Using EEG data as Dynamic Difficulty Adjustment in a serious game about plastic pollution in the oceans
DOI: https://doi.org/10.1145/3582515.3609512
By: Thomas Bjørner, Associate Professor and Head of Media Innovation & Game Research, Aalborg University. https://orcid.org/0000-0001-9071-7168
In: Bjørner, T. (2023). Using EEG data as Dynamic Difficulty Adjustment in a serious game about the plastic pollution in the oceans. In Proceedings of the 2023 ACM Conference on Information Technology for Social Good (pp. 6-15). https://doi.org/10.1145/3582515.3609512
Abstract: In this work, it is explored whether real-time EEG (Electroencephalography) can adjust the difficulty in a serious game focused on engagement, attention, and learning about plastic pollution in our oceans. Using EEG to balance the game around the players’ affective state by measuring brain activity in real-time, it is aimed to better fit the player’s skill level, enabling a stable flow state. The experimental study included 34 participants with an experimental group (n=17), and a control group (n=17). The experimental group played the game about plastic pollution in our oceans with an adaptive difficulty adjustment (DDA) based on changes in their levels of attention and calm measured by EEG. The evaluation is based on a user engagement questionnaire, structured interviews, the EEG data, and a knowledge test. The results revealed high engagement in the game from both the experimental group and the control group. However, the participants in the control group were more attentive while playing the game and scored higher on all questions in the knowledge test compared to the experimental group. In conclusion, our study cannot provide evidence for using EEG-DDA to increase engagement, attention, and learning about pollution in the oceans in a serious game. However, there are still advantages to including EEG in game-related research, and much future research is needed on how to provide optimal learning in serious games.
Keywords: Serious games, Flow, Eco-games, EEG, Dynamic Difficulty Adjustment, Engagement, Attention, Calm, Game-based Learning
Figure 2: A fish was used as the user-controlled character
Full text here: https://doi.org/10.1145/3582515.3609512
Contribution by our academic colleague, Thomas Bjørner, PhD, User Evaluations in Media Innovations and Game Research
Head of Media Innovation and Game Research (Me-Ga), Aalborg University
Associate Professor, Department of Architecture, Design and Media Technology
