The educational resources of an online course in logical-analytical thinking, and the results of the Index of Learning Styles Questionnaire from 17041 students were analyzed to find if the majority of learning styles is favored according to the Felder-Silverman Model. We found that while the majority of students are supported by the course, there exists a non-supported minority with predominance of verbal and global styles. A set of strategies are proposed to support these students.

Advances on Information and Communications Technology (ICT) have influenced education, and transformed the teaching-learning processes, among others aspects. It has been established that teachers' knowledge on digital media, their design and pedagogical application, is extremely relevant to improve their teaching activities. As Salinas (1997) says "teachers are essential at the time of initiating any change. Their knowledge and skills are essential for the correct operation of a program". Therefore, it is needed to extend the variety of educational experiences they can offer to students when technology is available in their environment, and it has become part of their culture. In this paper, it is discussed how important is the use of technological means as part of teaching strategies, and a teachers guide is proposed to select suitable technology for specific didactic strategies based on students learning styles.

Implementing decision-making support systems (DMSS) is considered an organizationally complex and risky task that is influenced by dynamic technical and social-political issues. Consequently, DMSS implementation failures, with associated economic loses, are still reported. While several statistics-based (static) quantitative models of successful factors and qualitative (descriptive) models to implement DMSS are available, few quantitative dynamic models have been posed. In this paper, we illustrate how a dynamic simulation model of the DMSS implementation process can be designed. We use a system dynamics approach via an extended methodology, which is called critical realism-based methodology for studying soft systems dynamics. Validation is realized through 1) the theoretical validity of the model, 2) the model's capability in reproducing historical DMSS implementation paths, and 3) the model's capability in predicting new DMSS implementation paths from new cases. Simulation results suggest the adequacy of using these modeling methods to complement the knowledge on the DMSS implementation processes.

In distance learning, the intervention of an adviser is essential for coaching the students. In this modality there are no space and time restrictions: the students have control over when and how they carry out their lectures and the adviser is responsible for responding to all their questions. Often the advisers are unable to answer immediately because of the amount and diversity of questions made by students. At all times, the students need support in order to continue learning when problems arise, but if they don't have answers right away, they wouldn 't be able to go on. This is why the advisor can benefit from a software tool that stores his experience and knowledge for reuse and quickly generates solutions to students' problems. In this paper, we describe an information system (MC) design that uses these ideas related to case-based reasoning (CBR) in order to flexibly, efficiently and immediately reply when questions are encountered by students.

Traditionally, QoS has been addressed by using network measurements (e.g., loss rates and delays), and little attention has been paid to the quality perceived by end-users of the applications running over the network. Here, we address the issue of integrating speech quality subjective scores and network parameters measurements, for designing control algorithms that would yield the best QoS that could be delivered under a given communications network situation. First, we build a neural network based automaton to measure speech quality in real time, at the style of a group of human subjects when participating in an MOS test. We consider the effects of changes in network parameters (e.g., packetization interval, packet loss rate and their pattern distribution) and encoding on speech signals transmitted over the network. Our database includes transmitted speech signals in different languages. Then, we outline a control mechanism which, based on the application performance within a session (i.e., MOS speech quality scores generated by the neural networks), dynamically adjusts parameters (codec and packetization interval). Finally, we analyze preliminary results to show two main benefits: first, a better use of bandwidth, and second, delivery of the best possible speech quality given the network current situation.