Dificultades para la transferencia en el aprendizaje del concepto de integral

Son muchas las causas para que se dificulte la transferencia del concepto de integral, entre ellas está en primer lugar la no abstracción del concepto de integral y luego deficiencias en la aplicación de la transferencia cercana o en la falta u olvido de conceptos previos. Nuestro trabajo docente debe pro-curar que el alumno progresivamente avance de la transferencia cercana a la lejana hasta comprender el concepto reintegral, y no dedicar demasiado tiempo a la mecánica de encontrar antiderivadas ni quedarnos en problemas donde se busca la aplicación inmediata del concepto

Ambigüedad y polisemia del signo radical:un problema matemático y didáctico

La ambigüedad de la raíz cuadrada y la polisemia del signo radical plantean un problema con raíces históricas. Como problema matemático ha sido resuelto, pero no como problema didáctico, ya que presenta sutilezas conceptuales y operatorias cuya omisión en la enseñanza es a menudo causa de malentendidos y conflictos fuertemente arraigados. En este artículo se aborda este problema en su dimensión matemática desde una perspectiva histórico epistemológica. Esta perspectiva permite sustentar una reflexión didáctica

Los SmartLands. El milagro de Bilbao

In the present article is analysed our cities future, observing that it depends on their capacity to attract and create human resources with a high quality, and to emphatize dare of survival, the cities and the regions must discover their singularities, being the innovation a basic aspect. A possible way of actuation are the SmartLands, territories able to develop an urban renovation, improve the ambiental quality, the urban space and the city image. In the last part of the article is studied the example of Bilbao, a city with an ambitious renovation strategyc that stakes for a new urban style anda new productive system to get successfully into the global economy

Tipología de los errores en el cálculo mental : un estudio en el contexto educativo

The present paper deals with a typology of errors and difficulty of Spanish students in a Teacher Training College when they apply historical mental computation methods (methods taken from the written tradition found in arithmetic textbooks) to solve problems with natural numbers and with decimal numbers

Neural Networks, Ordered Probit Models and Multiple Discriminants. Evaluating Risk Rating Forecasts of Local Governments in Mexico.

Credit risk ratings have become an important input in the process of improving transparency of public finances in local governments and also in the evaluation of credit quality of state and municipal governments in Mexico. Although rating agencies have recently been subjected to heavy criticism, credit ratings are indicators still widely used as a benchmark by analysts, regulators and banks monitoring financial performance of local governments in stable and volatile periods. In this work we compare and evaluate the performance of three forecasting methods frequently used in the literature estimating credit ratings: Artificial Neural Networks (ANN), Ordered Probit models (OP) and Multiple Discriminant Analysis (MDA). We have also compared the performance of the three methods with two models, the first one being an extended model of 34 financial predictors and a second model restricted to only six factors, accounting for more than 80% of the data variability. Although ANN provides better performance within the training sample, OP and MDA are better choices for classifications in the testing sample respectively.Credit Risk Ratings, Ordered Probit Models, Artificial Neural Networks, Discriminant Analysis, Principal Components, Local Governments, Public Finance, Emerging Markets