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How to navigate everyday distractions: Leveraging optimal feedback to train attention control

2020

Conference Paper

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sf


To stay focused on their chosen tasks, people have to inhibit distractions. The underlying attention control skills can improve through reinforcement learning, which can be accelerated by giving feedback. We applied the theory of metacognitive reinforcement learning to develop a training app that gives people optimal feedback on their attention control while they are working or studying. In an eight-day field experiment with 99 participants, we investigated the effect of this training on people's productivity, sustained attention, and self-control. Compared to a control condition without feedback, we found that participants receiving optimal feedback learned to focus increasingly better (f = .08, p < .01) and achieved higher productivity scores (f = .19, p < .01) during the training. In addition, they evaluated their productivity more accurately (r = .12, p < .01). However, due to asymmetric attrition problems, these findings need to be taken with a grain of salt.

Author(s): Maria Wirzberger and Anastasia Lado and Lisa Eckerstorfer and Ivan Oreshnikov and Jean-Claude Passy and Adrian Stock and Amitai Shenhav and Falk Lieder
Year: 2020
Month: July
Day: 29

Department(s): Rationality Enhancement, Software Workshop
Research Project(s): Executive Functions Training
Bibtex Type: Conference Paper (conference)
Paper Type: Abstract

DOI: 10.13140/RG.2.2.36421.68321
Event Name: Annual Meeting of the Cognitive Science Society
Event Place: Virtual

Language: English

Links: How to navigate everyday distractions: Leveraging optimal feedback to train attention control

BibTex

@conference{WirzbergerCogSci2020,
  title = {How to navigate everyday distractions: Leveraging optimal feedback to train attention control},
  author = {Wirzberger, Maria and Lado, Anastasia and Eckerstorfer, Lisa and Oreshnikov, Ivan and Passy, Jean-Claude and Stock, Adrian and Shenhav, Amitai and Lieder, Falk},
  month = jul,
  year = {2020},
  month_numeric = {7}
}