Trends in Adaptive Graphical User Interfaces in Moodle LMS Systems Through Artificial Intelligence Techniques

Despite widespread use, recent developments and the many forms of content that can be deployed on LMS platforms, virtual learning still faces several challenges to reach its full potential. One of these challenges is related to the homogeneity of the content presented and the lack of knowledge of aspects and user-specific characteristics of LMS systems. Among the current proposals, mostly from the use of learning styles, the use of Artificial Intelligence techniques, through elements and techniques of Machine Learning allow overcoming the limitations of learning styles determined statically. This paper presents, as part of a PhD thesis proposal on a Machine Learning model for GUI adaptability in LMS systems, a general analysis of the trends and proposals that have been presented regarding the adaptability of Graphical User Interfaces in Moodle LMS systems. Several databases were used, including IEEExplorer, Science Direct, Google Scholar, Journal Citation Reports, Scopus, and specific search criteria were applied to select the relevant studies. It is concluded that there really is a need to investigate adaptability and adaptivity in LMS systems from the analysis of behavior and certain criteria related to students as users of such systems.