01. Overview of the application

This application has been set up to run online listening experiments for music research. It presents questions, and typically audio stimuli, to participants, and collects their feedback.

The application consists of a backend in Django (Python), and a frontend in React (JavaScript). Upon load, the frontend makes a call to the backend's experiment endpoint. The experiment application contains actions (i.e., data to be serialized for frontend views: all actions have a corresponding frontend component), questions (i.e., texts for demographic questions or questions on musical expertise) and rules (i.e., the description of an experiment's logic). A call to experiment/slug will locate the rules associated with the slug, and return the rule's first_round. The first_round usually consists of a number of actions: an explanation of the experiment, a consent form (registered with the Participant), optionally a view to select a playlist, and will then create the Session for that experiment. Note that the first_round cannot contain any actions which require passing a result_id, as these require a Session to work.

The frontend will then request data for the next views via session/next_round, which is provided via the rules' next_round function. This typically contains a Trial or another view requesting user feedback. A Result is created for each user feedback, and its result_id is included in the response. It may also include a section id, to be loaded from the section endpoint. Once the user gives feedback, this is sent to the result/score endpoint, which registers the user's response, optionally assigns a score, and then makes another call to the rules' next_round function.

Results can either be profile type results, i.e., they are demographic information associated with a participant, and not expected to change. There is an option to avoid asking profile questions multiple times through the experiment.questions.utils.unasked_question function. Results can also be tied to a session instead, and ideally give insights into the phenomena an experiment is set up to test.

After each result, the participant may get feedback in a Score view, and at the end of the experiment, they will be presented with a Final view, which may include their final score, as well as links for sharing in social media, and a personalized link which gives them an overview of the experiments they participated in.

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