Abstract
Although many people will associate games with entertainment and leisure, games can also aim more serious purposes, such as training or education. Games with such goals are called serious games. In addition, gamification means that a (serious) task is enhanced with game elements. Examples of serious games and gamification can be seen in many aspects of daily life. Loyalty programs of stores, educational games in schools, fitness wearables and their gamified applications, rehabilitation games, and so on. In this dissertation, the focus is on a specific domain in which serious games and gamification can create societal benefit, namely by using them to empower vulnerable target groups.
In the first part of this dissertation, a literature review is performed to understand the domain of serious games and gamification for vulnerable target groups. Based on this review, research gaps can be identified. Moreover, the review resulted in a taxonomy that is used throughout the dissertation to classify different games and applications.
In the following parts of the dissertation, projects addressing two different target groups and in total three vulnerabilities are discussed. The first target group is older adults, who are vulnerable in different ways. In this dissertation, safety risks for doorstep scams and health risks through malnutrition are addressed. The first vulnerability is addressed by a serious game using interactive scenarios of doorstep scams. A diet tracking system that was used to support participants in a diet trial addressed the latter vulnerability. The second target group is young adults, which is an age group with a vulnerable mental well-being. The last part of this dissertation aims to study how gamification can be used to enhance self-compassion among young adults via an online 6-weeks training program, to increase their resilience in the face of mental well-being difficulties.
Artificial Intelligence (AI) technologies can be used to personalize and adapt the experience of a game to users. Tone of voice analysis was used to influence the progression in scenarios of the serious game about doorstep scams, and it gave players the possibility to assess the assertiveness of their voice. Machine learning algorithms were used to create personalized meal recommendations that can be used to improve the user experience of the diet tracking system for older adults. These algorithms base their recommendations on information about the historical intake of users to suggest meals and to additional items during meal editing. This makes the process of registering a meal less time-consuming. Sentiment analysis is used to adapt responses of the system in an exercise from the self-compassion training program. In addition, a topic detection algorithm was designed to assign one topic from a predefined set of topics to a note by a user of the training program. With this information, users can choose different types of situations to use in the exercises: frequently or rarely discussed topics. Aside from those techniques, knowledge representation is used in all projects, which is important for serious games/gamified applications since they are often based on expert and/or domain knowledge.
This dissertation contributes to understanding the domain of serious games and gamification to empower vulnerable groups. The work also contributes to the research on the development of applications within that domain. On top of that, it contributes to understanding how AI techniques can be used to offer (personalized) features that enrich serious games or gamified applications. Finally, for each of the project centered parts, the results that are found in those parts contribute to the research in those specific fields.
Original language | English |
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Qualification | PhD |
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Award date | 29 Jun 2022 |
Print ISBNs | 9789083246864 |
Publication status | Published - 29 Jun 2022 |