4 resultados para DNA Error Correction


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[Es]El presente trabajo se basa en las consultas que los profesores y profesoras de distintas asignaturas nos hacen al profesorado de lengua. Muchas veces los profesores debemos corregir no sólo el contenido de los trabajos de nuestros alumnos, sino también la lengua. La discusión no es nueva: ¿somos todos los profesores también profesores de lengua? Es un desafío del que difícilmente podemos escapar, ya que la lengua además de ser una materia de estudio también es el vehículo en el que se imparten los contenidos de todas las asignaturas. Con el presente trabajo pretendemos ayudar a los profesores que no imparten lengua como asignatura a corregir los trabajos de sus alumnos. Esta propuesta consta de tres ejes de actuación marcados por un orden de prioridad: prevenir, autocorregir y ayudar.

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[EN] Since Long's Interaction Hypothesis (Long, 1983) multiple studies have suggested the need of oral interaction for successful second language learning. Within this perspective, a great deal of research has been carried out to investigate the role of corrective feedback in the process of acquiring a second language, but there are still varied open debates about this issue. This comparative study seeks to contribute to the existing literature on corrective feedback in oral interaction by exploring teachers' corrective techniques and students' response to these corrections. Two learning contexts were observed and compared: a traditional English as a foreign language (EFL) classroom and a Content and Language Integrated Learning (CLIL) classroom .The main aim was to see whether our data conform to the Counterbalance Hypothesis proposed by Lyster and Mori (2006). Although results did not show significant differences between the two contexts, a qualitative analysis of the data shed some light on the differences between these two language teaching settings. The findings point to the need for further research on error correction in EFL and CLIL contexts in order to overcome the limitations of the present study.

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Building on Item Response Theory we introduce students’ optimal behavior in multiple-choice tests. Our simulations indicate that the optimal penalty is relatively high, because although correction for guessing discriminates against risk-averse subjects, this effect is small compared with the measurement error that the penalty prevents. This result obtains when knowledge is binary or partial, under different normalizations of the score, when risk aversion is related to knowledge and when there is a pass-fail break point. We also find that the mean degree of difficulty should be close to the mean level of knowledge and that the variance of difficulty should be high.