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Abstract
In educational serious games, the learning curve of a player represents his/her progress in acquiring cognitive abilities and new knowledge necessary for solving the game challenges. Hence, it is very important for an adaptive serious game to have a mechanism for detection of patterns of player´s learning curve in playing time. The paper presents the application of a game adaptation method based on automatic and dynamically detection of specific learning curves at runtime within a 3D video game of car driving in various weather conditions. The method uses a client-side software component called “Player-centric rule-and-pattern-based adaptation asset” and developed within the scope of the RAGE (Realising and Applied Gaming Ecosystem) H2020 project. The component is incorporated into a 3D car driving video game in order to enable a dynamic detection of different patterns of player performance. It allows the video game scenario to be adapted to each player by providing appropriately for him/her challenges and game features. We carried out a practical experiment with students from Sofia University, Bulgaria, where we found that adaptation of game difficulty by applying the RAGE software component resulted to improved game playability.
Original language | English |
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Title of host publication | Proceedings of the 10th Annual International Conference on Education and New Learning Technologies |
Subtitle of host publication | EDULEARN2018 |
Place of Publication | Palma de Mallorca |
Publisher | IATED Academy |
Pages | 8182-8191 |
ISBN (Electronic) | 978-84-09-02709-5 |
ISBN (Print) | 978-84-09-02709-5 |
DOIs | |
Publication status | Published - 2018 |
Externally published | Yes |
Event | EDULearn18: 10th annual International Conference on Education and New Learning Technologies - Mallorca, Palma, Spain Duration: 2 Jul 2018 → 4 Jul 2018 https://iated.org/edulearn18/ |
Conference
Conference | EDULearn18 |
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Abbreviated title | EDULearn18 |
Country/Territory | Spain |
City | Palma |
Period | 2/07/18 → 4/07/18 |
Internet address |
Keywords
- game adaptation
- player learning curve
- detection
- behaviour pattern
- game component
- RAGE
Fingerprint
Dive into the research topics of 'Dynamic game adaptation based on detection of behavioral patterns in the player learning curve'. Together they form a unique fingerprint.Projects
- 1 Finished
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Rage: Realising an Applied Gaming Eco-system
Westera, W., Georgiadis, K., Saveski, G., van Lankveld, G., Bahreini, K., van der Vegt, W., Berkhout, J., Nyamsuren, E., Kluijfhout, E. & Nadolski, R.
1/02/15 → 31/07/19
Project: Research