La construcción de sentido del inicio de un cambio estratégico en las organizaciones: el caso de la Universidad del Rosario

A través de un caso de estudio se explora cómo la construcción de sentido de un grupo de directivos, bajo una misma inspiración, generó el inicio de un cambio estratégico en una prestigiosa y reconocida universidad colombiana, la Universidad del Rosario. Una institución que en un momento determinado notó que estaba siendo percibida dentro del sector de la educación superior como pequeña, estática en el avance de algunas disciplinas del conocimiento y conservadora; en otras palabras, que estaba perdiendo el reconocimiento que usualmente la había acompañado. A través del estudio de este caso se utilizó la técnica de análisis de discurso para comprender la construcción de sentido del inicio de un cambio estratégico en las organizaciones. Esta técnica permitió analizar la información cualitativa derivada de las entrevistas que se realizaron en profundidad a la cúpula de directivos de la institución y a algunos destacados representantes del sector de la Educación Superior en Colombia. Los resultados sugieren que se hicieron presentes, efectivamente, algunas condiciones específicas que marcaron el inicio de un cambio estratégico en la institución y un viraje en su identidad e imagen. Hechos que se sustentaron en los miembros de un equipo que procuró interpretar y comprender los cambios existentes en el entorno global y local, y asimilar, igualmente, algunos destacados retos que se planteaban por aquella época, al interior de la propia Universidad

Human-machine symbiosis overview

The interface between humans and technology is a rapidly changing field. In particular as technological methods have improved dramatically so interaction has become possible that could only be speculated about even a decade earlier. This interaction can though take on a wide range of forms. Indeed standard buttons and dials with televisual feedback are perhaps a common example. But now virtual reality systems, wearable computers and most of all, implant technology are throwing up a completely new concept, namely a symbiosis of human and machine. No longer is it sensible simply to consider how a human interacts with a machine, but rather how the human-machine symbiotic combination interacts with the outside world. In this paper we take a look at some of the recent approaches, putting implant technology in context. We also consider some specific practical examples which may well alter the way we look at this symbiosis in the future. The main area of interest as far as symbiotic studies are concerned is clearly the use of implant technology, particularly where a connection is made between technology and the human brain and/or nervous system. Often pilot tests and experimentation has been carried out apriori to investigate the eventual possibilities before human subjects are themselves involved. Some of the more pertinent animal studies are discussed briefly here. The paper however concentrates on human experimentation, in particular that carried out by the authors themselves, firstly to indicate what possibilities exist as of now with available technology, but perhaps more importantly to also show what might be possible with such technology in the future and how this may well have extensive social effects. The driving force behind the integration of technology with humans on a neural level has historically been to restore lost functionality in individuals who have suffered neurological trauma such as spinal cord damage, or who suffer from a debilitating disease such as lateral amyotrophic sclerosis. Very few would argue against the development of implants to enable such people to control their environment, or some aspect of their own body functions. Indeed this technology in the short term has applications for amelioration of symptoms for the physically impaired, such as alternative senses being bestowed on a blind or deaf individual. However the issue becomes distinctly more complex when it is proposed that such technology be used on those with no medical need, but instead who wish to enhance and augment their own bodies, particularly in terms of their mental attributes. These issues are discussed here in the light of practical experimental test results and their ethical consequences.

Using an animated pedagogical agent to interact affectively with the student

This work proposes an animated pedagogical agent that has the role of providing emotional support to the student: motivating and encouraging him, making him believe in his self-ability, and promoting a positive mood in him, which fosters learning. This careful support of the agent, its affective tactics, is expressed through emotional behaviour and encouragement messages of the lifelike character. Due to human social tendency of anthropomorphising software, we believe that a software agent can accomplish this affective role. In order to choose the adequate affective tactics, the agent should also know the student’s emotions. The proposed agent recognises the student’s emotions: joy/distress, satisfaction/disappointment, anger/gratitude, and shame, from the student’s observable behaviour, i. e. his actions in the interface of the educational system. The inference of emotions is psychologically grounded on the cognitive theory of emotions. More specifically, we use the OCC model which is based on the cognitive approach of emotion and can be computationally implemented. Due to the dynamic nature of the student’s affective information, we adopted a BDI approach to implement the affective user model and the affective diagnosis. Besides, in our work we profit from the reasoning capacity of the BDI approach in order for the agent to deduce the student’s appraisal, which allows it to infer the student’s emotions. As a case study, the proposed agent is implemented as the Mediating Agent of MACES: an educational collaborative environment modelled as a multi-agent system and pedagogically based on the sociocultural theory of Vygotsky.

Participatory design in the project of virtual learning environment of histology

This present article describes a research on the development, under the approach of participatory design, a virtual teaching-learning of Histology in which students and teachers participated actively in all stages of development of the educational environment. We postulates that the development of virtual learning environment of Histology, through the Participatory Design approach, contributes to greater acceptance and use by students and that the adoption of virtual environment for teaching and learning by teachers is a determining factor of use by students

Polymorphisms of DNA repair genes XRCC1 and XRCC3, interaction with environmental exposure and risk of chronic gastritis and grastic cancer

Aim: To evaluate the association between polymorphisms XRCC1 Arg194Trp and Arg399Gln and XRCC3 Thr241Met and the risk for chronic gastritis and gastric cancer, in a Southeastern Brazilian population. Methods: Genotyping by PCR-RFLP was carried out on 202 patients with chronic gastritis (CG) and 160 patients with gastric cancer (GC), matched to 202 (C1) and 150 (C2) controls, respectively. Results: No differences were observed among the studied groups with regard to the genotype distribution of XRCC1 codons 194 and 399 and of XRCC3 codon 241. However, the combined analyses of the three variant alleles (194Trp, 399Gln and 241Met) showed an increased risk for chronic gastritis when compared to the GC group. Moreover, an interaction between the polymorphic alleles and demographic and environmental factors was observed in the CG and GC groups. XRCC1 194Trp was associated with smoking in the CG group, while the variant alleles XRCC1 399Gln and XRCC3 241Met were related with gender, smoking, drinking and H pylori infection in the CG and GC groups. Conclusion: Our results showed no evidence of a rela-tionship between the polymorphisms XRCC1 Arg194Trp and Arg399Gln and XRCC3 Thr241Met and the risk of chronic gastritis and gastric cancer in the Brazilian population, but the combined effect of these variants may interact to increase the risk for chronic gastritis, considered a premalignant lesion. Our data also indicate a gene-environment interaction in the susceptibility to chronic gastritis and gastric cancer. © 2005 The WJG Press and Elsevier Inc. All rights reserved.

A study on human error in the interaction with the computer systems

The term human factor is used by professionals of various fields meant for understanding the behavior of human beings at work. The human being, while developing a cooperative activity with a computer system, is subject to cause an undesirable situation in his/her task. This paper starts from the principle that human errors may be considered as a cause or factor contributing to a series of accidents and incidents in many diversified fields in which human beings interact with automated systems. We propose a simulator of performance in error with potentiality to assist the Human Computer Interaction (HCI) project manager in the construction of the critical systems. © 2011 Springer-Verlag.

Parental Ethnotheories of Child Development: Looking Beyond Independence and Individualism in American Belief Systems

Over the past several decades, the topic of child development in a cultural context has received a great deal of theoretical and empirical investigation. Investigators from the fields of indigenous and cultural psychology have argued that childhood is socially and historically constructed, rather than a universal process with a standard sequence of developmental stages or descriptions. As a result, many psychologists have become doubtful that any stage theory of cognitive or socialemotional development can be found to be valid for all times and places. In placing more theoretical emphasis on contextual processes, they define culture as a complex system of common symbolic action patterns (or scripts) built up through everyday human social interaction by means of which individuals create common meanings and in terms of which they organize experience. Researchers understand culture to be organized and coherent, but not homogenous or static, and realize that the complex dynamic system of culture constantly undergoes transformation as participants (adults and children) negotiate and re-negotiate meanings through social interaction. These negotiations and transactions give rise to unceasing heterogeneity and variability in how different individuals and groups of individuals interpret values and meanings. However, while many psychologists—both inside and outside the fields of indigenous and cultural psychology–are now willing to give up the idea of a universal path of child development and a universal story of parenting, they have not necessarily foreclosed on the possibility of discovering and describing some universal processes that underlie socialization and development-in-context. The roots of such universalities would lie in the biological aspects of child development, in the evolutionary processes of adaptation, and in the unique symbolic and problem-solving capacities of the human organism as a culture-bearing species. For instance, according to functionalist psychological anthropologists, shared (cultural) processes surround the developing child and promote in the long view the survival of families and groups if they are to demonstrate continuity in the face of ecological change and resource competition, (e.g. Edwards & Whiting, 2004; Gallimore, Goldenberg, & Weisner, 1993; LeVine, Dixon, LeVine, Richman, Leiderman, Keefer, & Brazelton, 1994; LeVine, Miller, & West, 1988; Weisner, 1996, 2002; Whiting & Edwards, 1988; Whiting & Whiting, 1980). As LeVine and colleagues (1994) state: A population tends to share an environment, symbol systems for encoding it, and organizations and codes of conduct for adapting to it (emphasis added). It is through the enactment of these population-specific codes of conduct in locally organized practices that human adaptation occurs. Human adaptation, in other words, is largely attributable to the operation of specific social organizations (e.g. families, communities, empires) following culturally prescribed scripts (normative models) in subsistence, reproduction, and other domains [communication and social regulation]. (p. 12) It follows, then, that in seeking to understand child development in a cultural context, psychologists need to support collaborative and interdisciplinary developmental science that crosses international borders. Such research can advance cross-cultural psychology, cultural psychology, and indigenous psychology, understood as three sub-disciplines composed of scientists who frequently communicate and debate with one another and mutually inform one another’s research programs. For example, to turn to parental belief systems, the particular topic of this chapter, it is clear that collaborative international studies are needed to support the goal of crosscultural psychologists for findings that go beyond simply describing cultural differences in parental beliefs. Comparative researchers need to shed light on whether parental beliefs are (or are not) systematically related to differences in child outcomes; and they need meta-analyses and reviews to explore between- and within-culture variations in parental beliefs, with a focus on issues of social change (Saraswathi, 2000). Likewise, collaborative research programs can foster the goals of indigenous psychology and cultural psychology and lay out valid descriptions of individual development in their particular cultural contexts and the processes, principles, and critical concepts needed for defining, analyzing, and predicting outcomes of child development-in-context. The project described in this chapter is based on an approach that integrates elements of comparative methodology to serve the aim of describing particular scenarios of child development in unique contexts. The research team of cultural insiders and outsiders allows for a look at American belief systems based on a dialogue of multiple perspectives.

Constructing a user experience user experience-based mobile learning environment

Mobile learning, in the past defined as learning with mobile devices, now refers to any type of learning-on-the-go or learning that takes advantage of mobile technologies. This new definition shifted its focus from the mobility of technology to the mobility of the learner (O'Malley and Stanton 2002; Sharples, Arnedillo-Sanchez et al. 2009). Placing emphasis on the mobile learner’s perspective requires studying “how the mobility of learners augmented by personal and public technology can contribute to the process of gaining new knowledge, skills, and experience” (Sharples, Arnedillo-Sanchez et al. 2009). The demands of an increasingly knowledge based society and the advances in mobile phone technology are combining to spur the growth of mobile learning. Around the world, mobile learning is predicted to be the future of online learning, and is slowly entering the mainstream education. However, for mobile learning to attain its full potential, it is essential to develop more advanced technologies that are tailored to the needs of this new learning environment. A research field that allows putting the development of such technologies onto a solid basis is user experience design, which addresses how to improve usability and therefore user acceptance of a system. Although there is no consensus definition of user experience, simply stated it focuses on how a person feels about using a product, system or service. It is generally agreed that user experience adds subjective attributes and social aspects to a space that has previously concerned itself mainly with ease-of-use. In addition, it can include users’ perceptions of usability and system efficiency. Recent advances in mobile and ubiquitous computing technologies further underline the importance of human-computer interaction and user experience (feelings, motivations, and values) with a system. Today, there are plenty of reports on the limitations of mobile technologies for learning (e.g., small screen size, slow connection), but there is a lack of research on user experience with mobile technologies. This dissertation will fill in this gap by a new approach in building a user experience-based mobile learning environment. The optimized user experience we suggest integrates three priorities, namely a) content, by improving the quality of delivered learning materials, b) the teaching and learning process, by enabling live and synchronous learning, and c) the learners themselves, by enabling a timely detection of their emotional state during mobile learning. In detail, the contributions of this thesis are as follows: • A video codec optimized for screencast videos which achieves an unprecedented compression rate while maintaining a very high video quality, and a novel UI layout for video lectures, which together enable truly mobile access to live lectures. • A new approach in HTTP-based multimedia delivery that exploits the characteristics of live lectures in a mobile context and enables a significantly improved user experience for mobile live lectures. • A non-invasive affective learning model based on multi-modal emotion detection with very high recognition rates, which enables real-time emotion detection and subsequent adaption of the learning environment on mobile devices. The technology resulting from the research presented in this thesis is in daily use at the School of Continuing Education of Shanghai Jiaotong University (SOCE), a blended-learning institution with 35.000 students.

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

Sharing Human-Generated Observations by Integrating HMI and the Semantic Sensor Web

Current “Internet of Things” concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and Semantic Sensor Web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and Sensor Web initiatives: the W3C’s Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) with its semantic extension, respectively. Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where drivers’ observations about the traffic or their environment are shared across the Semantic Sensor Web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, Sensor Web and Semantic Web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is sound

Intentions: a confident-based interaction design for smart spaces

The paradigm of ubiquitous computing has become a reference for the design of Smart Spaces. Current trends in Ambient Intelligence are increasingly related to the scope of Internet of Things. This paradigm has the potential to support cost-effective solutions in the fields of telecare, e-health and Ambient Assisted Living. Nevertheless, ubiquitous computing does not provide end users with a role for proactive interactions with the environment. Thus, the deployment of smart health care services at a private space like the home is still unsolved. This PhD dissertation aims to define a person-environment interaction model to foster acceptability and users confidence in private spaces by applying the concept of user-centred security and the human performance model of seven stages of action.

3D visual sensing of human hand for remote operation of a robotic hand

New low cost sensors and open free libraries for 3D image processing are making important advances in robot vision applications possible, such as three-dimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a novel method for recognizing and tracking the fingers of a human hand is presented. This method is based on point clouds from range images captured by a RGBD sensor. It works in real time and it does not require visual marks, camera calibration or previous knowledge of the environment. Moreover, it works successfully even when multiple objects appear in the scene or when the ambient light is changed. Furthermore, this method was designed to develop a human interface to control domestic or industrial devices, remotely. In this paper, the method was tested by operating a robotic hand. Firstly, the human hand was recognized and the fingers were detected. Secondly, the movement of the fingers was analysed and mapped to be imitated by a robotic hand.

Influence apart from Adoption: How Interaction between Programming and Scientific Practices Shapes Modes of Inquiry in Four Oceanography Teams

Thesis (Ph.D.)--University of Washington, 2016-06

User interaction monitoring and analysis framework

An overview is given of a user interaction monitoring and analysis framework called BaranC. Monitoring and analysing human-digital interaction is an essential part of developing a user model as the basis for investigating user experience. The primary human-digital interaction, such as on a laptop or smartphone, is best understood and modelled in the wider context of the user and their environment. The BaranC framework provides monitoring and analysis capabilities that not only records all user interaction with a digital device (e.g. smartphone), but also collects all available context data (such as from sensors in the digital device itself, a fitness band or a smart appliances). The data collected by BaranC is recorded as a User Digital Imprint (UDI) which is, in effect, the user model and provides the basis for data analysis. BaranC provides functionality that is useful for user experience studies, user interface design evaluation, and providing user assistance services. An important concern for personal data is privacy, and the framework gives the user full control over the monitoring, storing and sharing of their data.

Situating Design Research within Social Framework

This paper explores the expertise in industrial (product) design and contribution of knowledge generated trough the design research. Within this approach the research is situated within the social structure that constitutes people, activity, context and culture where an artifact is seen to be a mediator for the generation of new knowledge and its application. The paper concludes about the importance of research and practice integration and points out that situating the research around the artifacts, as mediators of knowledge, is transferable to Human-Computer Interaction field and any other area of the design research