Open University of Catalonia

About: Open University of Catalonia is a education organization based out in Barcelona, Spain. It is known for research contribution in the topics: Collaborative learning & Educational technology. The organization has 1943 authors who have published 4646 publications receiving 64200 citations. The organization is also known as: Universitat Oberta de Catalunya & UOC.

La utilización de las nuevas tecnologías de la información y la comunicación en psicología clínica

Abstract: The use of new technologies has experienced an important increment in the last years. The purpose of promoting the development and the use of these systems in different areas is to provide benefits to the population in any life area. Specifically, in Psychology these information and communication technologies (ICT) have been applied in different fields (experimental psychology, education psychology, social psychology, psychological assessment and clinical psychology). The present work describes some of these ICT technologies used by our research group which are reaching a high applicability in Clinical Psychology. These techniques are Virtual Reality, Augmented Reality and Internet-based Telepsychology. In addition, this work stands out the advantages of these systems in comparison to traditional therapy and some of the existing limitations. Finally, future perspectives in Clinical Psychology with these novelty systems and its utility are described.

Evaluating deep learning EEG-based mental stress classification in adolescents with autism for breathing entrainment BCI

Abstract: Mental stress is a major individual and societal burden and one of the main contributing factors that lead to pathologies such as depression, anxiety disorders, heart attacks, and strokes. Given that anxiety disorders are one of the most common comorbidities in youth with autism spectrum disorder (ASD), this population is particularly vulnerable to mental stress, severely limiting overall quality of life. To prevent this, early stress quantification with machine learning (ML) and effective anxiety mitigation with non-pharmacological interventions are essential. This study aims to investigate the feasibility of exploiting electroencephalography (EEG) signals for stress assessment by comparing several ML classifiers, namely support vector machine (SVM) and deep learning methods. We trained a total of eleven subject-dependent models-four with conventional brain-computer interface (BCI) methods and seven with deep learning approaches-on the EEG of neurotypical (n=5) and ASD (n=8) participants performing alternating blocks of mental arithmetic stress induction, guided and unguided breathing. Our results show that a multiclass two-layer LSTM RNN deep learning classifier is capable of identifying mental stress from ongoing EEG with an overall accuracy of 93.27%. Our study is the first to successfully apply an LSTM RNN classifier to identify stress states from EEG in both ASD and neurotypical adolescents, and offers promise for an EEG-based BCI for the real-time assessment and mitigation of mental stress through a closed-loop adaptation of respiration entrainment.

A Life-long Learning Recommender System to Promote Employability

Abstract: Is my professional knowledge outdated? Do I have the skills needed for the new challenges of the society? What knowledge do I lack to qualify for a job I like? What universities can I address to get knowledge that improves my employment expectations? These are relevant questions that all employees have done in any moment of their life. In addition, when there are high rates of unemployment and job offers that keep unfilled, the answers to these questions are even more relevant. Answering such questions open new opportunities for employed and unemployed people, by allowing them to design a formative plan according to their skills and expectations. It also provides evidences to employers about the skills and knowledge of the society, making them more aware of the skills of their potential future employees. The companies also will have more knowledge to design the professional career of their employees according to the company needs and the knowledge and skills of their employees. This paper proposes a system that helps people by showing which knowledge and skills a person misses for a given job position and what university courses the person can take to acquire the required skills and knowledge. The system has been implemented as a recommender system that helps users in planning their life-long learning. The paper shows the architecture of the proposed system, a case study to explain how it works, a survey to validate its usefulness and usability and some conclusions after its first experimentation.

Firm-Specific Knowledge and Competitive Advantage: Evidence and KM Practices

Abstract: Firm-specific, idiosyncratic knowledge is increasingly being recognized as a possible source of competitive advantage in today's business world, where more traditional sources seem to become less effective, to the extent of suggesting new approaches to strategy theory and even to the theory of the firm. This is routinely confirmed by the preliminary results from an on-going study of knowledge management (KM) approaches and practices used in Spanish firms. In this study, several senior management respondents unambiguously consider firm-specific knowledge very important for their firms' competitiveness, although they recognize, not surprisingly, that general purpose knowledge is also needed and in a higher proportion. However, when the specific KM practices used are analysed, it turns out that the majority of them do not seem to be particularly well geared to firm-specific knowledge development and usage, and neither for the effectiveness of the associated learning activities and processes. This suggests what could be a fundamental mismatch between the type of knowledge involved and appropriate KM practices. In this paper we present preliminary evidence stemming from the aforementioned study, make an attempt to characterize the kind of mismatches detected, and suggest ideas for further research on the practical and theoretical implications of the results obtained. Copyright © 2008 John Wiley & Sons, Ltd.

Flow experiences in personalised e-learning environments and the role of gender and academic performance

Abstract: The successful move to a new generation of technologies that provide students with personalised e-learning environments is connected to their ability to facilitate flow experiences – through which ...