Cognitive Therapy Abilities in People with Learning Disabilities

Background  There is a need to develop and adapt therapies for use with people with learning disabilities who have mental health problems. Aims  To examine the performance of people with learning disabilities on two cognitive therapy tasks (emotion recognition and discrimination among thoughts, feelings and behaviours). We hypothesized that cognitive therapy task performance would be significantly correlated with IQ and receptive vocabulary, and that providing a visual cue would improve performance. Method  Fifty-nine people with learning disabilities were assessed on the Wechsler Abbreviated Scale of Intelligence (WASI), the British Picture Vocabulary Scale-II (BPVS-II), a test of emotion recognition and a task requiring participants to discriminate among thoughts, feelings and behaviours. In the discrimination task, participants were randomly assigned to a visual cue condition or a no-cue condition. Results  There was considerable variability in performance. Emotion recognition was significantly associated with receptive vocabulary, and discriminating among thoughts, feelings and behaviours was significantly associated with vocabulary and IQ. There was no effect of the cue on the discrimination task. Conclusion  People with learning disabilities with higher IQs and good receptive vocabulary were more likely to be able to identify different emotions and to discriminate among thoughts, feelings and behaviours. This implies that they may more easily understand the cognitive model. Structured ways of simplifying the concepts used in cognitive therapy and methods of socialization and education in the cognitive model are required to aid participation of people with learning disabilities.

Learning CSR for sustainable corporate advantage

Corporate Social Responsibility (CSR) has become a strategic and operational reality of the business and academic world. Not that the principles of CSR are always respected or that its practice is consistently applied. Bearing in mind the multi-faceted nature of both CSR and the corporate environment, as well as the paradox of what is taught in Higher Education and what is practised within its own walls, this paper provides a learning cyclical pathway to sustainable CSR implementation and progress review. As well as highlighting the role that Higher Education has to play, the paper emphasises that in order to embed CSR within the corporate environment, questions need to be raised concerning on-going CSR improvement in order to both protect and engage a wide range of stakeholders towards sustainable corporate advantage.

Sport and re/creation: what skateboarders can teach us about learning

This paper explores the role of digital media and creativity in the processes of learning that occur in groups of urban skateboarders. In particular, it examines how the production and consumption of amateur videos contribute to both skaters’ mastery of the techniques of the sport and their integration into the culture of the sport. The data come from an ethnographic study of skateboarders in Hong Kong, which included in-depth interviews, participant observation and the collection of texts and artifacts like magazines, blog entries and amateur skating videos. Skateboarders use video in a number of ways that significantly impact their learning and integration into their communities. They use it to analyze tricks and techniques, to document the stages of their learning and socialization into the group, to set community standards, to build a sense of belonging with their ‘crews’ and to imagine ‘idealized futures’ for themselves and their communities. Understanding the value and function of such ‘semiotic mediation’ in learning and socialization into sport cultures, I suggest, can contribute to helping physical educators design tasks that integrate training in physical skills with opportunities for students to make meaning around their experiences of sport and physical education.

A 2-year follow-up study of work ability among college educators

The aim of this study was to evaluate work ability among college educators before and after an intervention at the workplace. An administrative restructuring in the workplace started to be implemented in 2005. The work ability index (WAI) was administered to 154 educators before the restructure in 2004 and to 60 educators following the restructure in 2006. A mest comparing the WAI score of the 60 educators who took part in both phases showed a trend of improving work ability (p = 0.06; mean WAI in 2004 was 41.7 and 43.3 in 2006). The results suggest that the intervention led to an improvement in psychosocial factors, which in turn positively influenced work ability. (c) 2008 Elsevier Ltd. All rights reserved.

Revealing the whiteboard to blind students: An inclusive approach to provide mediation in synchronous e-learning activities

Promoting the inclusion of students with disabilities in e-learning systems has brought many challenges for researchers and educators. The use of synchronous communication tools such as interactive whiteboards has been regarded as an obstacle for inclusive education. In this paper, we present the proposal of an inclusive approach to provide blind students with the possibility to participate in live learning sessions with whiteboard software. The approach is based on the provision of accessible textual descriptions by a live mediator. With the accessible descriptions, students are able to navigate through the elements and explore the content of the class using screen readers. The method used for this study consisted of the implementation of a software prototype within a virtual learning environment and a case study with the participation of a blind student in a live distance class. The results from the case study have shown that this approach can be very effective, and may be a starting point to provide blind students with resources they had previously been deprived from. The proof of concept implemented has shown that many further possibilities may be explored to enhance the interaction of blind users with educational content in whiteboards, and further pedagogical approaches can be investigated from this proposal. (C) 2009 Elsevier Ltd. All rights reserved.

Cross-situational learning of object-word mapping using Neural Modeling Fields

The issue of how children learn the meaning of words is fundamental to developmental psychology. The recent attempts to develop or evolve efficient communication protocols among interacting robots or Virtual agents have brought that issue to a central place in more applied research fields, such as computational linguistics and neural networks, as well. An attractive approach to learning an object-word mapping is the so-called cross-situational learning. This learning scenario is based on the intuitive notion that a learner can determine the meaning of a word by finding something in common across all observed uses of that word. Here we show how the deterministic Neural Modeling Fields (NMF) categorization mechanism can be used by the learner as an efficient algorithm to infer the correct object-word mapping. To achieve that we first reduce the original on-line learning problem to a batch learning problem where the inputs to the NMF mechanism are all possible object-word associations that Could be inferred from the cross-situational learning scenario. Since many of those associations are incorrect, they are considered as clutter or noise and discarded automatically by a clutter detector model included in our NMF implementation. With these two key ingredients - batch learning and clutter detection - the NMF mechanism was capable to infer perfectly the correct object-word mapping. (C) 2009 Elsevier Ltd. All rights reserved.

Color Segmentation using LVQ-Learning Vector Quantization

This thesis aims to present a color segmentation approach for traffic sign recognition based on LVQ neural networks. The RGB images were converted into HSV color space, and segmented using LVQ depending on the hue and saturation values of each pixel in the HSV color space. LVQ neural network was used to segment red, blue and yellow colors on the road and traffic signs to detect and recognize them. LVQ was effectively applied to 536 sampled images taken from different countries in different conditions with 89% accuracy and the execution time of each image among 31 images was calculated in between 0.726sec to 0.844sec. The method was tested in different environmental conditions and LVQ showed its capacity to reasonably segment color despite remarkable illumination differences. The results showed high robustness.

Learning in and through drama : The necessity to use multiple theoretical perspectives in order to understand how learning takes place in drama

The complexity of learning implies that learning seldom is about just one thing. It can be said that learning processes are interdisciplinary. Within educational contexts, learning is not limited to constructed school subjects. In drama education, learning is simultaneously about drama as aesthetic expression and content because drama always is about something. The mainly focus can be on form, content or social aspects. The different aspects are always present, but may be more or less foreground or the background depending on the purpose of education. How do development concerning understanding of form, content, and social interaction, interact in a learning process in drama? My research is based on the view that learning at the same time takes place as an individual, internal process and a socially situated, inter-subjective process. Can learning in drama imply learning that can be transferred between different situations, a transformative learning and if so, how? Transformative learning includes cognitive, affective and corporal and social action aspects and means that the individual's frames of reference are transformed, evolved, to become more insightful and flexible which implies a change of personality. It leads to an integrated knowledge that can be applied in different contexts.   In the paper that will be presented at the conference, theories about how we learn in drama will be discussed in relation to my empirical research concerning drama and learning.

Building a Learning Architecture : e-Learning and e-Services

With the rapid advancement of the webtechnology, more and more educationalresources, including software applications forteaching/learning methods, are available acrossthe web, which enables learners to access thelearning materials and use various ways oflearning at any time and any place. Moreover,various web-based teaching/learning approacheshave been developed during the last decade toenhance the capability of both educators andlearners. Particularly, researchers from bothcomputer science and education are workingtogether, collaboratively focusing ondevelopment of pedagogically enablingtechnologies which are believed to improve theinfrastructure of education systems andprocesses, including curriculum developmentmodels, teaching/learning methods, managementof educational resources, systematic organizationof communication and dissemination ofknowledge and skills required by and adapted tousers. Despite of its fast development, however,there are still great gaps between learningintentions, organization of supporting resources,management of educational structures,knowledge points to be learned and interknowledgepoint relationships such as prerequisites,assessment of learning outcomes, andtechnical and pedagogic approaches. Moreconcretely, the issues have been widelyaddressed in literature include a) availability andusefulness of resources, b) smooth integration ofvarious resources and their presentation, c)learners’ requirements and supposed learningoutcomes, d) automation of learning process interms of its schedule and interaction, and e)customization of the resources and agilemanagement of the learning services for deliveryas well as necessary human interferences.Considering these problems and bearing in mindthe advanced web technology of which weshould make full use, in this report we willaddress the following two aspects of systematicarchitecture of learning/teaching systems: 1)learning objects – a semantic description andorganization of learning resources using the webservice models and methods, and 2) learningservices discovery and learning goals match foreducational coordination and learning serviceplanning.

Learning Grammar : A study of upper secondary level students’ attitudes and beliefs concerning the learning of grammar

The communicative approach to language learning is widely taught in Western education, and yet its predecessor, the grammar-translation method, is still commonly employed in other parts of the world. In Sweden, the increasing popularity of the communicative approach is often justified by the high level of students’ communicative skills (Öhman, 2013). At the same time, students’ written texts and speech contain many grammatical errors (Öhman, 2013). Consequently, being aware of their tendency to produce grammatical errors, some students express beliefs regarding both the explicit and implicit learning of grammar (Sawir, 2005; Boroujeni, 2012). The objective of this thesis is to gain more knowledge regarding students’ beliefs concerning the learning of English grammar at the upper secondary level, in Sweden. With this purpose a survey was conducted in two schools in Sweden, where 49 upper-secondary English students participated. Qualitative and quantitative methods were applied to process the collected data. Despite some difference in the participants’ ages, there were many similarities in their attitudes towards the teaching and learning of grammar. The results show that the participants in both schools believe that only by applying both, explicit and implicit methods, can they obtain a high level of language proficiency. The results of this study can help teachers in planning different activities that enhance the students’ knowledge of grammar.

Prediction Of Hydrological Models’ Uncertainty By A Committee Of Machine Learning-Models

This study presents an approach to combine uncertainties of the hydrological model outputs predicted from a number of machine learning models. The machine learning based uncertainty prediction approach is very useful for estimation of hydrological models' uncertainty in particular hydro-metrological situation in real-time application [1]. In this approach the hydrological model realizations from Monte Carlo simulations are used to build different machine learning uncertainty models to predict uncertainty (quantiles of pdf) of the a deterministic output from hydrological model . Uncertainty models are trained using antecedent precipitation and streamflows as inputs. The trained models are then employed to predict the model output uncertainty which is specific for the new input data. We used three machine learning models namely artificial neural networks, model tree, locally weighted regression to predict output uncertainties. These three models produce similar verification results, which can be improved by merging their outputs dynamically. We propose an approach to form a committee of the three models to combine their outputs. The approach is applied to estimate uncertainty of streamflows simulation from a conceptual hydrological model in the Brue catchment in UK and the Bagmati catchment in Nepal. The verification results show that merged output is better than an individual model output. [1] D. L. Shrestha, N. Kayastha, and D. P. Solomatine, and R. Price. Encapsulation of parameteric uncertainty statistics by various predictive machine learning models: MLUE method, Journal of Hydroinformatic, in press, 2013.

Desafios para a implementação do Programa PRONATEC/OSASCO sem miséria : proposta de Plano de Ação para a Secretaria Municipal de Desenvolvimento: trabalho e inclusão

O presente trabalho objetivou identificar as principais causas dos baixos índices de resposta e adesão do público-alvo e alto índice de evasão dos alunos do Programa Nacional de Acesso ao Ensino Técnico e Emprego (PRONATEC) no âmbito do Programa Brasil Sem Miséria em Osasco. Para tanto, foi realizada pesquisa quantitativa por meio de questionários aplicados a 90 participantes no momento da pré-matrícula; e pesquisa qualitativa baseada em entrevistas semiestruturadas e grupos focais realizados com 122 pessoas ligadas diretamente ao Programa: gestores municipais envolvidos em sua implementação, gestores e educadores das instituições que ofertam os cursos, alunos matriculados, evadidos e pessoas que foram convocadas a participar, mas não responderam ao convite. A partir das pesquisas, foi identificada uma lista de 27 problemas divididos em cinco eixos: Concepção da Política, Características do Público-Alvo, Divulgação do Programa, Operação do Programa e Oferta dos Cursos. Com base na priorização desses problemas, um Plano de Ação foi proposto à Secretaria de Desenvolvimento, Trabalho e Inclusão (SDTI), responsável pela execução do PRONATEC/Osasco Sem Miséria.

Avaliação de Impacto em projetos sociais do terceiro setor: uma contribuição da teoria de policy learning

Esta pesquisa analisará o aprendizado em organizações do terceiro setor a partir de dois eixos principais: 1) Aprendizado através de análises empíricas (Avaliação de Impacto) - Pretende-se entender as principais recomendações para o terceiro setor em relação a Avaliação de Impacto e qual o cenário atual dessas práticas no contexto brasileiro. Para isso, foram entrevistadas 50 instituições que fazem parte de uma rede de organizações na área de educação, para entender como a avaliação vem sendo aplicada; 2) Aprendizado através da dimensão de Policy Learning: Social Learning e Instrumental Learning – Estabelecimento de conexão de teorias de aprendizado em políticas públicas com as instituições do terceiro setor e análise de possibilidades de aprendizado através de outras experiências e boas práticas.

Algoritmo Q-learning como estratégia de exploração e/ou explotação para metaheurísticas GRASP e algoritmo genético

Techniques of optimization known as metaheuristics have achieved success in the resolution of many problems classified as NP-Hard. These methods use non deterministic approaches that reach very good solutions which, however, don t guarantee the determination of the global optimum. Beyond the inherent difficulties related to the complexity that characterizes the optimization problems, the metaheuristics still face the dilemma of xploration/exploitation, which consists of choosing between a greedy search and a wider exploration of the solution space. A way to guide such algorithms during the searching of better solutions is supplying them with more knowledge of the problem through the use of a intelligent agent, able to recognize promising regions and also identify when they should diversify the direction of the search. This way, this work proposes the use of Reinforcement Learning technique - Q-learning Algorithm - as exploration/exploitation strategy for the metaheuristics GRASP (Greedy Randomized Adaptive Search Procedure) and Genetic Algorithm. The GRASP metaheuristic uses Q-learning instead of the traditional greedy-random algorithm in the construction phase. This replacement has the purpose of improving the quality of the initial solutions that are used in the local search phase of the GRASP, and also provides for the metaheuristic an adaptive memory mechanism that allows the reuse of good previous decisions and also avoids the repetition of bad decisions. In the Genetic Algorithm, the Q-learning algorithm was used to generate an initial population of high fitness, and after a determined number of generations, where the rate of diversity of the population is less than a certain limit L, it also was applied to supply one of the parents to be used in the genetic crossover operator. Another significant change in the hybrid genetic algorithm is the proposal of a mutually interactive cooperation process between the genetic operators and the Q-learning algorithm. In this interactive/cooperative process, the Q-learning algorithm receives an additional update in the matrix of Q-values based on the current best solution of the Genetic Algorithm. The computational experiments presented in this thesis compares the results obtained with the implementation of traditional versions of GRASP metaheuristic and Genetic Algorithm, with those obtained using the proposed hybrid methods. Both algorithms had been applied successfully to the symmetrical Traveling Salesman Problem, which was modeled as a Markov decision process

ISE-SPL: Uma abordagem baseada em linha de produtos de software aplicada à geração automática de sistemas para educação médica na plataforma E-learning

E-learning, which refers to the use of Internet-related technologies to improve knowledge and learning, has emerged as a complementary form of education, bringing advantages such as increased accessibility to information, personalized learning, democratization of education and ease of update, distribution and standardization of the content. In this sense, this paper aims to develop a tool, named ISE-SPL, whose purpose is the automatic generation of E-learning systems for medical education, making use of concepts of Software Product Lines. It consists of an innovative methodology for medical education that aims to assist professors of healthcare in their teaching through the use of educational technologies, all based on computing applied to healthcare (Informatics in Health). The tests performed to validate the ISE-SPL were divided into two stages: the first was made by using a software analysis tool similar to ISE-SPL, called SPLOT and the second was performed through usability questionnaires to healthcare professors who used ISESPL. Both tests showed positive results, proving it to be an efficient tool for generation of E-learning software and useful for professors in healthcare