## 6 Conclusions and Future Work  
Although solutions based on AR have already become part of our everyday lives, not enough attention was paid to the accessibility of such solutions to make them available to as many users as possible. This is even more important considering the benefits of such solutions in different domains, especially in education where different serious games based on AR can be useful to many learners since they bring innovative and interesting ways of learning. To make AR-based serious games more inclusive, it is important to understand the needs of different users in AR in the context of accessibility. One approach to better understanding the needs of various users in AR is to utilize its interactive nature making it a rich source of data. Tracking user interactions in AR-based serious games can benefit all stakeholders involved in the process of creating an accessible AR for all. By analysing stored data on user activities and results, one can better understand user behaviour and user performance in AR and thus use this data to adapt the content and interaction mechanisms to the individual user. To be able to make these solutions accessible to as many people as possible, it is inevitable to include people with various disabilities and different ages in the process of designing alternative ways of interacting and perceiving the AR content. By following universal design principles, it is possible to address many accessibility barriers. However, since there is a need to address the various needs of different users, including people with disabilities and older people which are a very heterogeneous group of users, some requirements to address these needs can be conflicting. To enable flexibility in use and adaptation to an individual user, we proposed a solution that follows the previously mentioned approach of tracking user interactions. We proposed a framework for tracking user interactions to improve the accessibility of serious games based on handheld AR. The framework relies on the proposed methodology for automated collection, storage and analysis of interaction parameters in the context of accessibility. To enable the goal of improving the accessibility of AR-based serious games for an individual user, we first investigated the factors that can have an impact on accessibility and defined a data model for tracking user interaction data based on features of accessibility, serious games and AR for handheld devices. By implementing and evaluating the technological platform based on the proposed methodology and model, we showed that by tracking and analysing user interaction data, it is possible to define adaptation mechanisms that can improve accessibility and user satisfaction when using AR-based serious games. In this paper, special emphasis is placed on the evaluation of interaction mechanisms in transformation tasks in AR that were adapted for the participants in the experiment. The results showed that for the majority of participants, the assigned interaction mechanisms for transformation tasks were satisfactory. Currently, the method for calculating the interaction settings for an individual user considers selected interaction parameters (objective and subjective metrics). However, the defined data model enables tracking numerous other interaction parameters and the interaction tracking model can be easily expanded with new parameters. Therefore, the system implemented in this way is suitable for further research in the context of determining the impact of other parameters on accessibility and usability as well as defining new guidelines for the development and design of AR-based serious games. Considering the complexity of the research area in the context of the number and combination of different variables that can affect the accessibility and user experience of serious games in AR on mobile devices, for future work we propose to use more advanced inference techniques based on data such as different machine learning methods for determining how to adapt these solutions to individual users.