In recent years, more and more cognitive scientists have incorporated personalized and adaptive elements into the design of cognitive training games. 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., 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, 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). From the perspective of personalization and adaptability, this article systematically discusses the research status and design methods of electronic science games to enhance cognitive ability, as well as the advantages and challenges of personalized and adaptive design in electronic science games.

In recent years, a series of studies based on brain science methods have shown that electronic science games have the effect of promoting cognitive enhancement and that individual differences in game players will make them obtain different effects in cognitive training (Shang and Zhang, 2017). Therefore, in order to allow gamers to obtain the best training results, more and more researchers are beginning to design games from the perspective of personalization and adaptation, and prove the advantages of personalized and adaptive games through experiments.

In 2019, Ahmed Tlili et al. divided 51 learners into a control group and an experimental group, and they learned through the non-personalized version and the personalized version of the game, respectively (Tlili et al., 2019). The experimental results showed that personalized educational games not only reduced the cognitive burden of learners, but also allowed learners to show higher perceived usefulness and willingness to use. In the same year, Troussas et al. conducted research on personalized games and showed that integrating personalization and collaboration into mobile game learning could further help higher education students to improve their knowledge and cognition level (Troussas et al., 2019).

In 2013, Sampayo-Vargas et al. began to explore adaptive design. They compared adaptive difficulty adjustment games and non-adaptive difficulty adjustment games. The results showed that players who played adaptive games had achieved better results (Sampayo-Vargas et al., 2013).

In 2014, Montani developed a new adaptive game, and the results showed that adaptive games can improve the cognitive ability of game players (Montani et al., 2014). Recently, Daghestani et al. developed a gamification learning system that combines gamification, classification and adaptive technologies. The results showed that the adaptive gamification learning system had a positive impact on students' learning participation and academic performance (Daghestani et al., 2020).

In summary, electronic science games incorporating personalized and adaptive elements have a significant positive effect on increasing player participation, reducing the burden on players in the game, and achieving game training goals.

With the continuous development of cognitive science and the video game industry, electronic science games for cognitive enhancement have been sought after. However, how to design such games is the core issue of this research. The following will introduce how such games are designed from the perspective of personalization and adaptation.

In short, electronic science games that integrate personalization and adaptive design to improve cognitive ability can not only stimulate the interest of gamers, but also give gamers a stronger sense of substitution, and can also cultivate their concentration and execution. In terms of cognition, it has higher practicality (Guangxin and Fei, 2006).

However, there are still some problems to be solved in the personalized and adaptive design of electronic science games at this stage.

Therefore, with the continuous development of electronic science games, we need to overcome the above-mentioned challenges and contribute to their further application in cognitive enhancement. In addition, considering that Alzheimer's Disease patients have obvious cognitive decline, it is a good choice to improve their cognitive ability to use the electronic science games that embody personalization and adaptability in the future.

YZhou, DW, and WY contributed to conception and design of the study. WY, YZhon, and HC searched the database. DW, WY, YZhon, and HC performed the analysis of literatures. WY, JX, and DW wrote the first draft of the manuscript. SW, YZhon, and HC wrote sections of the manuscript. XD and MS revised this paper and analyzed the literatures. All authors contributed to manuscript revision, read, and approved the submitted version.

This work was supported in part by National Natural Science Foundation of China (61876165 and 61503326), Natural Science Foundation of Hebei Province in China (F2016203343).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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