The COVID-19 pandemic has made it necessary to adapt the methodologies used and the resources developed for face-to-face classes to support online teaching and learning overnight. This document describes the adaptation made in the context of the Operating Systems subject of the Computer Science Engineering studies at Universidad Autonoma de Madrid, to fulfill the new needs at the time of COVID-19. It includes details about the changes made regarding educational materials, communication among the different actors and evaluation approaches to fit the new requirements and engage the students. It also analyzes the results obtained by the students living this situation and compares them with those from the previous year.

This document introduces the GHIA research group, summarizes its main research areas regarding e-Learning systems and spot out some of its future work, exposing all this information within the context of the eMadrid network.

In this work, we describe an experiment on the categorization of poems based on their emotional content, which is automatically measured. For that purpose, we center on the poetry of Francisco de Quevedo and a well-known sentiment categorization of it. Thereby, we explore how emotions can help in the classification process. The goal was to verify whether the information about emotional content can be used to build classifiers reproducing that categorization.

In this work, we analyze the possible existing correlations between student marks, as assigned by their classmates or by their instructors, and the emotion traces that can be found in their writings. For that purpose, data corresponding to 168 contributions of a course on Computer Systems were gathered. The results obtained indicate that some kind of correlation exists between marks and emotions, as in the case of highest marks as at the case of lowest marks.

In this work, we analyze the possible existing correlations associated to short technical documents written by graduate students between its social acceptation, which are related to assigned classmates' marks and its emotion traces. The results obtained indicate that some kind of correlation exists between quality measure and emotions in the case of classmates' highest marks.

Affective and emotional factors seem to affect student motivation and, in general, the outcome of the learning process. By detecting and managing the emotions underlying a learning activity it would be possible to contribute to improve the student motivation and performance. In this work we explore different possibilities aimed at automatically extracting emotions from texts. We present a case study in which twelve essays written by a fresher student along her first semester in college are analyzed. Those results support the idea of using non-intrusive emotion detection for providing feedback to students. An example of use in an existing context-based adaptive e-learning system is presented. Incorporating emotions to this type of systems broadens their possibilities, allowing dynamic recommendation of activities according to the student emotions at each time, as well as emotion-based content adaptation, among others.

In the context of adaptive intelligent systems, it is essential to build user models to be considered with adaptation purposes. Personality is an interesting user feature to be incorporated in user models; it may lead to know the user needs or preferences in different situations. In this direction, eliciting user personality is needed. This information should be obtained as unobtrusively as possible, yet without compromising the reliability of the model built. In this paper, we present a method for eliciting user personality by analyzing user interactions within the social network Facebook, with the goal of mining behavioral patterns. We have developed TP2010, a Facebook application based on the ZKPQ-50-cc questionnaire, to get information about both the user personality and his interactions within Facebook. We have built a classifier model starting from the analysis of a set of data from more than 11000 users. The results show that it is feasible to get information about the user personality by analyzing data from social network interactions.

In the last years the development of learning environments, and particularly of Educational Adaptive Hypermedia (EAH) systems has increased significantly. However, it is important to complement this development with evaluation methods in order to improve EAH system performance. In this context, we propose to analyze the data from student interaction with EAH systems utilizing the GeSES method. This method has been specifically designed to work with student logs and is based on C4.5 rules. In particular, the work described in this paper aims to achieve the following two objectives: testing the method with different types of data in order to find out its reliability, and detecting symptoms of low performance in a specific adaptive learning environment, called CoMoLE.

Attention to diversity is growing concern in public secondary schools in Spain. This paper presents an assessment about the use of Adaptive Hypermedia technology for supporting diversity. Three experiences were carried out with an adaptive course on Mathematics to test the effects of this technology on the heterogeneous population of secondary schools. Their results and conclusions are also presented.

In this work we present a tool for assisting object-oriented framework instantiation based on Intelligent Agent technology. Differently from other approaches, the user is able to select the functionality needed for the new application, and based on this selection an agent elaborates a sequence of programming activities that should be carried out in order to implement it. In addition, the agent guides the execution of the activities according to the framework design. To enable this behavior, the framework need to be documented following the SmartBooks method, which extends traditional framework documentation with instantiation rules. In this paper we present an example of an instantiation environment built based on these ideas and the main characteristics of the SmartBooks method for documenting frameworks through instantiation knowledge rules.

In this work, we present an approach for documenting object-oriented application frameworks and use the documentation to guide the framework instantiation process. Our approach is based on a shift from a framework-centered to a functionality-centered documentation, through which a tool can guide the instantiation process according to the functionality required for the new application. The fundamental idea of our work is the combination of the concept of user-tasks modeling and least commitment planning methods to guide the instantiation process. Based on these techniques, the tool is able to present the different high level activities that can be carried out when creating a new application from a framework to the developer, taking as a basis the documentation provided by the designer through instantiation rules.