Development and Assessment of an E-Learning Course on Breast Imaging for Radiographers: A Stratified Randomized Controlled Trial

Background: Mammography is considered the best imaging technique for breast cancer screening, and the radiographer plays an important role in its performance. Therefore, continuing education is critical to improving the performance of these professionals and thus providing better health care services. Objective: Our goal was to develop an e-learning course on breast imaging for radiographers, assessing its efficacy , effectiveness, and user satisfaction. Methods: A stratified randomized controlled trial was performed with radiographers and radiology students who already had mammography training, using pre- and post-knowledge tests, and satisfaction questionnaires. The primary outcome was the improvement in test results (percentage of correct answers), using intention-to-treat and per-protocol analysis. Results: A total of 54 participants were assigned to the intervention (20 students plus 34 radiographers) with 53 controls (19+34). The intervention was completed by 40 participants (11+29), with 4 (2+2) discontinued interventions, and 10 (7+3) lost to follow-up. Differences in the primary outcome were found between intervention and control: 21 versus 4 percentage points (pp), P<.001. Stratified analysis showed effect in radiographers (23 pp vs 4 pp; P=.004) but was unclear in students (18 pp vs 5 pp; P=.098). Nonetheless, differences in students’ posttest results were found (88% vs 63%; P=.003), which were absent in pretest (63% vs 63%; P=.106). The per-protocol analysis showed a higher effect (26 pp vs 2 pp; P<.001), both in students (25 pp vs 3 pp; P=.004) and radiographers (27 pp vs 2 pp; P<.001). Overall, 85% were satisfied with the course, and 88% considered it successful. Conclusions: This e-learning course is effective, especially for radiographers, which highlights the need for continuing education.

O lugar da Hispanoamérica no processo de ensinoaprendizagem de Espanhol como Língua Estrangeira no Ensino Secundário Português

Tendo em conta um enfoque comunicativo experiencial (Fernández- Corbacho, 2014) e uma pedagogia crítica emancipatória (Jiménez Raya, Lamb & Vieira, 2007), enriquecida por enfoques multissensoriais (Arslan, 2009), é nossa intenção, com este projeto, contribuir para a implementação de práticas que espelhem as variedades linguísticas e culturais da Hispanoamérica (Liceras, 1995; Beave, 2000) na aula de espanhol como língua estrangeira no ensino secundário português. Neste estudo, através duma perspetiva metodológica de índole qualitativa, pretendemos, como ponto de partida, analisar: a) as representações de alunos portugueses sobre o lugar da Hispanoamérica no processo de ensino-aprendizagem de espanhol como língua estrangeira (Altmann & Vences, 2004; Pérez, 2003), através de inquéritos por questionário; e, ainda, b) as abordagens das variedades linguísticas e culturais do espanhol, que surgem nos manuais utilizados no ensino secundário português. Por outro lado, através de um estudo de caso (Benson, Chik, Gao, Huang & Wang, 2009), procurámos evidenciar uma mostra de possíveis boas práticas didático-pedagógicas e materiais, com vista a um trabalho sistemático e próativo com as variedades linguísticas e culturais do espanhol, baseado numa (hiper)pedagogia crítica e encarando a língua enquanto objeto manipulável e potenciador de cidadãos verdadeiramente conscientes do mundo. Para tal, criámos materiais físicos e digitais, que foram posteriormente implementados com alunos do 11º ano de escolaridade, no nível de iniciação de espanhol, num agrupamento de escolas da região de Aveiro. Os resultados mostram que práticas e materiais desta natureza poderão favorecer aprendizagens comunicativas experienciais, quanto à criação de futuros cidadãos críticos e ativos, fomentando o desenvolvimento das suas competências comunicativa plurilingue e pluricultural e duma consciência cultural crítica (Byram, Gribkova & Starkey, 2002) dos alunos, no contexto de ensino-aprendizagem do ensino secundário.

Learning in higher education: strategies to overcome challenges faced by adult students - lessons drawn from two studies in portugal

Int’l J. of Information and Communication Technology Education, 3(2), 1-14, April-June 2007

Adapting remote labs to learning scenarios: case studies using VISIR and RemotElectLab

Remote laboratories are an emergent technological and pedagogical tool at all education levels, and their widespread use is an important part of their own improvement and evolution. This paper describes several issues encountered on laboratorial classes, on higher education courses, when using remote laboratories based on PXI systems, either using the VISIR system or an alternate in-house solution. Three main issues are presented and explained, all reported by teachers, that gave support to students' use of remote laboratories. The first issue deals with the need to allow students to select the actual place where an ammeter is to be inserted on electric circuits, even incorrectly, therefore emulating real-world difficulties. The second one deals with problems with timing when several measurements are required at short intervals, as in the discharge cycle of a capacitor. In addition, the last issue deals with the use of a multimeter in dc mode when reading ac values, a use that collides with the lab settings. All scenarios are presented and discussed, including the solution found for each case. The conclusion derived from the described work is that the remote laboratories area is an expanding field, where practical use leads to improvement and evolution of the available solutions, requiring a strict cooperation and information-sharing between all actors, i.e., developers, teachers, and students.

Learning to manage in knowledge based organizations: the role of portfolios

Paper presented at the 8th European Conference on Knowledge Management, Barcelona, 6-7 Sep. 2008 URL: http://www.academic-conferences.org/eckm/eckm2007/eckm07-home.htm

Web survey system to discover the actual role of experience in learning in higher education: a case study

March 19 - 22, 2006, São Paulo, BRAZIL World Congress on Computer Science, Engineering and Technology Education

Learning business strategies for competitive electronic marketplaces

This paper presents a Multi-Agent Market simulator designed for developing new agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. This tool studies negotiations based on different market mechanisms and, time and behavior dependent strategies. The results of the negotiations between agents are analyzed by data mining algorithms in order to extract rules that give agents feedback to improve their strategies. The system also includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agent reactions.

Strategic bidding methodology for electricity markets using adaptive learning

The very particular characteristics of electricity markets, require deep studies of the interactions between the involved players. MASCEM is a market simulator developed to allow studying electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is implemented as a multiagent system, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. This paper also presents a methodology to define players’ models based on the historic of their past actions, interpreting how their choices are affected by past experience, and competition.

Data mining applications in power systems - case-studies and future trends

Presently power system operation produces huge volumes of data that is still treated in a very limited way. Knowledge discovery and machine learning can make use of these data resulting in relevant knowledge with very positive impact. In the context of competitive electricity markets these data is of even higher value making clear the trend to make data mining techniques application in power systems more relevant. This paper presents two cases based on real data, showing the importance of the use of data mining for supporting demand response and for supporting player strategic behavior.

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.

Managing informal learning in engineering contexts: the learners' perspective

According to recent studies, informal learning accounts for more than 75% of our continuous learning through life. However, the awareness of this learning, its benefits and its potential is still not very clear. In engineering contexts, informal learning could play an invaluable role helping students or employees to engage with peers and also with more experience colleagues, exchanging ideas and discussing problems. This work presents an initial set of results of the piloting phase of a project (TRAILER) where an innovative service based on Information & Communication Technologies was developed in order to aid the collection and visibility of informal learning. This set of results concerns engineering contexts (academic and business), from the learners' perspective. The major idea that emerged from these piloting trials was that it represented a good way of collecting, recording and sharing informal learning that otherwise could easily be forgotten. Several benefits were reported between the two communities such as being helpful in managing competences and human resources within an institution.

A tool to aid institutions recognize their employees competences acquired by informal learning

People do not learn only in formal educational institutions, but also throughout their lives, from their experiences, conversations, observations of others, exploration of the Internet, meetings and conferences, and chance encounters etc. However this informal and non-formal learning can easily remain largely invisible, making it hard for peers and employers to recognize or act upon it. The TRAILER project aims to make this learning visible so that it can benefit both the individual and the organization. The proposed demonstration will show a software solution that (i) helps the learners to capture, organize and classify a wide range of ’informal’ learning taking place in their lives, and (ii) assists the organization in recognizing this learning and use it to help managing human resources (benefiting both parts). This software tool has recently been used in two phases of pilot studies, which have run in four different European countries.

Structuring and moodleing a course: case studies at the polytechnic of Porto - School of engineering

This work presents a comparative study covering four different courses lectured at the Polytechnic of Porto - School of Engineering, in respect to the usage of a particular Learning Management System, i.e. Moodle, and its impact on students' results. Even though positive correlation factors exist, e.g. between the number of Moodle accesses versus the final exam grade obtained by each student, the explanation behind it may not be straightforward. Mapping this particular factor to course numbers reveals that the quality of the resources might be preponderant and not only their quantity. This paper also addresses teachers who used this platform as a complement to their courses (b-learning) and identifies some particular issues they should be aware in order to potentiate students' engagement and learning.

Engaging students by moodleing a course? Case studies at the Polytechnic of Porto–School of Engineering

This work presents a comparative study covering four different courses lectured at the Polytechnic of Porto - School of Engineering, regarding the usage of a particular Learning Management System, i.e. Moodle, and its impact on students' results. This study addresses teachers who used this platform as a complement to their courses (b-learning) and identifies some particular issues in order to potentiate students' engagement and learning. Even though positive correlation factors exist, e.g. between the number of Moodle accesses versus the final exam grade obtained by each student, the explanation behind it may not be straightforward. Mapping this particular factor to course numbers reveals that the quality of the resources might be preponderant and not only their quantity. These results point to the fact that some dynamic resources might enlarge students' engagement.

Using device detection techniques in M-learning scenarios

Recent studies of mobile Web trends show the continued explosion of mobile-friend content. However, the wide number and heterogeneity of mobile devices poses several challenges for Web programmers, who want automatic delivery of context and adaptation of the content to mobile devices. Hence, the device detection phase assumes an important role in this process. In this chapter, the authors compare the most used approaches for mobile device detection. Based on this study, they present an architecture for detecting and delivering uniform m-Learning content to students in a Higher School. The authors focus mainly on the XML device capabilities repository and on the REST API Web Service for dealing with device data. In the former, the authors detail the respective capabilities schema and present a new caching approach. In the latter, they present an extension of the current API for dealing with it. Finally, the authors validate their approach by presenting the overall data and statistics collected through the Google Analytics service, in order to better understand the adherence to the mobile Web interface, its evolution over time, and the main weaknesses.