Optimal feedback improves behavioral focus during self-regulated computer-based work

Author:

Wirzberger Maria,Lado Anastasia,Prentice Mike,Oreshnikov Ivan,Passy Jean-Claude,Stock Adrian,Lieder Falk

Abstract

AbstractDistractions are omnipresent and can derail our attention, which is a precious and very limited resource. To achieve their goals in the face of distractions, people need to regulate their attention, thoughts, and behavior; this is known as self-regulation. How can self-regulation be supported or strengthened in ways that are relevant for everyday work and learning activities? To address this question, we introduce and evaluate a desktop application that helps people stay focused on their work and train self-regulation at the same time. Our application lets the user set a goal for what they want to do during a defined period of focused work at their computer, then gives negative feedback when they get distracted, and positive feedback when they reorient their attention towards their goal. After this so-called focus session, the user receives overall feedback on how well they focused on their goal relative to previous sessions. While existing approaches to attention training often use artificial tasks, our approach transforms real-life challenges into opportunities for building strong attention control skills. Our results indicate that optimal attentional feedback can generate large increases in behavioral focus, task motivation, and self-control—benefitting users to successfully achieve their long-term goals.

Funder

Cyber Valley Research Fund

Universität Stuttgart

Publisher

Springer Science and Business Media LLC

Reference67 articles.

1. Berns, G. S., Laibson, D. & Loewenstein, G. Intertemporal choice-toward an integrative framework. Trends Cogn. Sci. 11, 482–488 (2007).

2. Lieder, F., Chen, O., Krueger, P. M. & Griffiths, T. L. Cognitive prostheses for goal achievement. Nat. Hum. Behav. 3, 1096–1106 (2019).

3. Shore, J. Social Media Distractions Cost U.S. Economy $650 Billion [INFOGRAPHIC]. Mashable (2012). Available at: https://mashable.com/2012/11/02/social-media-work-productivity/ (Accessed: January 20, 2020).

4. Trafton, J. G., Altmann, E. M., Brock, D. P. & Mintz, F. E. Preparing to resume an interrupted task: Effects of prospective goal encoding and retrospective rehearsal. Int. J. Hum. Comput. Stud. 58, 583–603 (2003).

5. Altmann, E. M. & Trafton, J. G. Memory for goals: An activation-based model. Cogn. Sci. 26, 39–83 (2002).

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