Flow and Learning in Games

Creating services to support efficient serious games development

In the field of serious games (SG), there is a clear need for supporting pedagogical authors with methodologies and tools that can support them in providing effective learning experiences. Games offer the potential to put players into a flow state, which it is argued leads to optimal performance. As pedagogical authors are not game designers who can create flow states, this project investigates how to create an automated flow experience in games and its contribution to learning.

There were two main objectives in this project: 1) to identify the subjective flow experience and its relation with learning, and 2) to automatically identify the flow experience from physiological signals in order to enable adaptation. A game prototype for learning was created with and without an adaptive tutor system and subsequently assessed in terms of flow and learning.

We found that the two game prototypes have significantly different flow in which, surprisingly, the one with the tutor has higher flow. Furthermore, we found flow improves the perceived performance, but not the actual performance.In addition we found that flow can be distinguished from boredom and frustration using a 1-s window of brainwave signals at a moderate level. This implies the possibility of real time inferencing of the player state in a consumer context and real time difficulty adaptation.


This research project is a collaborative effort between the University of Genoa (IT) and Eindhoven University of Technology, providing reference material for a future of service oriented serious game creation.


Erasmus Mundus Joint Doctorate (EMJD) in Interactive and Cognitive Environments (ICE)), which is funded via the Education, Audiovisual and Culture Executive Agency (EACEA) of the European Commission under EMJD ICE FPA nÂș 2010-0012.

Related Publications

Pranantha, D., Luo, C., Bellotti, F., de Gloria, A. (2011). Designing Contents for a Serious Game for Learning Computer Programming with Different Target Users. In 2011th International Conference on Design and Modeling in Science, Education, and Technology (DeMSET).

Luo, C., Espinosa, AP., Pranantha, D., De Gloria, A. (2011). Multi-robot search and rescue team. Safety, Security, and Rescue Robotics (SSRR), IEEE International Symposium on , pages 296-301. 

Pranantha, D., Bellotti, F., Berta, R., and DeGloria, A. (2012). A Format of Serious Games for Higher Technology Education Topics: A Case Study in a Digital Electronic System Course. In International Conference on Advanced Learning Technologies, pages 13-17, Rome. IEEE.

Pranantha, D., Bellotti, F., Berta, R., and De Gloria, A. (2012). Puzzleit: An html5 serious games platform for education. In E-Learning and Games for Training, Education, Health and Sports, pages 134-143. Springer. 

Plotnikov, A., Stakheika, N., Schatten, C., Pranantha, D., Berta, R., and De Gloria, A. (2012). Measuring enjoyment in games through electroencephalogram (eeg) signal analysis. In 6th European Conference on Games-Based Learning (ECGBL 2012), pages 393-400. 

Berta, R., Bellotti, F., De Gloria, A., Pranantha, D., Schatten, C. (2013). Electroencephalogram and physiological signal analysis for assessing flow in games. Computational Intelligence and AI in Games, IEEE Transactions on, 5(2), 164-175. 

Ling. Y., Pranantha, D. (2013). HTML5 Serious Games Platform for Education, IEEE Technology and Engineering Education (ITEE), 8(2), pages 15-17. 

Pranantha, D., Chen, W., Bellotti, F., Van der Spek, E. D., De Gloria, A., and Rauterberg, M. (2014). Designing physics game to support inquiry learning and to promote retrieval practice. In 6th International Conference on Computer Supported Education (CSEDU). 

Pranantha, D., Spek, E. v., Bellotti, F., Berta, R., De Gloria, A., and Rauterberg, M. (2014). Game Design and Development for Learning Physics Using the Flow Framework. In 2014 Gaming and Learning Alliance (GALA) Conference