SL students can plot deficit against area and comment on proportionality. To reach top band, fit a numerical model with drag in a spreadsheet and compare it to the tracked path. HL students can add the v² dependence by varying launch speed too.
- Where marks are lost
- Research design: launch speed drifts between shots and is never checked. Data analysis: deficit is a small difference of two large numbers, and its uncertainty is ignored. Evaluation: ignores that a flat disc tumbles in flight, so the drag coefficient changes.
- Data
- Needs a launcher, a phone camera and Tracker; the main uncertainty is launch speed repeatability and frame timing.
Ramp angle and the time for a block to slide down
Research question. How does the angle of an inclined plank, from 10° to 40° in steps of 5°, affect the time a wooden block takes to slide 0.80 m from rest?
- A.1 Kinematics
- SL and HL
- Easy data
- Rarely listed
My take. A safe, common set-up; to stand out, use the linearisation to extract μk and g and comment on the block not moving below about 10° if it sticks.
Method, physics and where marks are lost+
- Independent variable
- Ramp angle: 10°, 15°, 20°, 25°, 30°, 35°, 40°, set from height and length using sin θ = h/L, 5 repeats each.
- What you measure
- Time over 0.80 m measured with two light gates, or a 240 fps video; acceleration calculated from a = 2s/t².
- Controlled variables
- Block mass and contact face, the same block with the same face down. Ramp surface, wiped and dried before each set. Release position, fixed by a stop at the start. Ramp length, fixed at 1.2 m.
- Physics and graph
- a = g(sin θ − μk cos θ). Plot a against sin θ; if μk is constant the gradient is g cos-corrected. Better: plot a/cos θ against tan θ, giving gradient g and intercept −μk g. The block starts sliding only above the angle where tan θ = μs.
- SL and HL
- SL: plot a against sin θ, and find μk from the fit. Top band: linearise fully, compare g from the gradient with 9.81, and consider whether μk changes with speed. HL not needed.
- Where marks are lost
- Research design: only doing time against angle with no theory, and a range too small to see the curve. Data analysis: reaction time errors from hand timing. Evaluation: not discussing how μk varies over the surface.
- Data
- Plank, block, ruler and a stopwatch is enough but light gates or video reduce timing error; the angle from the height measurement gives ±0.3°.
Rolling acceleration on different surfaces on a ramp
Research question. How does the surface covering a 1.0 m ramp at 10° affect the acceleration of a steel ball rolling down it, using six different surfaces?
- A.1 Kinematics
- SL and HL
- Easy data
- Rarely listed
My take. Accessible but the framing is misleading: friction is needed for rolling. Make it stronger by measuring rolling resistance and using HL rotational dynamics.
Method, physics and where marks are lost+
- Independent variable
- Surface material glued on the ramp: bare wood, felt, sandpaper of two grades, carpet, and rubber mat, giving six surfaces with five runs each. Roughness described by measured rolling friction, not by an assumed coefficient.
- What you measure
- Acceleration from a = 2s/t² using a metre rule and video timing at 240 fps, or two light gates for speeds. Effective friction inferred by comparing with the ideal rolling value.
- Controlled variables
- Ramp angle: fixed with a protractor and checked with a clinometer app. Ball: the same steel ball, cleaned. Release point: the same mark, released without push. Ramp length and straightness: same rail throughout.
- Physics and graph
- For a solid sphere rolling without slipping a = (5/7) g sin θ, about 0.85 m/s² at 10°. Rolling resistance lowers this. Plot measured a for each surface against the ideal value and find the deficit, then relate to a rolling resistance coefficient.
- SL and HL
- SL: compare accelerations and explain them with the ideal value. Top band: extract rolling resistance and test the rolling condition. HL: include moment of inertia and rotational energy, from rigid body mechanics.
- Where marks are lost
- Research design: surface described as a friction coefficient that was never measured. Data analysis: five runs but no uncertainty from timing at short distances. Evaluation: not spotting that a ball needs friction to roll at all, so more friction does not mean slower.
- Data
- Ramp, ball and phone video; short run times give large timing uncertainty, so use a longer ramp or video frames.
Ruler-drop reaction time after fatiguing grip exercise
Research question. How does the reaction time, found from ruler-drop distance, change during 5 minutes of recovery after 60 seconds of gripping a hand dynamometer, tested at 0, 30, 60, 120, 180 and 300 s?
- A.1 Kinematics
- SL and HL
- Easy data
- Rarely listed
My take. Physics content is light, so I would only pick it if you tie it firmly to kinematics and uncertainty analysis. Randomised drop timing is the twist.
Method, physics and where marks are lost+
- Independent variable
- Time after fatiguing exercise: 0, 30, 60, 120, 180 and 300 s (6 values), with 10 drops per time. A resting baseline is measured on a separate day.
- What you measure
- Distance the ruler falls before it is caught, read on a 30 cm ruler. Reaction time t = √(2d/g) is calculated from it for each drop.
- Controlled variables
- Participant: one or two volunteers, same hand. Method: same ruler, dropped by the same person at random moments. Time of day: sessions done at the same hour. Exercise: same grip force, checked on a dynamometer.
- Physics and graph
- Free fall from rest gives d = ½gt², so t = √(2d/g). Plot t (y) against time after exercise (x) and fit a recovery curve, or plot d (y) against t² (x) to check that g is recovered from the gradient ×2.
- SL and HL
- SL students calculate t and compare it with the baseline. Top band work models the recovery with an exponential curve, considers the resolution of the ruler and the anticipation effect, and does a statistical comparison of the means.
- Where marks are lost
- Research design: the physics is thin and the fatigue level is not measured. Data analysis: too few drops, means without uncertainty. Evaluation: learning effect making later drops faster.
- Data
- Needs a metre rule and a hand dynamometer; the main uncertainty is anticipation and the learning effect over repeated drops.
Sail area and starting acceleration of a fan-driven trolley
Research question. How does the area of a card sail, from 50 cm² to 250 cm² in five steps, affect the initial acceleration of a low-friction trolley in a steady stream of air from a desk fan?
- A.1 Kinematics
- SL and HL
- Needs care
- Rarely listed
My take. A good choice with a trolley in place of a boat, which avoids hard-to-control water. The twist: map fan air speed across the sail plane first.
Method, physics and where marks are lost+
- Independent variable
- Sail area: 50, 100, 150, 200 and 250 cm², cut from one card sheet, 4 repeats each.
- What you measure
- Acceleration from the first 0.3 s of a 240 fps slow-motion video of the trolley beside a ruler, using s = ½at², or from the gradient of a velocity–time graph in video analysis software.
- Controlled variables
- Fan speed and distance from the sail, fixed by a mark on the bench and checked with an anemometer. Trolley mass, kept constant by adding plasticine to balance the mass of the sails. Track levelled with a spirit level. Sail height and orientation, fixed to face square-on.
- Physics and graph
- Newton's second law with drag force F ≈ ½ρCdAv², so a = F/m if mass is constant. Plot a against sail area, expecting a straight line through the origin. Note that boat wording in the source is replaced by a trolley on a track, which is more controlled than water.
- SL and HL
- SL: linear graph and comparison of the gradient with the fan wind speed. Top band: estimate the drag coefficient from the gradient and discuss uneven airflow across large sails. HL adds nothing needed.
- Where marks are lost
- Research design: mass changes with sail size, and airflow is not uniform across the fan face. Data analysis: uncertainty in acceleration from few video points. Evaluation: wind speed falls off away from the fan and no anemometer map is given.
- Data
- Needs a phone with slow motion and a dynamics track; the main uncertainty is non-uniform fan flow and friction in the wheels.
Time step size and accuracy in a projectile drag model
Research question. How does the time step, from 0.001 s to 0.5 s, change the calculated range of a projectile with quadratic air drag compared with the smallest step?
- A.1 Kinematics
- SL and HL
- Easy data
- simulation
- Rarely listed
My take. Fine as a modelling piece, but risky as a stand-alone since a simulation only checks itself. Twist: film a ping pong ball launch and fit its drag coefficient.
Method, physics and where marks are lost+
- Independent variable
- Time step in an Euler model, 6 to 8 values from 0.5 s down to 0.001 s, plus a repeat with a better method if time allows.
- What you measure
- Calculated range and maximum height from a spreadsheet or Python model; percentage difference from the smallest step result.
- Controlled variables
- Same launch speed and angle. Same drag coefficient and mass. Same gravitational field strength. Same stopping condition, ending at ground level with interpolation.
- Physics and graph
- Equations of motion with F = mg and drag F = kv2, stepped as a = F/m. For zero drag the analytic range v2 sin(2 θ)/g is the check. Plot error against time step on log-log axes; the gradient shows the order of the method.
- SL and HL
- SL: show error shrinking with step and justify a step choice. Top band: compare with real launches filmed for the drag, and fit the drag coefficient. HL: add a second method and compare convergence.
- Where marks are lost
- Research design: no real measurement to test the model. Data analysis: no error measure. Conclusion: no link to physics. Evaluation: not discussing the model's assumptions such as constant drag coefficient.
- Data
- Needs only a spreadsheet or code; without real data the investigation tests the method, not nature, so add a video measured launch.
Video analysis of a jump trajectory as projectile motion
Research question. How well does the path of a jumping animal or person's centre of mass follow a parabola, and how does the fitted launch speed change with take off angle between 30° and 70°?
- A.1 Kinematics
- SL and HL
- Needs care
- Rarely listed
My take. As written it is not measurable, and a horse is out of reach for a school lab. Use a person, a toy or a rolling ball instead, or use published video of a horse only if the scale is known. The twist is to compare the centre of mass path with the foot path.
Method, physics and where marks are lost+
- Independent variable
- Take off angle of the jumper, five or more values from 30° to 70°, from several jumps each filmed, using a small toy or a person doing standing jumps.
- What you measure
- Position of a marker on the hip filmed with a phone at 120 fps against a metre grid and tracked in Tracker. Calculate the launch speed and the vertical acceleration from the fitted parabola.
- Controlled variables
- Camera fixed on a tripod at hip height and perpendicular to the plane of motion. Same person or object and same marker position. Same take off surface and grid scale in the plane of the jump. Same frame rate and lighting.
- Physics and graph
- For projectile motion y = x tan θ − g x² / (2 v² cos² θ). Fit a parabola to y against x and extract g from the vertical motion, expecting 9.81 m s⁻². The horizontal velocity should be constant.
- SL and HL
- SL tracks the motion and shows the horizontal velocity is nearly constant and the vertical acceleration is close to g. A stronger answer compares the height and range with what the launch speed predicts, and considers energy in the jump. HL depth is not needed. I would not use a real horse as a source of data, since access is unrealistic.
- Where marks are lost
- Research design: the source idea has no measurable variable, and a real horse is not practical. Data analysis: tracking a limb rather than the centre of mass, and no uncertainty in the scale. Evaluation: perspective error from the camera not being perpendicular.
- Data
- Needs a phone, tripod and Tracker; the main uncertainty is the marker not following the centre of mass and the scale calibration.
Ideas were collected from public lists and published IA titles, merged when they are the same investigation, and rewritten from scratch. “On N sites” counts how many public lists carry the same investigation. How this list was made.
Frequently asked questions
What are good IB Physics IA ideas on kinematics?
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Good starting points with easy data that few sites list are launch angle and range of a golf ball from a putter or wedge, ramp angle and the time for a block to slide down and rolling acceleration on different surfaces on a ramp. Each one gives a straight-line graph from school equipment, which is what the Data analysis and Conclusion criteria need.
Which kinematics IA ideas are overdone?
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launch angle and range with a calibrated launcher appear on three or more public lists. They still work, but they need a twist that shows your own thinking.
Can I do a kinematics IA at SL?
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Yes. All 13 ideas on this page use physics from the SL syllabus. HL students can take the same ideas further, and each idea says how.