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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 uncertainty.clegglab@gmail.com. If you have any questions about your rights as a volunteer in this research, contact Colorado State University Institutional Review Board (IRB) at RICRO_IRB@mail.colostate.edu.

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.

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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.

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In each block you will encounter a new Target type. Some targets will have a wider range of possible trajectories(Example: Target A), some will have a more narrow range of possible trajectories (Example: Target B). Your role is to learn the general pattern of trajectories within each block using the information you are given.

You will be completing 3 different blocks, in addition to a practice block.

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Phase Overview:

Each block consists of 2 phases of 12 trials each, a prediction phase and an estimation phase.

In the prediction phase you will be asked to predict the most likely location of the target at T3 and adjust a capture circle to encompass a certain percentage of the possible trajectories (you will be informed of the capture percentage value for each trial).

In the estimation phase, you will be given a capture circle and be asked to estimate the percentage of all possible trajectories that will end in that location.

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On each screen you will see a white cloud in the background. This cloud represents the probablity distribution of 10,000 possible T3 locations based on the same pattern of trajectories.

Use this distribution to help make informed decisions about where T3 will be based on any given trial.

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Prediction Phase:

For the prediction phase 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 location following its trajectory at time T1, and you will then be asked to predict the location at time T3 using the mouse.

Once you have selected a location (you can reposition until you submit), adjust the circle size to capture the displayed percentage of endpoints. Remember, the goal is to catch the EXACT percentage of endpoints being asked for ‐ NOT ALL POSSIBLE ENDPOINTS.

For example: When asked for 75% capture, you should adjust the size of the circle so that it will encompass 3 out of 4 possible trajectories from the same start point and the same pattern of trajectories.

The percentage will change between trials. In order to reduce potential carry over error, please confirm the percentage you are being asked to capture before submission.

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Prediction Phase:

Following submission you will receive feedback with the trajectory endpoint on that particular trial. Use this information to inform future decisions in the current phase and in the estimation phase.

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Estimation Phase:

In the estimation phase, you will be shown T0, T1, and 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 the prediction phase. The location and size of the capture area will change across trials. You will not receive feedback during the estimation phase. However, you will still see probability cloud.

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Estimation Phase:

You will now begin the practice block

Click next to continue or back to revisit the instructions. Once you have begun the practice block you will be unable to review the instructions.

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Your browser does not support the HTML5 canvas tag.

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




You are now entering the actual experiment.

Important, save file as a CSV

Phase 1:

Phase 2:

Path Settings:

Block Order: