Classroom procedures based on the multisensory approach for 6th graders to develop reading comprehension at Unidad Educativa San Francisco

Este trabajo es un proyecto de investigación basado primeramente en el estudio de la teoría del Enfoque Multisensorial. Para desarrollarlo, fue necesario analizar el estudio del Dr. Samuel TorreyOrton sobre problemas del aprendizaje, el que lo llevó a establecer un procedimiento de instrucción multisensorial. Estos y otros análisis permitieron a las investigadoras de este proyecto crear un folleto, el cual contiene lecturas e instrucciones para ser aplicadas de manera multisensorial. Es por eso que no solo se recopiló lecturas sino también material multisensorial, con el fin de enseñar a los estudiantes a través de este enfoque. Para llevar a cabo este proyecto, se involucró a veintiocho (28) estudiantes del sexto de básica, paralelo “B”, de la Unidad Educativa “San Francisco”. Se tomó una prueba previa a los estudiantes para medir su nivel de comprensión lectora. Después, se aplicaron los procedimientos en el aula basados en el Enfoque Multisensorial(lectura en voz alta, presentaciónde vocabulario, presentación de un video, actuación de una obra de teatro y manejo de materiales de escultura), así como se usó material multisensorial(tarjetas de memoria, videos, materiales de escultura, entre otros) para desarrollar una clase que duró ochenta (80) minutos. Este proceso se administró durante siete sesiones en un periodo de tres semanas y media. Finalmente, se aplicó una prueba posterior para verificar los logros del proyecto. Los resultados de la prueba posterior mostraron una gran mejoría en la comprensión lectora de los estudiantes.This work is a research project based on a study of the theory of the Multisensory Approach. Thus, it was necessary to learn about Dr. Samuel Torrey Orton’s study on learning disabilities, which led him to establish a multisensory instruction procedure. This and other analyses allowed the researchers of this project to create a booklet that contains readings and instructions to be applied in a multisensory manner. That is why, not only stories, but also multisensory material, were collected in order to teach students through this approach. To carry out this project, twenty-eight (28) students of 6th “B” grade from UnidadEducativa “San Francisco” were involved. A pre-test on reading comprehension was taken by the students in order to measure their reading comprehension level. After that, classroom procedures based on the Multisensory Approach (reading aloud, presenting vocabulary, presenting a video, acting out a role play, and manipulating sculpting materials) and multisensory material (flash cards, videos, sculpting materials, among others) were comprised in a single class that lasted eighty (80) minutes. This process was administered for seven sessions during three and a half weeks. Finally, a post-test was applied in order to find out the effects of the project. The results of the post-test showed great improvement in the students’ reading comprehension.Licenciada en Ciencias de la Educación en Lengua y Literatura InglesaCuenc

Gestión del conocimiento. Perspectiva multidisciplinaria. Volumen 17

El libro “Gestión del Conocimiento. Perspectiva Multidisciplinaria”, Volumen 17 de la Colección Unión Global, es resultado de investigaciones. Los capítulos del libro, son resultados de investigaciones desarrolladas por sus autores. El libro es una publicación internacional, seriada, continua, arbitrada, de acceso abierto a todas las áreas del conocimiento, orientada a contribuir con procesos de gestión del conocimiento científico, tecnológico y humanístico. Con esta colección, se aspira contribuir con el cultivo, la comprensión, la recopilación y la apropiación social del conocimiento en cuanto a patrimonio intangible de la humanidad, con el propósito de hacer aportes con la transformación de las relaciones socioculturales que sustentan la construcción social de los saberes y su reconocimiento como bien público

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

Mapping density, diversity and species-richness of the Amazon tree flora

AbstractUsing 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution.</jats:p

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution.A study mapping the tree species richness in Amazonian forests shows that soil type exerts a strong effect on species richness, probably caused by the areas of these forest types. Cumulative water deficit, tree density and temperature seasonality affect species richness at a regional scale

Mapping density, diversity and species-richness of the Amazon tree flora

Files for "Mapping density, diversity and species-richness of the Amazon tree flora"PlotData.csv: Plot metadata and diversity data, needed to run the R-scripts, plus references.PlotsAbiotic.csv: Abiotic metadata for all plots, needed to run R-scriptsAmazonLowLandForestRaisg.csv: Coordinate file of Amazon forest (0.1 degree), withing Raisg boundary.SoterRaisg.asc: Raster PlotsAbiotic.csv: Abiotic metadata for all plots, needed to run R-scriptsTreeDiversityFunctions.R: Functions need to run R-scriptTreeDiversityScript.R: R-script to create all outputTreeDensity.asc: raster file of estimated tree density of Amazon forestTreeDiversity.asc: raster file of fisher's alpha (0.1 degree) of Amazon forest TreeRichness_ha.asc: raster file of species richness/ha (0.1 degree) of Amazon forest TreeDiversityPoster01.tif: High resolution poster of tree diversity (Fisher's alpha) of Amazon forestTreeDiversityPoster02.tif: High resolution poster of tree species richness/ha of Amazon fores

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

Mapping density, diversity and species-richness of the Amazon tree flora

International audienceUsing 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree speciesrichness results and gridded maps at 0.1-degree resolution