Overview
Staying focused in environments filled with digital distractions is a challenge for students and professionals. Led by Falk Lieder and Maria Wirzberger, this project developed ACTrain, a desktop application designed to support attention control during real computer-based work and study tasks.
Users set a goal and a focus period, such as writing or studying. The system then identifies whether their current activity is consistent with that goal and provides feedback when they become distracted or regain focus. Its feedback system is based on computational models of self-regulation and is designed to make goal-directed behaviour more rewarding in the short term.
Key results
- Developed a desktop-based attention-training programme that can be used during everyday work and study rather than only in artificial exercises.
- Implemented model-based “optimal” feedback that rewards staying focused and returning to a chosen task after a distraction.
- Introduced a points system that links immediate feedback to progress toward a user-defined goal.
- Evaluated the system in a 12-day randomized field experiment. Participants who received the feedback displayed more focused behaviour than the control group and reported higher task motivation, productivity, and ability to resist distractions.
- The intervention improved six of eight task-specific measures, but it did not significantly improve general executive functions or participants’ overall progress toward longer-term goals.
- Related work applied the same reward-shaping principle to self-directed learning. In a controlled online study with a simplified learning task, appropriately designed rewards improved learners’ choices and learning outcomes; the approach was proposed for integration into the educational game Dawn of Civilization.
Why it matters
The project demonstrates how digital tools can support attention regulation within ordinary work and learning activities. Instead of blocking distractions, ACTrain encourages users to notice when they have left their chosen task and helps them return to it. The approach could be useful in education, professional work, and digital learning environments.
Publications and outputs
- Wirzberger, M., Lado, A., Eckerstorfer, L., Oreshnikov, I., Passy, J. C., Stock, A., Shenhav, A., & Lieder, F. (2024). Optimal feedback improves behavioral focus during self-regulated computer-based work. Scientific Reports, 14, 3134. doi:10.1038/s41598-024-53388-3
- Kukamjad, T., Pauly, R., Heindrich, L., Amo, V., & Lieder, F. (2024, May). Evaluation of Brain Point Intervention in The Dawn of Civilization. UCLA Psychology Undergraduate Research Conference. https://doi.org/10.13140/RG.2.2.11284.48008
- Pauly, R., Heindrich, L., Amo, V., & Lieder, F. (2022, June). What to learn next? Aligning gamification rewards to long-term goals using reinforcement learning. The 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM2022). https://doi.org/10.13140/RG.2.2.32661.19684
- Teo. J., Pauly, R., Heindrich, L., Amo, V., & Lieder, F. (2021, June). Leveraging AI to support the self-directed learning of disadvantaged youth in developing countries. The first Life Improvement Science Conference. https://is.mpg.de/publications/paulyteoheindrichamolieder2021lisa-leveraging
- Wirzberger, M., Lado, A., Eckerstorfer, L., Oreshnikov, I., Passy, J. C., Stock, A., Shenhav, A., & Lieder, F. (2020). How to navigate everyday distractions: Leveraging optimal feedback to train attention control. CogSci 2020. https://www.cognitivesciencesociety.org/cogsci20/papers/0380/
- Wirzberger, M., Oreshnikov, I., Passy, J., Lado, A., Shenhav, A., Lieder, F. (2020). ACTrain: Ein KI-basiertes Aufmerksamkeitstraining für die Wissensarbeit. 66th Spring Conference of the German Ergonomics Society. https://doi.org/10.13140/RG.2.2.14709.50406
