L’expérience d’acquisition de ressources en enseignement à la clientèle et de leur utilisation en situation clinique telle que perçue par des infirmiers ayant suivi un cours e-learning : étude qualitative descriptive

Les infirmiers doivent maintenir leurs connaissances à jour et poursuivre le développement de leurs compétences. Toutefois, dans le contexte actuel de pénurie d’infirmiers, la formation continue représente un défi pour eux. Or, le e-learning semble offrir un potentiel intéressant pour relever ce défi. Une étude qualitative basée sur la méthode des incidents critiques visait à décrire l’expérience clinique d’infirmiers (n=4) suite à un cours e-learning sur l’enseignement à la clientèle. Ce cours de 45 heures était basé sur l’approche par compétences. Des entrevues individuelles ont permis de documenter l’acquisition et l’utilisation en contexte clinique d’apprentissages effectués durant le cours. Les résultats révèlent que ce cours e-learning a permis aux infirmiers qui ont participé à l’étude (n=4) d’acquérir des ressources (connaissances et habiletés) et de les utiliser dans des situations cliniques d’enseignement à la clientèle. Les stratégies pédagogiques, qui apparaissent les plus prometteuses, à la lumière des résultats, sont la discussion de situations cliniques sur le forum de discussion « en ligne » et le projet de mise en contexte réel. En somme, le e-learning, basé sur l’approche par compétences se révèle une approche pédagogique prometteuse pour soutenir le développement des compétences des infirmiers. Mots clés : e-learning, formation continue, stratégies pédagogiques, approche par compétences

Learning and Adjustment Outcomes in Socialized and Unsocialized Newcomers : An Ex- Post-Facto Comparative Study

Les restructurations et les mutations de plus en plus nombreuses dans les entreprises font évoluer la trajectoire de carrière des employés vers un cheminement moins linéaire et amènent une multiplication des changements de rôle (Delobbe & Vandenberghe, 2000). Les organisations doivent de plus en plus se soucier de l’intégration de ces nouveaux employés afin de leur transmettre les éléments fondamentaux du fonctionnement et de la culture qu’elles privilégient. Par contre, la plupart des recherches sur la socialisation organisationnelle portent sur les « meilleures pratiques », et les résultats qui en découlent sont mixtes. Cette étude comparative cherche à déterminer si et sur quelles variables les nouveaux employés socialisés par leur entreprise diffèrent des nouveaux employés « non socialisés ». Premièrement, cette étude vise à comparer ces deux groupes sur 1) les résultantes proximales (la maîtrise du contenu de la socialisation organisationnelle et la clarté de rôle) et 2) les résultantes distales (l’engagement organisationnel affectif, la satisfaction au travail et l’intention de quitter) du processus de socialisation organisationnelle, ainsi que sur 3) les caractéristiques des réseaux sociaux d’information, en contrôlant pour la proactivité. Dans un second temps, cette étude a pour objectif d’explorer si le processus de socialisation organisationnelle (les relations entre les variables) diffère entre les nouveaux employés socialisés ou non. Cinquante-trois nouveaux employés (moins d’un an d’ancienneté) d’une grande entreprise québécoise ont participé à cette étude. L’entreprise a un programme de socialisation en place, mais son exécution est laissée à la discrétion de chaque département, créant deux catégories de nouveaux employés : ceux qui ont été socialisés par leur département, et ceux qui n’ont pas été socialisés (« non socialisés »). Les participants ont été sondés sur les stratégies proactives, les résultantes proximales et distales et les caractéristiques des réseaux sociaux d’information. Pour le premier objectif, les résultats indiquent que les nouveaux employés socialisés maîtrisent mieux le contenu de la socialisation organisationnelle que les nouveaux employés non socialisés. En ce qui a trait au deuxième objectif, des différences dans le processus de socialisation organisationnelle ont été trouvées. Pour les nouveaux employés « non socialisés », la recherche proactive d’informations et la recherche de rétroaction sont liées à certaines caractéristiques des réseaux sociaux, alors que le cadrage positif est lié à la satisfaction au travail et à l’intention de quitter, et que la clarté de rôle est liée uniquement à la satisfaction au travail. Les nouveaux employés socialisés, quant à eux, démontrent des liens entre la maîtrise du contenu de la socialisation organisationnelle et chacune des résultantes distales (l’engagement organisationnel affectif, la satisfaction au travail et l’intention de quitter). Globalement, l’intégration des nouveaux employés non socialisés serait plutôt influencée par leurs stratégies proactives, tandis que celle des nouveaux employés non socialisés serait facilitée par leur maîtrise du contenu de la socialisation organisationnelle. De façon générale, cette étude comparative offre un aperçu intéressant des nouveaux employés rarement trouvé dans les recherches portant sur les « meilleures pratiques » de la socialisation organisationnelle. Des recommandations pour la recherche et la pratique en suivent.

“When I Grow Up I Want to be a Doctor”: Promoting Atikamekw Children’s Interest for Health Professions Through a Book Collection

Introduction: Aboriginal peoples are underrepresented within the healthcare professions, and recruitment of Aboriginal students has become a priority for medical schools in Canada. Because of very low high-school completion rates among youth living on-reserve, the Université de Montréal’s Faculty of Medicine launched in 2011 the Mini-école de la santé, a program where health sciences students visit aboriginal schools. Through activities and games, students introduce children to the discovery of health professions. In 2014, the Health Library joined the project with the development of a science books collection for the school libraries and by having a librarian participate in the school visits. Description: In collaboration with the two Atikamekw elementary schools to be visited in 2014, 70 children books on science, human anatomy and the health professions were selected and purchased for each school by the Health Library. A librarian joined the health sciences students during the schools visits and the book collection was integrated in the activities organised during the day. The books were afterwards donated to the school library. Outcomes: Children, school teachers and administrators greatly appreciated the collection. The books were integrated in the library school collections or in the classrooms collections. Discussion: Quality school libraries play an important role in student learning, and access to science and health sciences books could enhance children‘s interest for the health professions. By participating in this project, the library is supporting the Health sciences faculties in achieving their goal of reaching out to Aboriginal children and making them aware that a career in health sciences is possible for them. The collaboration has been successful and will be pursued: the Health library will work with the high schools in the same Atikamekw communities to develop science book collections and the schools will be visited in 2015. A Masters in Library and Information Science student will be joining the Mini-école. Upgrading all donated collections is planned as well.

Towards Non Invasive Diagnosis of Scoliosis Using Semi-supervised Learning Approach

In this paper, a new methodology for the prediction of scoliosis curve types from non invasive acquisitions of the back surface of the trunk is proposed. One hundred and fifty-nine scoliosis patients had their back surface acquired in 3D using an optical digitizer. Each surface is then characterized by 45 local measurements of the back surface rotation. Using a semi-supervised algorithm, the classifier is trained with only 32 labeled and 58 unlabeled data. Tested on 69 new samples, the classifier succeeded in classifying correctly 87.0% of the data. After reducing the number of labeled training samples to 12, the behavior of the resulting classifier tends to be similar to the reference case where the classifier is trained only with the maximum number of available labeled data. Moreover, the addition of unlabeled data guided the classifier towards more generalizable boundaries between the classes. Those results provide a proof of feasibility for using a semi-supervised learning algorithm to train a classifier for the prediction of a scoliosis curve type, when only a few training data are labeled. This constitutes a promising clinical finding since it will allow the diagnosis and the follow-up of scoliotic deformities without exposing the patient to X-ray radiations.

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

"|mpact of trawling on sea bottom and its living communities along the inshore waters of southwest coast of India'’

Mechanized fishing started in Indian waters in mid —fifties and large-scale operation of trawl fishing began in the mid sixties by the surfeit of individual entrepreneurs. The southwest coast of India especially the coastal waters of Kerala are the most productive area in the subcontinent and the state has been in the forefront in marine fish production (Kurup, 2001a). Though the coastline of Kerala is one tenth of the coastline of India, the state occupies the foremost position in the marine fish production of the country, accounting for more than 30% of the marine fish landings (Thomas, 2000). The coastal waters of Kerala have rich and diversified fishery resources, which are prone to heavy exploitation by a unprecedently high number of fishing gears, among them, mechanized bottom trawlers with a numerical strength of 4550 (Kurup, 2001a) against the permissible number of 1145 (Kalawar, et al., 1985) are the most destructive. Trawling operations during monsoon periods in Kerala has been a subject of controversy between traditional fishermen and trawl fishers on a subject that trawl fishing destroys large amount of juveniles and young ones of fishes since this period is the major breeding season of most of the fish and prawns (John, 1996). Therefore Government of Kerala imposed a ban on bottom trawling activities from 1988 onwards for a period varying from 21-70 days, which usually commences from June 15th. Though many studies revealed that large amount of non-target groups were destroyed in the commercial trawl fishing in the Indian waters, no concerted study has been conducted so far to evaluate the real impact of bottom trawling on the sea bottom and its living communities. The present study was conducted to assess the impact of excessive bottom trawling exerted on the sea bottom habitat and its living communities, which would be useful in impressing up on the seriousness of habitat degradation and biotic devastation, enabling the concerned to adopt relevant conservation and management steps to conserve the resources for sustainable exploitation

Learning Three-Dimensional Shape Models for Sketch Recognition

Artifacts made by humans, such as items of furniture and houses, exhibit an enormous amount of variability in shape. In this paper, we concentrate on models of the shapes of objects that are made up of fixed collections of sub-parts whose dimensions and spatial arrangement exhibit variation. Our goals are: to learn these models from data and to use them for recognition. Our emphasis is on learning and recognition from three-dimensional data, to test the basic shape-modeling methodology. In this paper we also demonstrate how to use models learned in three dimensions for recognition of two-dimensional sketches of objects.

Policy gradient based Reinforcement Learning for real autonomous underwater cable tracking

This paper proposes a field application of a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot in cable tracking task. The learning system is characterized by using a direct policy search method for learning the internal state/action mapping. Policy only algorithms may suffer from long convergence times when dealing with real robotics. In order to speed up the process, the learning phase has been carried out in a simulated environment and, in a second step, the policy has been transferred and tested successfully on a real robot. Future steps plan to continue the learning process on-line while on the real robot while performing the mentioned task. We demonstrate its feasibility with real experiments on the underwater robot ICTINEU AUV

Technology Enhanced Learning Guide

Technology is changing how students learn and how we research. Perhaps you want to use technology to enhance communication or improve student support. You may want create a distance learning activity, a flexibly delivered module or indeed a whole course. You may simply want to find out where to find authoritative information, or to see what support exists for this type of work. The University is committed to delivering high quality learning and teaching, using technology where appropriate, in order to offer a distinctive Southampton educational experience. Technology Enhanced Learning (TEL), also known as e‑learning, is becoming increasingly important to students, teaching staff and the institution. This guide highlights some of the most important matters to consider. It is intended to help you to tackle the key issues that determine the success of TEL projects and to work on those projects in a considered way. Written with the input of colleagues from around the University, it prompts you to ask important questions and points you to sources of up-to-date knowledge and advice. Technology changes rapidly. This guide is about managing the work in a practical way. The University supports the use of a variety of TEL approaches for teaching and learning and colleagues are ready to offer their experience and advice. Each person has distinctive skills and specific experiences. No single person will have all the answers you are looking for. Be ready to investigate alternative approaches that suit you and your students’ needs in different ways. - Madeline Paterson, University of Southampton

Actitudes de los directivos en torno a la adopción del e-learning como herramienta de trabajo en las empresas

El desarrollo del presente documento constituye una investigación sobre las actitudes de los directivos frente a la adopción del e-learning como herramienta de trabajo en las organizaciones de Bogotá. Para ello se realizó una encuesta a 101 directivos, tomando como base el tipo de muestreo de conveniencia; esto con el objetivo de identificar sus actitudes frente al uso del e-learning y su influencia dentro de la organización. Como resultado se obtuvo que las actitudes de los directivos influencian en el uso de herramientas e-learning, así como también en las acciones que promueven su uso y en las actitudes de los empleados; por otro lado se identificó que las creencias relacionadas con la apropiación de herramientas e-learning y los factores facilitadores del uso de estas, influencian en las actitudes de los directivos. Lo anterior, corresponde a los análisis llevados a cabo a partir de los resultados contrastados con los estudios empíricos hallados y el marco teórico desarrollado.

Motivation, the Engine of Learning

This essay centers in motivation as a fundamental aspect of learning and in the double way sense that this relation must have. It defines the word “motivation” and the manner how relationship between students and teachers come about in the game of helping out or reduce motivation, and thus learning. It also defines the reason why teachers must help build up the so called “intrinsic motivation”, ending with the importance this has and how it can be achieved.

Desarrollo de un estado de la cuestión acerca de las interacciones entre el control de gestión y el aprendizaje organizacional.

Las organizaciones en la actualidad deben encontrar diferentes maneras de sobrevivir en un tiempo de rápida transformación. Uno de los mecanismos usados por las empresas para adaptarse a los cambios organizacionales son los sistemas de control de gestión, que a su vez permiten a las organizaciones hacer un seguimiento a sus procesos, para que la adaptabilidad sea efectiva. Otra variable importante para la adaptación es el aprendizaje organizacional siendo el proceso mediante el cual las organizaciones se adaptan a los cambios del entorno, tanto interno como externo de la compañía. Dado lo anterior, este proyecto se basa en la extracción de documentación soporte valido, que permita explorar las interacciones entre estos dos campos, los sistemas de control de gestión y el aprendizaje organizacional, además, analizar el impacto de estas interacciones en la perdurabilidad organizacional. ​

Improved SOM learning using simulated annealing

Self-Organizing Map (SOM) algorithm has been extensively used for analysis and classification problems. For this kind of problems, datasets become more and more large and it is necessary to speed up the SOM learning. In this paper we present an application of the Simulated Annealing (SA) procedure to the SOM learning algorithm. The goal of the algorithm is to obtain fast learning and better performance in terms of matching of input data and regularity of the obtained map. An advantage of the proposed technique is that it preserves the simplicity of the basic algorithm. Several tests, carried out on different large datasets, demonstrate the effectiveness of the proposed algorithm in comparison with the original SOM and with some of its modification introduced to speed-up the learning.

Innovative use of vodcast (Video-Podcast) to enrich learning experience in structures laboratory

Students may have difficulty in understanding some of the complex concepts which they have been taught in the general areas of science and engineering. Whilst practical work such as a laboratory based examination of the performance of structures has an important role in knowledge construction this does have some limitations. Blended learning supports different learning styles, hence further benefits knowledge building. This research involves an empirical study of how vodcasts (video-podcasts) can be used to enrich learning experience in the structural properties of materials laboratory of an undergraduate course. Students were given the opportunity of downloading and viewing the vodcasts on the theory before and after the experimental work. It is the choice of the students when (before or after, before and after) and how many times they would like to view the vodcasts. In blended learning, the combination of face-to-face teaching, vodcasts, printed materials, practical experiments, writing reports and instructors’ feedbacks benefits different learning styles of the learners. For the preparation of the practical, the students were informed about the availability of the vodcasts prior to the practical session. After the practical work, students submitted an individual laboratory report for the assessment of the structures laboratory. The data collection consisted of a questionnaire completed by the students, follow-up semi-structured interviews and the practical reports submitted by them for assessment. The results from the questionnaire were analysed quantitatively, whilst the data from the assessment reports were analysed qualitatively. The analysis shows that most of the students who have not fully grasped the theory after the practical, managed to gain the required knowledge by viewing the vodcasts. According to their feedbacks, the students felt that they have control over how to use the material and to view it as many times as they wish. Some students who have understood the theory may choose to view it once or not at all. Their understanding was demonstrated by their explanations in their reports, and was illustrated by the approach they took to explicate the results of their experimental work. The research findings are valuable to instructors who design, develop and deliver different types of blended learning, and are beneficial to learners who try different blended approaches. Recommendations were made on the role of the innovative application of vodcasts in the knowledge construction for structures laboratory and to guide future work in this area of research.

Sewage effluent clean-up reduces phosphorus but not phytoplankton in lowland chalk stream (River Kennet, UK) impacted by water mixing from adjacent canal

Information is provided on phosphorus in the River Kennet and the adjacent Kennet and Avon Canal in southern England to assess their interactions and the changes following phosphorus reductions in sewage treatment work (STW) effluent inputs. A step reduction in soluble reactive phosphorus (SRP) concentration within the effluent (5 to 13 fold) was observed from several STWs discharging to the river in the mid-2000s. This translated to over halving of SRP concentrations within the lower Kennet. Lower Kennet SRP concentrations change from being highest under base-flow to highest under storm-flow conditions. This represented a major shift from direct effluent inputs to a within-catchment source dominated system characteristic of the upper part to the catchment. Average SRP concentrations in the lower Kennet reduced over time towards the target for good water quality. Critically, there was no corresponding reduction in chlorophyll-a concentration, the waters remaining eutrophic when set against standards for lakes. Following the up gradient input of the main water and SRP source (Wilton Water), SRP concentrations in the canal reduced down gradient to below detection limits at times near its junction with the Kennet downstream. However, chlorophyll concentrations in the canal were in an order of magnitude higher than in the river. This probably resulted from long water residence times and higher temperatures promoting progressive algal and suspended sediment generations that consumed SRP. The canal acted as a point source for sediment, algae and total phosphorus to the river especially during the summer months when boat traffic disturbed the canal's bottom sediments and the locks were being regularly opened. The short-term dynamics of this transfer was complex. For the canal and the supply source at Wilton Water, conditions remained hypertrophic when set against standards for lakes even when SRP concentrations were extremely low.