FuzzEG: Fuzzy logic for adaptive scenarios in an educational adventure game

NanoDoc: Designing an Adaptive Serious Game for Programming With Working Examples Support

“…The adaptive support model extends a previous method from the education game FuzzEg (Papadimitriou et al, 2019) and applies Fuzzy logic to describe student knowledge level in a domain. The process can be defined by five steps:…”

“…The formula transforms the data from a submitted solution into a positive decimal number with a maximum value of 1 which is the best possible result of a solved puzzle. The following step converts the efficiency score to fuzzy values using four membership functions (Papadimitriou et al, 2019) as depicted in Figure 5. The fuzzy set definitions enforce certain restrictions for each quadruplet.…”

“…Figure 5: Membership functions of knowledge fuzzy setsEvery puzzle of the game is associated with a specific learning domain, so the fuzzy output describes the knowledge level of the student in that domain. The knowledge level is described as a quadruplet (μUn, μUK, μK, μL) of the following fuzzy sets(Papadimitriou et al, 2019):1. Unknown (Un): The domain concept is unknown to the player.…”

Electronic Science Games Used to Enhance Cognitive Ability: Opinion of Design From Personalization and Adaptation

“…From the perspective of personalization, some researchers allow game players to choose roles, scenes or personalized cognitive training tasks according to their own preferences to achieve personalized game design (Reategui et al, 2006 ; Wei, 2009 ; Hollingdale and Greitemeyer, 2013 ; Lin et al, 2013 ; Li et al, 2016 ; Nagle et al, 2016 ; Orji et al, 2017 ; Orji and Moffatt, 2018 ; Soares et al, 2018 ; Waltemate et al, 2018 ; Zibrek et al, 2018 ; González et al, 2019 ; Knutas et al, 2019 ; Troussas et al, 2019 ). There are also some researchers from the adaptive point of view, by dynamically changing the parameters in the game, automatically adapting to the player's game difficulty, dynamically generating new content and other methods to achieve the adaptive design of the game (Carro et al, 2002 ; Hunicke, 2005 ; Togelius et al, 2010 ; Johnson et al, 2014 ; Li et al, 2014 ; Yannakakis and Togelius, 2015 ; Shaker et al, 2016 ; Schadenberg et al, 2017 ; Soler-Dominguez et al, 2017 ; Ashish et al, 2018 ; Lopes et al, 2018 ; Shi and Chen, 2018 ; Souza et al, 2018 ; Denisova and Cairns, 2019 ; Dey et al, 2019 ; Hendrix et al, 2019 ; Liang et al, 2019 ; Pan et al, 2019 ; Papadimitriou et al, 2019 ; Peng et al, 2019 ; Plass et al, 2019 ; Sepulveda et al, 2019 ). Relevant research showed that adding personalized design to electronic science games for improving cognitive abilities could enhance the cognitive training experience of gamers, stimulate their interest in cognitive training, and better enhance the training experience and cognition ability of gamers (Reategui et al, 2006 ; Wei, 2009 ; Hollingdale and Greitemeyer, 2013 ; Lin et al, 2013 ; Li et al, 2016 ; Nagle et al, 2016 ; Orji et al, 2017 ; Orji and Moffatt, 2018 ; Soares et al, 2018 ; Waltemate et al, 2018 ; Zibrek et al, 2018 ; González et al,…”

“…There are also some researchers from the adaptive point of view, by dynamically changing the parameters in the game, automatically adapting to the player's game difficulty, dynamically generating new content and other methods to achieve the adaptive design of the game (Carro et al, 2002 ; Hunicke, 2005 ; Togelius et al, 2010 ; Johnson et al, 2014 ; Li et al, 2014 ; Yannakakis and Togelius, 2015 ; Shaker et al, 2016 ; Schadenberg et al, 2017 ; Soler-Dominguez et al, 2017 ; Ashish et al, 2018 ; Lopes et al, 2018 ; Shi and Chen, 2018 ; Souza et al, 2018 ; Denisova and Cairns, 2019 ; Dey et al, 2019 ; Hendrix et al, 2019 ; Liang et al, 2019 ; Pan et al, 2019 ; Papadimitriou et al, 2019 ; Peng et al, 2019 ; Plass et al, 2019 ; Sepulveda et al, 2019 ). Relevant research showed that adding personalized design to electronic science games for improving cognitive abilities could enhance the cognitive training experience of gamers, stimulate their interest in cognitive training, and better enhance the training experience and cognition ability of gamers (Reategui et al, 2006 ; Wei, 2009 ; Hollingdale and Greitemeyer, 2013 ; Lin et al, 2013 ; Li et al, 2016 ; Nagle et al, 2016 ; Orji et al, 2017 ; Orji and Moffatt, 2018 ; Soares et al, 2018 ; Waltemate et al, 2018 ; Zibrek et al, 2018 ; González et al, 2019 ; Knutas et al, 2019 ; Troussas et al, 2019 ); adding adaptive design to electronic science games used to improve cognitive ability, which can match the player's level with the difficulty of the game, so that gamers can obtain the best training effect (Carro et al, 2002 ; Hunicke, 2005 ; Togelius et al, 2010 ; Johnson et al, 2014 ; Li et al, 2014 ; Yannakakis and Togelius, 2015 ; Shaker et al, 2016 ; Schadenberg et al, 2017 ; Soler-Dominguez et al, 2017 ; Ashish et al, 2018 ; Lopes et al, 2018 ; Shi and Chen,…”