Calibration to Spatial Uncertainty
Practice Only With Test
Full Experiment Only
Practice and Full Experiment
Participant ID (blank for auto)

Dear Participant,

My name is Benjamin Clegg, and I am a researcher from Colorado State University in the Department of Psychology. We are conducting a research study on human decision making and are interested in how individuals arrive at the best possible decisions. The title of our project is Calibration in Understanding Uncertainty.

In this research, you will first answer a few demographic questions pertaining to your age, gender and location. You will then be presented with some information, and then asked a series of questions or be given a set of choices. You may be asked to produce an answer to a question, provide a judgment, choose an answer among several options, or rate the correctness or probability of several options. In some cases, you may be asked to read or study some material before answering questions, and you may also sometimes be given a test on your memory for the questions that you studied. If used such a test may ask you to type in what you can remember or might give you a hint to help you remember. Participation will take approximately 90 minutes. Your participation in this research is voluntary. If you decide to participate in the study, you may withdraw your consent and stop participation at any time without penalty.

Your name and any other identifying information will not be collected and your answers will remain completely confidential. Your data will added to that from other participants, and will be stored in a form such that it is entirely anonymous. Only then may it be shared within our research team. Findings may be reported to others on the aggregate data. While there are no direct benefits to you, we hope to gain more knowledge on how individuals make decisions.

There are no risks associated with this study. It is not possible to identify all potential risks in research procedures, but the researcher(s) have taken reasonable safeguards to minimize any known and potential, but unknown, risks.

If you have any questions, you may contact Benjamin Clegg at If you have any questions about your rights as a volunteer in this research, contact Colorado State University Institutional Review Board (IRB) at

Do not repeat this survey, repeats of this survey will be rejected.

Benjamin Clegg, Ph.D.
Department of Psychology
Colorado State University

If you wish to participate in this research, please click the box below. Otherwise please exit the survey.



The current project investigates how people learn about predicting movement in space. Predicting where objects will be in future states of the world is useful in many real-life situations, from forecasting weather patterns to intercepting drug smugglers.

One simple example of spatial prediction might be the prediction of the flight of a soccer ball toward the goal, when kicked from a particular location, with a particular speed, in conditions of gusty winds. If that particular kick direction and speed were repeated, because of the random and unpredictable nature of the wind gusts, the outcome would be somewhat different each time, some falling within the goal and some outside. However, over time an observer would eventually learn what the “average” trajectory of the ball would look like, as well as what the range of trajectories looks like.

In this Experiment, you will be tasked with learning the pattern of trajectories for a target object over a number of trials and asked to predict its location at a future time point. The target will follow a pattern of trajectories that includes some degree of randomness, but will start in the same location and move in a similar direction at similar speed (Note “similar” but not identical). We will refer to the position at various timepoints in the scenario as T_. For example, T0 is the position it has at the very start, T1 is the position of the target at 1 minute, and T3 is where you predict the target to be at 3 minutes. After learning the pattern of trajectories for a target, you will be asked to report the probability it will be in particular locations.

You will be completing 5 blocks of Experimental trials, with a different pattern of target behavior in each block. Each block consists of two phases.

Phase 1:
Each trial represents a new encounter with the same target, following the same pattern of behavior, but with different variability. This variability will be illustrated by the cloud of dots in the background.

For each trial, you will be shown two images representing the location of the target at two timepoints. You will be shown the start location of the target at time T0 and a possible target location following its trajectory at time T1, and you will then be asked to predict the location at time T3 using the mouse.

After selecting a location, use the slider until the shadowed circle encompasses where the target will be 75% of the time. Then, use the number entry box to make a confidence judgement for how likely it is that you have marked the correct location and made the circle encompass the likelihood the target will be within the circle 75% of the time.

After submitting you will receive feedback on where the target actually ended up going at T3 as well as a probability cloud of possible locations. Use this information to inform future decisions in the current phase and in Phase 2.

On the final 5 trials of each block, your circle size will be evaluated and compared to a simulation of 10,000 trials.

Phase 2:
In the second phase, you will be shown an area and asked to predict the probability the target at T3 is within that area as if the target was behaving as it was in phase 1. You will not receive feedback during Phase 2.


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Click in the blue area to move the circle.
Please slide this bar until the circle encompasses where the T3 location will be 75% of the time.

How confident are you that you have placed the circle so it encompasses EXACTLY 75% of the likelihood the T3 target will be within the circle?


You are now entering the actual experiment. You will no longer have access to the probability cloud on each screen, please try to form your own mental model of the likelihood cloud as you are performing the task.

Important, save file as a CSV

Phase 1:

Phase 2:

Path Settings:

Block Order: