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.
%0 Conference Paper
%1 wirzberger2020navigate
%A Wirzberger, Maria
%A Lado, Anastasia
%A Eckerstorfer, Lisa
%A Oreshnikov, Ivan
%A Passy, Jean-Claude
%A Stock, Adrian
%A Shenhav, Amitai
%A Lieder, Falk
%B Proceedings of the 42nd Annual Conference of the Cognitive Science Society
%D 2020
%E Denison, Stephanie
%E Mack, Michael
%E Xu, Yang
%E Armstrong, Blair C.
%I Cognitive Science Society
%K attention cognition control distraction feedback myown training
%P 1736
%T How to navigate everyday distractions: Leveraging optimal feedback to train attention control
%U https://maria-wirzberger.de/wp-content/uploads/2020/07/Poster_Wirzberger_CogSci2020.pdf
%X 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.
@inproceedings{wirzberger2020navigate,
abstract = {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.},
added-at = {2020-08-16T17:44:17.000+0200},
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},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/213ebc4a8181233a87de80249e0a594eb/mariawirzberger},
booktitle = {Proceedings of the 42nd Annual Conference of the Cognitive Science Society},
editor = {Denison, Stephanie and Mack, Michael and Xu, Yang and Armstrong, Blair C.},
interhash = {8cc82162cfd50441763115ea99d70af4},
intrahash = {13ebc4a8181233a87de80249e0a594eb},
keywords = {attention cognition control distraction feedback myown training},
pages = 1736,
publisher = {Cognitive Science Society},
timestamp = {2023-10-31T09:22:45.000+0100},
title = {How to navigate everyday distractions: Leveraging optimal feedback to train attention control},
url = {https://maria-wirzberger.de/wp-content/uploads/2020/07/Poster_Wirzberger_CogSci2020.pdf},
year = 2020
}