Player modeling and estimation of player experience have become very active research fields within affective computing, human computer interaction, and game artificial intelligence in recent years. For advancing our knowledge and understanding on player experience, we introduce the Platformer Experience Dataset (PED) — the first open-access game experience corpus — that contains multiple modalities of user data of Super Mario Bros players. The open-access database aims to be used for player experience capture through context based (i.e. game content), behavioral and visual recordings of platform game players. In addition, the database contains demographical data of the players and self-reported annotations of experience in two forms: ratings and ranks. PED opens up the way to desktop and console games that use video from web cameras and visual sensors and offer possibilities for holistic player experience modeling approaches that can, in turn, yield richer game personalization.
There are fifty eight volunteers participated in the recording sessions (28 male, with player age ranging from 22 to 48 years), which took place in Denmark (with participants of different ethnic backgrounds) and Greece (with mostly Greek participants). Participants played a total of 321 games (more than 6 hours of recording in total).
The dataset contains demographic information about participants' gender, age, frequency of playing games, hours spent on gameplay on a weekly basis and any previous experience with Super Mario Bros.
Players played level A and had three chances to finish it after which they were presented with a rating questionnaire which asked them to report their level of engagement, frustration and challenge in a scale between 0 to 4 (0 denoting “not at all’’, 4 meaning “extremely’’). The process was then repeated with a different game level (level B) and another rating questionnaire.
After completing these two games, players were asked to report which of the two games they preferred via a 4-alternative forced choice (4- AFC) questionnaire protocol: A over B; B over A; both equally engaging/frustrating/challenging; both equally not preferred.
Finally, players were given the option to play more pairs of games (most of them did) or quit the game.
The logged features available with the dataset are: level completion; Mario death and the cause of death; bumping into blocks and picking up bonuses as an absolute number and percentage of total; killing enemies; changing mode and time spent in small, big or fire mode; changing direction and time spent moving left, right, jumping, ducking and running; and the full trajectory of Mario as a combination of temporal events.
The dataset contains the complete video stream associated with each gameplay session.
A complete description of the database can be found in: K. Karpouzis, N. Shaker, G. Yannakakis, S. Asteriadis. The Platformer Experience Dataset, 6th Affective Computing and Intelligent Interaction (ACII 2015) Conference, Xi’an, China, 21-24 September, 2015
For further details about the development and analysis of the dataset. Please refer to:
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