After conducting a historical review and establishing the state of the art of the various approaches regarding the design and implementation of adaptive e-learning systems-taking into consideration the characteristics of the user, in particular their learning styles and preferences in order to focus on the possibilities for personalizing the ways of utilizing learning materials and objects in a manner distinct from what e-learning systems have traditionally been, which is to say designed for the generic user, irrespective of individual knowledge and learning styles-the authors propose a system model for the classification of user interactions within an adaptive e-learning platform, and its analysis through a mechanism based on backpropagation neural networks and fuzzy logic, which allow for automatic, online identification of the learning styles of the users in a manner which is transparent for them and which can also be of great utility as a component of the architecture of adaptive e-learning systems and knowledge-management systems. Finally, conclusions and recommendations for future work are established.

After conducting the historical review and establishing the state of the art, the authors of this paper focus on the incorporation of Project Based Learning (PBL), in an adaptive e-Learning environment, a novel and emerging perspective, which allows the application of what today constitutes one of the most effective strategies for the process of teaching learning. In PBL, each project is defined as a complex task or problem of reality, for which resolution, the student must develop research activities, planning, design, development, validation, testing, etc. For the proposal of the Hybrid Architecture of the e-Learning system model, the authors use artificial intelligence techniques, which make it possible to identify the Learning Styles (LS), with the purpose of automatically assigning the projects, according to the characteristics, interests, expectations and demands of the student, who will interact with an e-Learning environment, with a high capacity of adaptation to each individual. Finally, the conclusions and recommendations of the research work are established.

The principal aim of this article is to review and reformulate the work published by Alfaro-Casas, Bridi and Fialho [1], in 1997, about the use of virtual reality immersion techniques for enhancing workers performance'. The challenge to be solved is related to the discussion about eventual advances occurring since the publication of the original work published. The strength of the achievements relies on the open dialogue established with different human cognition theories. We consider not only Humberto Maturana and Francisco Varela autopoiesis (human biological foundations theories) but also some other approaches derived from Education Sciences and Knowledge Management. The focus is on Artificial Intelligence and the use of Immersive technologies. The state of the art is established and its contributions towards the construction of knowledge are investigated, as a means for the development of formation and capacitation activities of the workforce. The methodology used is the bibliographical revision on several databases and the search of theses in the main universities. The greatest weakness of the research relies on the fact that we limited the search to documents using the English, Spanish, or Portuguese language. Some of the open immersion problems of virtual immersion are also treated.

After conducting the historical review of marketing and especially experiential marketing, which considers various types of experiences such as sensations, feelings, thoughts, actions and relationships, seeking in the consumer greater satisfaction and therefore greater effectiveness in the action of marketing, as well as establishing the state of the art of immersive technologies and their applications in marketing, the authors propose a software architecture model for hotel services, which includes the description of hardware and software elements for development and implementation. The model would make it possible to bring customers closer to experiences that are very close to reality, based on their profiles and characteristics, previously treated by a recommendation module included in the proposal, a fact that supports the decision of purchase, with a high degree of adaptation to their needs and requirements. The proposal and development of the model with attributes of originality, aims to contribute to the development and technological innovation of marketing in the hotel industry. Finally, conclusions and recommendations for future work are established.

Individual Learning Style identification is an essential aspect in the development of intelligent or adaptive e-Learning platforms. Traditional methods are based on the application of questionnaires or psychological tests, which may not be the most appropriate in all cases. The proposed model is based on the analysis of user behavior through the study of their interactions within an e-Learning platform, using a multilayer Backpropagation Neural Network and Fuzzy Logic concepts, for the preprocessing of the inputs and the categorization of the outputs.