Quality of Learners' Time and Learning Performance Beyond Quantitative Time-on-Task

Peer-reviewed

Analysing Professional Discourse in Interactive Learning: Integrating Historical and Situational Perspectives

Peer-reviewed

Trabajo colaborativo en entornos e-learning y desarrollo de competencias transversales de trabajo en equipo: Análisis del caso del Máster en gestión de Proyectos en Cooperación Internacional, CSEU La Salle

Peer-reviewed

Transparent Network Interfaces to Mobile Peer-to-Peer Environment

The fact that most of new Personal Data Assistant (PDA) devices and smartphones have the ability to communicate via different wireless technologies has made several new applications possible. While traditional network model is based on the idea of static hosts, mobile devices can create decentralized, self-organizing ad-hoc networks and act as peers in the network. This kind of adapting network is suitable for mobile devices which can freely join and leave the networks. Because several different wireless communication technologies are involved, flexible changing of the networking technology must be handled in order to enable seamless communication between these networks. This thesis presents a transparent network interface to mobile Peer-to-Peer environment which is named as Virtual PeerHood. Different wireless technologies and aspects of providing a seamless connectivity between these technologies are explored. The result is a middleware platform for mobile Peer-to-Peer environment, capable of handling several networking technologies.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

PROM-OPEN: PROMOTING OPEN SCIENCE IN AN ON-LINE E-LEARNING ENVIRONMENT

Peer-reviewed

Broadening the CRM domain of application to higher educational (e-learning) environments

In this paper, we reflect about the broadening of the field of application of CRM from the business domain to a wider context of relationships in which the inclusion of non-profit making organizations seems natural. In particular, we focus on analyzing the suitability of adopting CRM processes by universities and higher educational institutions dedicated to e-learning. This is an issue that, in our opinion, has much potential but has received little attention in research so far.

Exploring new criteria to design materials for online education

Peer-reviewed

Online Learning and Teaching in Higher Education, a book review

Peer-reviewed

University teacher competences in a virtual teaching/learning environment : analysis of a teacher training experience

This paper attempts to shed light on the competencies a teacher must have inorder to teach in online university environments. We will relate a teacher trainingexperience, which was designed taking into account the methodological criteriaestablished in line with previous theoretical principles. The main objective of ouranalysis is to identify the achievements and difficulties of a specific formativeexperience, with the ultimate goal of assessing the suitability of this conceptualmethodologicalframework for the design of formative proposals aiming to contribute tothe development of teacher competencies for virtual environments.

Towards automated specifications of scenarios in enhanced learning technology

Recent standardization efforts in e-learning technology have resulted in a number of specifications, however, the automation process that is considered essential in a learning management system (LMS) is a lessexplored one. As learning technology becomes more widespread and more heterogeneous, there is a growing need to specify processes that cross the boundaries of a single LMS or learning resource repository. This article proposes to obtain a specification orientated to automation that takes on board the heterogeneity of systems and formats and provides a language for specifying complex and generic interactions. Having this goal in mind, a technique based on three steps is suggested. The semantic conformance profiles, the business process management (BPM) diagram, and its translation into the business process execution language (BPEL) seem to be suitable for achieving it.

An ontology to automated learning scenarios? an approach to its knowledge domain

Automation or semi-automation of learning scenariospecifications is one of the least exploredsubjects in the e-learning research area. There isa need for a catalogue of learning scenarios and atechnique to facilitate automated retrieval of stored specifications. This requires constructing anontology with this goal and is justified inthis paper. This ontology must mainlysupport a specification technique for learning scenarios. This ontology should also be useful in the creation and validation of new scenarios as well as in the personalization of learning scenarios or their monitoring. Thus, after justifying the need for this ontology, a first approach of a possible knowledge domain is presented. An example of a concrete learning scenario illustrates some relevant concepts supported by this ontology in order to define the scenario in such a way that it could be easy to automate.

Lifelong learning teachers' needs in virtual learning environments

Peer-reviewed