Diseño e implementación de 4SPPIces Tool: Una aplicación web para dar apoyo a la creación de actividades educativas colaborativas en entornos mezclados

La introducción de dispositivos tecnológicos como PDAs, móviles o portátiles, en la educación ofrece nuevas oportunidades para el aprendizaje. El uso apropiado de estas herramientas abre la posibilidad a un abanico de escenarios educativos colaborativos que no serían posibles sin la tecnología. Sin embargo, uno de los problemas principales que dificulta la adopción de estos dispositivos en entornos educativos reales es el comprender cómo aplicarlos de forma adecuada y beneficiosa para cubrir los objetivos de aprendizaje esperados. Para ello es necesario establecer vínculos entre educadores y tecnólogos para que este tipo de escenarios se puedan llevar a cabo. Por un lado, los educadores tienen conocimientos sobre prácticas educativas y, por otro lado, los tecnólogos pueden aportar con sus conocimientos acerca de las oportunidades que las tecnologías ofrecen. 4SPPIces es un modelo conceptual que tiene como objetivo establecer este puente entre las dos comunidades. Concretamente, se trata de un modelo que propone 4 factores interrelacionados que deben considerarse en el diseño de experiencias educativas colaborativas que combinen actividades dentro y fuera del aula: (1) el método pedagógico (Pedagiocal Method), (2) los participantes (Participants), (3) el espacio (Space) y (4) el historial (History). El objetivo de este proyecto es desarrollar una aplicación web para que educadores y tecnólogos colaboren en el diseño de escenarios basados en este modelo. Concretamente, este trabajo presenta el proceso de desarrollo de la aplicación así como algunas pruebas con usuarios para analizar la usabilidad y utilidad del sistema.

Organisational Values as "Attractors of Chaos": An Emerging Cultural Change to Manage Organisational Complexity

Business organisations are excellent representations of what in physics and mathematics are designated "chaotic" systems. Because a culture of innovation will be vital for organisational survival in the 21st century, the present paper proposes that viewing organisations in terms of "complexity theory" may assist leaders in fine-tuning managerial philosophies that provide orderly management emphasizing stability within a culture of organised chaos, for it is on the "boundary of chaos" that the greatest creativity occurs. It is argued that 21st century companies, as chaotic social systems, will no longer be effectively managed by rigid objectives (MBO) nor by instructions (MBI). Their capacity for self-organisation will be derived essentially from how their members accept a shared set of values or principles for action (MBV). Complexity theory deals with systems that show complex structures in time or space, often hiding simple deterministic rules. This theory holds that once these rules are found, it is possible to make effective predictions and even to control the apparent complexity. The state of chaos that self-organises, thanks to the appearance of the "strange attractor", is the ideal basis for creativity and innovation in the company. In this self-organised state of chaos, members are not confined to narrow roles, and gradually develop their capacity for differentiation and relationships, growing continuously toward their maximum potential contribution to the efficiency of the organisation. In this way, values act as organisers or "attractors" of disorder, which in the theory of chaos are equations represented by unusually regular geometric configurations that predict the long-term behaviour of complex systems. In business organisations (as in all kinds of social systems) the starting principles end up as the final principles in the long term. An attractor is a model representation of the behavioral results of a system. The attractor is not a force of attraction or a goal-oriented presence in the system; it simply depicts where the system is headed based on its rules of motion. Thus, in a culture that cultivates or shares values of autonomy, responsibility, independence, innovation, creativity, and proaction, the risk of short-term chaos is mitigated by an overall long-term sense of direction. A more suitable approach to manage the internal and external complexities that organisations are currently confronting is to alter their dominant culture under the principles of MBV.

Detection of Optimal Models in Parameter Space with Support Vector Machines

The paper proposes an approach aimed at detecting optimal model parameter combinations to achieve the most representative description of uncertainty in the model performance. A classification problem is posed to find the regions of good fitting models according to the values of a cost function. Support Vector Machine (SVM) classification in the parameter space is applied to decide if a forward model simulation is to be computed for a particular generated model. SVM is particularly designed to tackle classification problems in high-dimensional space in a non-parametric and non-linear way. SVM decision boundaries determine the regions that are subject to the largest uncertainty in the cost function classification, and, therefore, provide guidelines for further iterative exploration of the model space. The proposed approach is illustrated by a synthetic example of fluid flow through porous media, which features highly variable response due to the parameter values' combination.

Effective continuing professional development for translating shared decision making in primary care: A study protocol.

Background: Shared decision making (SDM) is a process by which a healthcare choice is made jointly by the healthcare professional and the patient. SDM is the essential element of patient-centered care, a core concept of primary care. However, SDM is seldom translated into primary practice. Continuing professional development (CPD) is the principal means by which healthcare professionals continue to gain, improve, and broaden the knowledge and skills required for patient-centered care. Our international collaboration seeks to improve the knowledge base of CPD that targets translating SDM into the clinical practice of primary care in diverse healthcare systems. Methods: Funded by the Canadian Institutes of Health Research (CIHR), our project is to form an international, interdisciplinary research team composed of health services researchers, physicians, nurses, psychologists, dietitians, CPD decision makers and others who will study how CPD causes SDM to be practiced in primary care. We will perform an environmental scan to create an inventory of CPD programs and related activities for translating SDM into clinical practice. These programs will be critically assessed and compared according to their strengths and limitations. We will use the empirical data that results from the environmental scan and the critical appraisal to identify knowledge gaps and generate a research agenda during a two-day workshop to be held in Quebec City. We will ask CPD stakeholders to validate these knowledge gaps and the research agenda. Discussion: This project will analyse existing CPD programs and related activities for translating SDM into the practice of primary care. Because this international collaboration will develop and identify various factors influencing SDM, the project could shed new light on how SDM is implemented in primary care.

Toward a Statistically Robust Assessment of Social and Solidarity Economy Actors. Conceptual Development and Empirical Validation

Many definitions and debates exist about the core characteristics of social and solidarity economy (SSE) and its actors. Among others, legal forms, profit, geographical scope, and size as criteria for identifying SSE actors often reveal dissents among SSE scholars. Instead of using a dichotomous, either-in-or-out definition of SSE actors, this paper presents an assessment tool that takes into account multiple dimensions to offer a more comprehensive and nuanced view of the field. We first define the core dimensions of the assessment tool by synthesizing the multiple indicators found in the literature. We then empirically test these dimensions and their interrelatedness and seek to identify potential clusters of actors. Finally we discuss the practical implications of our model.

Iterated local search

Iterated Local Search has many of the desirable features of a metaheuristic: it is simple, easy to implement, robust, and highly effective. The essential idea of Iterated Local Search lies in focusing the search not on the full space of solutions but on a smaller subspace defined by the solutions that are locally optimal for a given optimization engine. The success of Iterated Local Search lies in the biased sampling of this set of local optima. How effective this approach turns out to be depends mainly on the choice of the local search, the perturbations, and the acceptance criterion. So far, in spite of its conceptual simplicity, it has lead to a number of state-of-the-art results without the use of too much problem-specific knowledge. But with further work so that the different modules are well adapted to the problem at hand, Iterated Local Search can often become a competitive or even state of the artalgorithm. The purpose of this review is both to give a detailed description of this metaheuristic and to show where it stands in terms of performance.

Sex differences in the neurobiology of fear conditioning and extinction: a preliminary fMRI study of shared sex differences with stress-arousal circuitry.

BACKGROUND: The amygdala, hippocampus, medial prefrontal cortex (mPFC) and brain-stem subregions are implicated in fear conditioning and extinction, and are brain regions known to be sexually dimorphic. We used functional magnetic resonance imaging (fMRI) to investigate sex differences in brain activity in these regions during fear conditioning and extinction. METHODS: Subjects were 12 healthy men comparable to 12 healthy women who underwent a 2-day experiment in a 3 T MR scanner. Fear conditioning and extinction learning occurred on day 1 and extinction recall occurred on day 2. The conditioned stimuli were visual cues and the unconditioned stimulus was a mild electric shock. Skin conductance responses (SCR) were recorded throughout the experiment as an index of the conditioned response. fMRI data (blood-oxygen-level-dependent [BOLD] signal changes) were analyzed using SPM8. RESULTS: Findings showed no significant sex differences in SCR during any experimental phases. However, during fear conditioning, there were significantly greater BOLD-signal changes in the right amygdala, right rostral anterior cingulate (rACC) and dorsal anterior cingulate cortex (dACC) in women compared with men. In contrast, men showed significantly greater signal changes in bilateral rACC during extinction recall. CONCLUSIONS: These results indicate sex differences in brain activation within the fear circuitry of healthy subjects despite similar peripheral autonomic responses. Furthermore, we found that regions where sex differences were previously reported in response to stress, also exhibited sex differences during fear conditioning and extinction.

Shared knowledge

Agents use their knowledge on the history of the economy in orderto choose what is the optimal action to take at any given moment of time,but each individual observes history with some noise. This paper showsthat the amount of information available on the past evolution of theeconomy is an endogenous variable, and that this leads to overconcentrationof the investment, which can be interpreted as underinvestment in research.It presents a model in which agents have to invest at each period in one of$K$ sectors, each of them paying an exogenous return that follows a welldefined stochastic path. At any moment of time each agent receives an unbiasednoisy signal on the payoff of each sector. The signals differ across agents,but all of them have the same variance, which depends on the aggregate investmentin that particular sector (so that if almost everybody invests in it theperceptions of everybody will be very accurate, but if almost nobody doesthe perceptions of everybody will be very noisy). The degree of hetereogeneityacross agents is then an endogenous variable, evolving across time determining,and being determined by, the amount of information disclosed.As long as both the level of social interaction and the underlying precisionof the observations are relatively large agents behave in a very preciseway. This behavior is unmodified for a huge range of informational parameters,and it is characterized by an excessive concentration of the investment ina few sectors. Additionally the model shows that generalized improvements in thequality of the information that each agent gets may lead to a worse outcomefor all the agents due to the overconcentration of the investment that thisproduces.

New ideas need new space

We develop a setting with weak intellectual property rights, where firms' boundaries, location and knowledge spillovers are endogenous. We have two main results. The first one is that, if communication costs increase with distance, entrepreneurs concerned about information leakage have a benefit from locating away from the industry center: distance is an obstacle to collusive trades between members andnon-members. The second result is that we identify a trade-off for the entrepreneur between owning a facility (controlling all its characteristics) and sharing a facility with a {\it non-member} (an agent not involved in production), therefore losing control over some of its characteristics. We focus on ``location" as the relevant characteristic of the facility, but location can be used as a spatial metaphor for other relevant characteristics of the facility. For theentrepreneur, sharing the facility with non-members implies that the latter, as co-owners, know the location (even if they do not have access to it). Knowledge of the location for the co-owners facilitates collusion with employees, what increases leakage. The model yields a benefit for new plants from spatial dispersion (locating at the periphery of the industry), particularly so for new plants of new firms.We relate this result with recent empirical findings on the dynamics of industry location.

Organisational values as "attractors of chaos": An emerging cultural change to manage organisational complexity

Business organisations are excellent representations of what in physics and mathematics are designated "chaotic" systems. Because a culture of innovation will be vital for organisational survival in the 21st century, the present paper proposes that viewing organisations in terms of "complexity theory" may assist leaders in fine-tuning managerial philosophies that provide orderly management emphasizing stability within a culture of organised chaos, for it is on the "boundary of chaos" that the greatest creativity occurs. It is argued that 21st century companies, as chaotic social systems, will no longer be effectively managed by rigid objectives (MBO) nor by instructions (MBI). Their capacity for self-organisation will be derived essentially from how their members accept a shared set of values or principles for action (MBV). Complexity theory deals with systems that show complex structures in time or space, often hiding simple deterministic rules. This theory holds that once these rules are found, it is possible to make effective predictions and even to control the apparent complexity. The state of chaos that self-organises, thanks to the appearance of the "strange attractor", is the ideal basis for creativity and innovation in the company. In this self-organised state of chaos, members are not confined to narrow roles, and gradually develop their capacity for differentiation and relationships, growing continuously toward their maximum potential contribution to the efficiency of the organisation. In this way, values act as organisers or "attractors" of disorder, which in the theory of chaos are equations represented by unusually regular geometric configurations that predict the long-term behaviour of complex systems. In business organisations (as in all kinds of social systems) the starting principles end up as the final principles in the long term. An attractor is a model representation of the behavioral results of a system. The attractor is not a force of attraction or a goal-oriented presence in the system; it simply depicts where the system is headed based on its rules of motion. Thus, in a culture that cultivates or shares values of autonomy, responsibility, independence, innovation, creativity, and proaction, the risk of short-term chaos is mitigated by an overall long-term sense of direction. A more suitable approach to manage the internal and external complexities that organisations are currently confronting is to alter their dominant culture under the principles of MBV.

Aproximacíon Teórico-Conceptual a la Metáfora y el Símbolo

La metáfora y el símbolo constituyen eje central de esta investigación, la cual en principio no pretende ser un estudio exhaustivo de estos conceptos, tarea que requeriría muchos años de indagación y búsqueda, al ser éste un primer acercamiento a un controvertido, sugerente e interesante problema que se encuentra no sólo en las raíces de nuestro lenguaje, sino también de nuestro pensamiento y por tanto del devenir filosófico. El recurso de la metáfora y el símbolo, no sólo es propio de la literatura sino común a toda obra humana. Tal es el caso de los mitos, las alegorías, la poesía, las obras de teatro, los ensayos —que a menudo los contienen— y los modelos a escalas tanto teóricos como reales con los que trabaja la ciencia para luego, transferir lo peculiar de la ficción heurística a la realidad.

A dynamic choice model of hybrid behavior in the attribute-space

This paper presents a dynamic choice model in the attributespace considering rational consumers that discount the future. In lightof the evidence of several state-dependence patterns, the model isfurther extended by considering a utility function that allows for thedifferent types of behavior described in the literature: pure inertia,pure variety seeking and hybrid. The model presents a stationaryconsumption pattern that can be inertial, where the consumer only buysone product, or a variety-seeking one, where the consumer buys severalproducts simultane-ously. Under the inverted-U marginal utilityassumption, the consumer behaves inertial among the existing brands forseveral periods, and eventually, once the stationary levels areapproached, the consumer turns to a variety-seeking behavior. An empiricalanalysis is run using a scanner database for fabric softener andsignificant evidence of hybrid behavior for most attributes is found,which supports the functional form considered in the theory.