%0 Conference Paper %1 oberdorfer2018effective %A Oberdörfer, Sebastian %A Latoschik, Marc Erich %B Proceedings of the 10th International Conference on Virtual Worlds and Games for Serious Applications (VS Games 2018) %D 2018 %K myown oberdoerfer %P 1-8 %R 10.1109/VS-Games.2018.8493417 %T Effective Orbital Mechanics Knowledge Training Using Game Mechanics %U https://downloads.hci.informatik.uni-wuerzburg.de/2018-vsgames-ksp-preprint.pdf %X Computer games consist of game mechanics (GMs) that encode a game's rules, principles and overall knowledge thus structuring the gameplay. These knowledge rules can also consist of information relevant to a specific learning content. This knowledge then is required and trained by periodically executing the GMs during the gameplay. Simultaneously, GMs demonstrate the encoded knowledge in an audiovisual way. Hence, GMs create learning affordances for the learning content thus requiring its application and informing about the underlying principles. However, it is still unclear how knowledge can directly be encoded and trained using GMs. Therefore, this paper analyzes the GMs used in the computer game Kerbal Space Program (KSP) to identify the encoded knowledge and to predict their training effects. Also, we report the results of a study testing the training effects of KSP when played as a regular game and when used as a specific training environment. The results indicate a highly motivating and effective knowledge training using the identified GMs.

@inproceedings{oberdorfer2018effective, abstract = {Computer games consist of game mechanics (GMs) that encode a game's rules, principles and overall knowledge thus structuring the gameplay. These knowledge rules can also consist of information relevant to a specific learning content. This knowledge then is required and trained by periodically executing the GMs during the gameplay. Simultaneously, GMs demonstrate the encoded knowledge in an audiovisual way. Hence, GMs create learning affordances for the learning content thus requiring its application and informing about the underlying principles. However, it is still unclear how knowledge can directly be encoded and trained using GMs. Therefore, this paper analyzes the GMs used in the computer game Kerbal Space Program (KSP) to identify the encoded knowledge and to predict their training effects. Also, we report the results of a study testing the training effects of KSP when played as a regular game and when used as a specific training environment. The results indicate a highly motivating and effective knowledge training using the identified GMs.}, added-at = {2018-07-10T15:16:30.000+0200}, author = {Oberdörfer, Sebastian and Latoschik, Marc Erich}, biburl = {https://www.bibsonomy.org/bibtex/28d8b6ba81bcb8ad2348985ea9caf41c5/hci-uwb}, booktitle = {Proceedings of the 10th International Conference on Virtual Worlds and Games for Serious Applications (VS Games 2018)}, doi = {10.1109/VS-Games.2018.8493417}, interhash = {67ea3212f5f867e634b45772cc737115}, intrahash = {8d8b6ba81bcb8ad2348985ea9caf41c5}, keywords = {myown oberdoerfer}, month = {September}, organization = {IEEE}, pages = {1-8}, timestamp = {2023-02-21T13:00:31.000+0100}, title = {Effective Orbital Mechanics Knowledge Training Using Game Mechanics}, url = {https://downloads.hci.informatik.uni-wuerzburg.de/2018-vsgames-ksp-preprint.pdf}, year = 2018 }