About This Project

Flow, aka "the zone", is at the center of peak performance and intrinsic motivation. Despite such benefits of flow, we are far from fully understanding it. In fact, objectively identifying flow has been an issue due to the subjective nature of flow experience and expensive gadgets to measure attentional state like eye trackers. Thus, this project aims to answer the following RQ: TWE is there a quantifiable correlation between attention and flow state?

Ask the Scientists

What is the context of this research?

The term ‘flow state’, coined by M. Csikszentmihalyi, refers to one’s mental state when immersed in an activity. Colloquially called "being in the zone," flow state can "transform a previously unengaging task into that which is intrinsically motivating.” While further investigation of the nature of flow state is vital, researchers face challenges to objectively identify flow state due to 1) the subjective nature of flow experience, and 2) lack of access to quantitative neurological indicators such as EEG. Despite these challenges, recent studies have proposed an alternative to objectively measure flow state: attention. However, the high costs of such gadgets have been acting as barriers for further research on flow state.

What is the significance of this project?

According to a 10-year McKinsey study, top executives' productivity increased to 500% in flow state. Apart from increased productivity, flow state is known to boost personal development and happiness as Csikszentmihalyi claims that flow state as an essential component for personal happiness. Flow state has even been found to correlate strongly with self-transcendent experiences like awe and heightened meaningfulness in life, suggesting life-changing benefits. Thus, an easily accessible and effective model to objectively measure flow state can advance flow state research and promote its benefits. In addition, the relationship between validated attention indexes and flow state quantification may enhance our understanding of the mechanism of flow state.

What are the goals of the project?

Deep learning models and other AI algorithms will be applied to estimate selected indicators of attention (i.e., blinks, head movement, head rotation) and calculate participant attention indexes via webcam recording, while the Flow State Scale (FSS) will be used as a measure of ground truth for participants' flow state. A software prototype will be developed to store collected data, perform data visualization, and etc. Using the prototype, a behavioral attention experiment will be conducted to calculate the participants' attention index and analyze the correlation between attention and flow state. A research paper that summarizes the procedures and results of this project will be submitted. The data and code will be publicized to promote further research.