Flow Learning

To form the emotional bond between the user and the interactive system is a very tricky issue because it is hard to capture and quantify the emotion. In addition, it is hard to ensure that the user acquires the same user experience as expected both in magnitude and category by the designer of the interactive system. To solve this problem, I came up with a framework named ‘Flow Learning’.

Flow learning is an emotion evocation framework I made based on machine learning and the flow theory. First we constructed an immersive environment. Then, we can control or influence the user’s actions and experiences. This is a cycling process of retroaction and regulation to give users the emotional experience the designers want.

To make Frame Learning framework well understood, there are briefly two questions to explain in this article.

1. how to create an immersion environment? The state of immersion is the prerequisite for any emotion evocation. If the user does not believe the illusion generated in the first place, the media is a failure.

2. How to guarantee a unified emotional experience? If we already find a way to maintain the user’s immersion state, we have to find a way to evoke the emotion designed. This is not an easy task because it is hard to construct a formula between the emotion and the input of the system and emotion is very subjective and can vary among people.

In response to the first question, we apply the ‘flow theory’.

In order to maintain a person’s flow experience, the activity needs to reach a balance between the challenges of the activity and the abilities of the participant. If the challenge is higher than the ability, the activity becomes overwhelming and generates anxiety. If the challenge is lower than the ability, it provokes boredom. Fortunately, human beings have tolerance, there is a fuzzy safe zone where the activity is not too challenging or too boring, and psychic entropies like anxiety and boredom would not occur.

Due to the special relationship between challenge and ability, Flow has been used in fields like sports and tutoring. The famous GRE test is a good example of design based on the concept of the Flow Zone.

To create an immersion environment, it needs the balance between ability (A) and challenge (C). From the user’s activities and feedbacks, the system measures the relationship between A index and C index, which is basically the slope of the fuzzy zone. Then dynamically and automatically, the system adjusts the C index based on the A index to keep the user in the flow.

But how to guarantee a specific unified emotional experience? To solve this problem, we establish a model between the features of the system and the user’s emotional experience. Take visual effects as an example, we associate different features with the image or picture. Features from the picture includes the frequency of color, the proportion of each RGB components, the symmetry exists in the picture, etc. According to the output of visualization, we could establish a feedback model with user’s feeling.

In sum, flow learning is an augmented approach that can be used to guarantee the unified emotional experience. The first part of it applies the flow theory to dynamically maintain the balance between challenge and ability in order to create an immersion experience. And then it establishes a feedback model between the features of the interactive system and user’s emotional feelings.

Flow learning can be widely used in the information world, not only applied in the field of interactive systems like video games and operating systems, but can also help improve the quality of education and marketing operation. The biggest challenge to apply this module is the selection of features of the media the user to interact with, which required the knowledge of an expert in the specific domain.