The implementation of graphic organizers to teach reading comprehension skills to second graders of the sur oriental Boston Branch School

El propósito del siguiente proyecto fue seguir una secuencia didáctica y aplicar mapas mentales tal como un organizador gráfico como herramienta de entendimiento y al mismo tiempo mejorar las habilidades de lectura en el L2 con el fin de guiar los aprendices a localizar y clasificar información usando un mapa mental como un organizador gráfico para mejorar las habilidades de lectura

Challenging Social Cognition Models of Adherence:Cycles of Discourse, Historical Bodies, and Interactional Order

Attempts to model individual beliefs as a means of predicting how people follow clinical advice have dominated adherence research, but with limited success. In this article, we challenge assumptions underlying this individualistic philosophy and propose an alternative formulation of context and its relationship with individual actions related to illness. Borrowing from Scollon and Scollon’s three elements of social action – “historical body,” “interaction order,” and “discourses in place” – we construct an alternative set of research methods and demonstrate their application with an example of a person talking about asthma management. We argue that talk- or illness-related behavior, both viewed as forms of social action, manifest themselves as an intersection of cycles of discourse, shifting as individuals move through these cycles across time and space. We finish by discussing how these dynamics of social action can be studied and how clinicians might use this understanding when negotiating treatment with patients

On Quantifying Qualitative Geospatial Data: A Probabilistic Approach

Living in the era of data deluge, we have witnessed a web content explosion, largely due to the massive availability of User-Generated Content (UGC). In this work, we specifically consider the problem of geospatial information extraction and representation, where one can exploit diverse sources of information (such as image and audio data, text data, etc), going beyond traditional volunteered geographic information. Our ambition is to include available narrative information in an effort to better explain geospatial relationships: with spatial reasoning being a basic form of human cognition, narratives expressing such experiences typically contain qualitative spatial data, i.e., spatial objects and spatial relationships. To this end, we formulate a quantitative approach for the representation of qualitative spatial relations extracted from UGC in the form of texts. The proposed method quantifies such relations based on multiple text observations. Such observations provide distance and orientation features which are utilized by a greedy Expectation Maximization-based (EM) algorithm to infer a probability distribution over predefined spatial relationships; the latter represent the quantified relationships under user-defined probabilistic assumptions. We evaluate the applicability and quality of the proposed approach using real UGC data originating from an actual travel blog text corpus. To verify the quality of the result, we generate grid-based maps visualizing the spatial extent of the various relations

Building a semantically annotated corpus of clinical texts

In this paper, we describe the construction of a semantically annotated corpus of clinical texts for use in the development and evaluation of systems for automatically extracting clinically significant information from the textual component of patient records. The paper details the sampling of textual material from a collection of 20,000 cancer patient records, the development of a semantic annotation scheme, the annotation methodology, the distribution of annotations in the final corpus, and the use of the corpus for development of an adaptive information extraction system. The resulting corpus is the most richly semantically annotated resource for clinical text processing built to date, whose value has been demonstrated through its use in developing an effective information extraction system. The detailed presentation of our corpus construction and annotation methodology will be of value to others seeking to build high-quality semantically annotated corpora in biomedical domains