# Software Architectures for Adaptive Mobile Learning Systems: A Systematic Literature Review
## 7 Conclusions and Future Work  
This research presented an SLR on software architectures aimed at developing AMLSs. The main objectives of this SLR were to compare and identify the critical aspects of the software architectures proposed in the specialized literature for AMLS development. Based on the obtained results, we have identified various desirable requirements to be considered in the design of a reference software architecture for AMLS development: path adaptation, content adaptation, format adaptation, obtaining context, student history, student profile, administration of educational resources, administration of technological resources, usability, heterogeneity, robustness against disconnections, lightness, extensibility, modularity, and ease of testing and maintenance. The components and layered architectural styles are mainly used to support some requirements for the analyzed studies. However, none of the selected primary works consider all the identified requirements and quality attributes proposed in the specialized literature in the design of their software architecture. Few works consider the requirement of path adaptation, and no work considers the three types of adaptation in its software architecture proposal (path, content, and format). Only 45% of the proposed software architectures were evaluated in real or simulated scenarios that involved instantiating the architecture and involving students. In these cases, usability aspects were mainly evaluated concerning the adaptability services the developed AMLS provided. We note that research on usability evaluations of path adaptation servicesis limited, and no primary work reports a usability evaluation of all adaptation types (path, content, and format adaptation). The main finding of this work is the lack of a reference software architecture that considers all the requirements and quality attributes needed for developing AMLSs. This gap hinders the effective development and standardization of quality AMLSs, suggesting a critical need for a comprehensive reference software architecture. The research synthesis of this SLR has generated a knowledge base of the software architectures proposed in the specialized literature oriented toward AMLS development in terms of requirements, quality attributes, stakeholders, services provided to users, views and architectural styles, components, and implementation technologies. The results of this SLR can be used, on the one hand, by research groups that seek to identify relevant primary works and their advantages, limitations, and existing challenges, and on the other hand, as a guide for development teams that need to study the software architectures mainly used in real scenarios and identify the desirable requirements to be covered in the development of AMLSs. This study has some limitations due to the nature of the research. The search words, strings, and databases may have limited the proposed SRL in this work. The search strings were limited to terms related to AMLSs, software architectures, and adaptive learning considering three research domains: (1) mobile learning as the main research domain, (2) an adaptive learning system as a research subtopic, and (3) software architecture as a specified category. In addition, the selected databases and the inclusion and exclusion criteria may, by their nature, have excluded some primary works. Finally, primary works specifically focused on providing artificial intelligence techniques to improve only the components or mechanisms that support AMLS adaptive services or learner models in AMLSs were not reviewed. In future work, we propose to conduct a detailed analysis of the usability metrics, quality attributes, and evaluation methods applicable to content, format, and path adaptation services in AMLSs and map the use of machine learning in AMLS, elucidating the benefits and open challenges. In addition, we propose the development of a reference software architecture that considers all the desirable requirements for developing quality AMLSs.