The Cost of Conducting Experiments with the oTree Python Framework
The development of various online platforms such as oTree Python Framework has made running online experiments simpler, especially in the field of psychological research and cognitive tasks. However, like any scientific study, the execution of behavioural experiments using this framework can come with hidden costs. In this guide, we will navigate the costs of running experiments using oTree, the expenses of licensing, conducting experiments with a sample of 100 participants, hidden costs, and sharing valuable tips to reduce costs.
oTree License Model
Contrary to the traditional proprietary software, oTree operates on an open-source model. This signifies that access to the framework, including its installation, incorporation, and distribution, is free of charge. However, please note that although the oTree software itself is free, conducting research and running experiments might incur additional costs.
Example Cost of an Experiment with 100 Participants
Let's assume you're conducting a simple cognitive experiment with 100 participants. The direct costs will primarily arise from participant compensation, which can vary based on the demographic profile, duration of the task, and other experimental complexities. Let's say each participant is compensated $10 for their time and effort, resulting in a direct participant cost of $1000. Other expenses may include costs for promoting the study, technically setting up the experiment or funds paid to your data hosting service like Cognition.
Hidden Costs
While the license cost is out of the picture when running experiments with oTree, researchers often overlook hidden costs. They might involve data analysis and interpretation, time spent on scripting the experiment in jspsych, modifications to suit the framework, and debugging. Unanticipated issues during the deployment process can lead to additional time and cost investments.
Tips to Reduce Costs
Several measures can help reduce the cost of running online experiments. Reusing or modifying previously available scripts from resources like jspsych can significantly cut down the time and costs tied with writing scripts from scratch. Additionally, utilizing free survey tools for data collection where possible can reduce costs linked with proprietary software. Moreover, planning the experiment meticulously to avoid debugging or re-running the test due to unexpected errors is highly advantageous.
Implementing online experiments using the oTree Python Framework may seem demanding at first glance, but a strategic and planned execution can greatly reduce these challenges. By acknowledging the costs and taking measures to manage them, the mounting need to move psychological and cognitive research into the virtual sphere will be a smooth transition.