Health and psychosocial effects of flexible working hours

OBJECTIVE: To examine whether any impairments in health and social lives can be found under different kinds of flexible working hours, and whether such effects are related to specific characteristics of these working hours. METHODS: Two studies - a company based survey (N=660) and an internet survey (N=528) - have been conducted. The first one was a questionnaire study (paper and pencil) on employees working under some 'typical' kinds of different flexible working time arrangements in different companies and different occupational fields (health care, manufacturing, retail, administration, call centres). The second study was an internet-based survey, using an adaptation of the questionnaire from the first study. RESULTS: The results of both studies consistently show that high variability of working hours is associated with increased impairments in health and well-being and this is especially true if this variability is company controlled. These effects are less pronounced if variability is self-controlled; however, autonomy does not compensate the effects of variability. CONCLUSIONS: Recommendations for an appropriate design of flexible working hours should be developed in order to minimize any impairing effects on health and psychosocial well-being; these recommendations should include - besides allowing for discretion in controlling one's (flexible) working hours - that variability in flexible working hours should be kept low (or at least moderate), even if this variability is self-controlled.

Information and communication technologies in education – a web-based intelligent tutoring system on teaching and learning electrical project

Electrical activity is extremely broad and distinct, requiring by one hand, a deep knowledge on rules, regulations, materials, equipments, technical solutions and technologies and assistance in several areas, as electrical equipment, telecommunications, security and efficiency and rational use of energy, on the other hand, also requires other skills, depending on the specific projects to be implemented, being this knowledge a characteristic that belongs to the professionals with relevant experience, in terms of complexity and specific projects that were made.

A web-based intelligent tutoring system on teaching and learning electrical project

The Information and Communication Technology (ICT) provide new strategies for disseminating information and new communication models in order to change attitudes and human behaviour concerning to education. Nowadays the internet is crucial as a means of communication and information sharing. To education or tutorship will be required to use ICT, supported on the internet, to establish the communication of teacher-student and student-student, disseminating the content of the subjects, and as a way of teaching and learning process. This paper presents an intelligent tutor that aims to be a tool to support teaching and learning in the field of the electrical engineering project.

Learning objects recommendation in an adaptive educational hypermedia system

The aim of this paper is presenting the modules of the Adaptive Educational Hypermedia System PCMAT, responsible for the recommendation of learning objects. PCMAT is an online collaborative learning platform with a constructivist approach, which assesses the user’s knowledge and presents contents and activities adapted to the characteristics and learning style of students of mathematics in basic schools. The recommendation module and search and retrieval module choose the most adequate learning object, based on the user's characteristics and performance, and in this way contribute to the system’s adaptability.

Multi-apprentice learning for meta-heuristics parameter tuning in a multi agent scheduling system

The scheduling problem is considered in complexity theory as a NP-hard combinatorial optimization problem. Meta-heuristics proved to be very useful in the resolution of this class of problems. However, these techniques require parameter tuning which is a very hard task to perform. A Case-based Reasoning module is proposed in order to solve the parameter tuning problem in a Multi-Agent Scheduling System. A computational study is performed in order to evaluate the proposed CBR module performance.

A educação de adultos: um novo desafio organizacional na escola pública

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação Especialização em Administração Escolar

Self-optimizing through CBR learning

In this paper, we foresee the use of Multi-Agent Systems for supporting dynamic and distributed scheduling in Manufacturing Systems. We also envisage the use of Autonomic properties in order to reduce the complexity of managing systems and human interference. By combining Multi-Agent Systems, Autonomic Computing, and Nature Inspired Techniques we propose an approach for the resolution of dynamic scheduling problem, with Case-based Reasoning Learning capabilities. The objective is to permit a system to be able to automatically adopt/select a Meta-heuristic and respective parameterization considering scheduling characteristics. From the comparison of the obtained results with previous results, we conclude about the benefits of its use.

PCMAT, an adaptive learning platform

This paper is about PCMAT, an adaptive learning platform for Mathematics in Basic Education schools. Based on a constructivist approach, PCMAT aims at verifying how techniques from adaptive hypermedia systems can improve e-learning based systems. To achieve this goal, PCMAT includes a Pedagogical Model that contains a set of adaptation rules that influence the student-platform interaction. PCMAT was subject to a preliminary testing with students aged between 12 and 14 years old on the subject of direct proportionality. The results from this preliminary test are quite promising as they seem to demonstrate the validity of our proposal.

Adaptation model for PCMAT – Mathematics collaborative learning platform

The aim of this paper is to present an adaptation model for an Adaptive Educational Hypermedia System, PCMAT. The adaptation of the application is based on progressive self-assessment (exercises, tasks, and so on) and applies the constructivist learning theory and the learning styles theory. Our objective is the creation of a better, more adequate adaptation model that takes into account the complexities of different users.

Word learning and text organisation: an intervention case

In the present study we focus on the interaction between the acquisition of new words and text organisation. In the acquisition of new words we emphasise the acquisition of paradigmatic relations such as hyponymy, meronymy and semantic sets. We work with a group of girls attending a private school for adolescents in serious difficulties. The subjects are from disadvantaged families. Their writing skills were very poor. When asked to describe a garden, they write a short text of a single paragraph, the lexical items were generic, there were no adjectives, and all of them use mainly existential verbs. The intervention plan assumed that subjects must to be exposed to new words, working out its meaning. In presence of referents subjects were taught new words making explicit the intended relation of the new term to a term already known. In the classroom subjects were asked to write all the words they knew drawing the relationships among them. They talk about the words specifying the relation making explicit pragmatic directions like is a kind of, is a part of or are all x. After that subjects were exposed to the task of choosing perspective. The work presented in this paper accounts for significant differences in the text of the subjects before and after the intervention. While working new words subjects were organising their lexicon and learning to present a whole entity in perspective.

Condições de acessibilidade na universidade: o ponto de vista de estudantes com deficiência

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Os suportes de expressão como veículos promotores de aprendizagens no Ensino Pré-Escolar e no 1.º ciclo do Ensino Básico

Mestrado (PES II), Educação Pré-Escolar e Ensino do 1.º Ciclo do Ensino Básico, 26 de Junho de 2014, Universidade dos Açores.

Academic social network in EHES

This paper presents the foundations of an Academic Social Network (ASN) focusing the Bologna Declaration and the Bologna Process (BP) mobility issues using ontological support. An ASN will permit students to share commons academic interests, preferences and mobility paths in the European Higher Education Space (EHES). The description of the conceptual support is ontology based allowing knowledge sharing and reuse. An approach is presented by merging Academic Ontology to Support the Bologna Mobility Process with Friend of a Friend ontology. The resulting ontology supports the student mobility profile in the ASN. The strategies to make available, in the network, knowledge about mobility issues, are presented including knowledge discovery and simulation approaches to cover student's mobility scenarios for BP.

Machine Learning Algorithms at Myocardial Perfusion Imaging - a Preliminary Study

Introduction: A major focus of data mining process - especially machine learning researches - is to automatically learn to recognize complex patterns and help to take the adequate decisions strictly based on the acquired data. Since imaging techniques like MPI – Myocardial Perfusion Imaging on Nuclear Cardiology, can implicate a huge part of the daily workflow and generate gigabytes of data, there could be advantages on Computerized Analysis of data over Human Analysis: shorter time, homogeneity and consistency, automatic recording of analysis results, relatively inexpensive, etc.Objectives: The aim of this study relates with the evaluation of the efficacy of this methodology on the evaluation of MPI Stress studies and the process of decision taking concerning the continuation – or not – of the evaluation of each patient. It has been pursued has an objective to automatically classify a patient test in one of three groups: “Positive”, “Negative” and “Indeterminate”. “Positive” would directly follow to the Rest test part of the exam, the “Negative” would be directly exempted from continuation and only the “Indeterminate” group would deserve the clinician analysis, so allowing economy of clinician’s effort, increasing workflow fluidity at the technologist’s level and probably sparing time to patients. Methods: WEKA v3.6.2 open source software was used to make a comparative analysis of three WEKA algorithms (“OneR”, “J48” and “Naïve Bayes”) - on a retrospective study using the comparison with correspondent clinical results as reference, signed by nuclear cardiologist experts - on “SPECT Heart Dataset”, available on University of California – Irvine, at the Machine Learning Repository. For evaluation purposes, criteria as “Precision”, “Incorrectly Classified Instances” and “Receiver Operating Characteristics (ROC) Areas” were considered. Results: The interpretation of the data suggests that the Naïve Bayes algorithm has the best performance among the three previously selected algorithms. Conclusions: It is believed - and apparently supported by the findings - that machine learning algorithms could significantly assist, at an intermediary level, on the analysis of scintigraphic data obtained on MPI, namely after Stress acquisition, so eventually increasing efficiency of the entire system and potentially easing both roles of Technologists and Nuclear Cardiologists. In the actual continuation of this study, it is planned to use more patient information and significantly increase the population under study, in order to allow improving system accuracy.