The student evaluation of teaching and the competence of students as evaluators

When the college student satisfaction survey is considered in the promotion and recognition of instructors, a usual complaint is related to the impact that biased ratings have on the arithmetic mean (used as a measure of teaching effectiveness). This is especially significant when the number of students responding to the survey is small. In this work a new methodology, considering student to student perceptions, is presented. Two different estimators of student rating credibility, based on centrality properties of the student social network, are proposed. This method is established on the idea that in the case of on-site higher education, students often know which others are competent in rating the teaching and learning process.Comment: 20 pages, 2 table

Evaluation of the higher education teaching activity considering the perception that students have of their peers

La opinión de los estudiantes en el proceso de evaluación del desempeño docente en la educación superior se recaba a partir de las encuestas de satisfacción. En este proceso, una de las quejas más habituales por parte del profesorado es que, en ocasiones, la valoración sesgada de algún estudiante puede llegar a tener una influencia determinante en el resultado final de la evaluación, especialmente cuando el número de encuestados es reducido. En este trabajo, se propone un indicador de satisfacción docente que pondera el resultado de las encuestas según la percepción que los estudiantes tienen los unos de los otros en su faceta de evaluadores de la actividad docente universitaria.A opinião dos estudantes no processo de avaliação do desempenho docente na educação superior se angaria a partir das enquetes de satisfação. Neste processo, uma das queixas mais habituais por parte do professorado é do que, em ocasiões, a valoração enviesada de algum estudante pode chegar a ter uma influência determinante no resultado final da avaliação, especialmente quando o número de interrogados é reduzido. Neste trabalho, propõe-se um indicador de satisfação docente que pondera o resultado das enquetes segundo a percepção que os estudantes têm os uns dos outros em sua faceta de avaliadores da atividade docente universitária.The opinion of the student in the higher education teaching evaluation process is carried out by the satisfaction surveys. In this process, one of the more usual teacher complaints is that, sometimes, the biased view of some students can take a decisive influence in the evaluation final result, especially when the number of respondents is reduced. In this work, an indicator of teaching satisfaction, which weighs the result of the surveys according to the perception that students have the one another as evaluators, is proposed

Do fixed citation windows affect the impact maturation rates of scientific journals?

ABSTRACTScientific fields employ distinct citation practices. As such, bibliometric indicators based on citations need to be standardized to allow comparisons between fields. This paper examines more than six hundred journals in eight JCR categories. Results indicate that impact maturation rates vary considerably from one category to another. The time elapsed until the citation distribution reaches a maximum oscillates between two and five years; hence the opening and closing of the citation window is crucial to the impact factor. Some journals are penalized by the two-year impact factor and benefited by the five-year impact factor, and the reverse situation was also found. Nonetheless, there are impact factors of variable citation windows that produce closer measures of central tendency

Hábitos de publicación y citación según campos científicos: Principales diferencias a partir de las revistas JCR

Journals’ impact indicators are not comparable among scientific fields because of systematic differences in publication and citation habits. In this work, the impact factor was decomposed into five independent variables, as applied to journal category, fields, and areas considered in the databases of the leading provider of science indicators, Thomson Reuters. A Principal Component Analysis was employed to find the sources of the variance and a Cluster Analysis was used to detect similarities. In spite of systematic differences between disciplines, the principal components explain 78% of the total variance. From the statistical point of view, some categories of Science are closer to the Social Sciences than to Science and vice versa.Los indicadores de impacto de revistas no son comparables entre campos científicos debido a las diferencias significativas en los hábitos de publicación y citación. En este trabajo se presenta una descomposición del factor de impacto en cinco variables independientes. Esta descomposición se aplica a las categorías de revista, campos y áreas considerados en las bases de datos del principal proveedor de indicadores científicos, Thomson Reuters. Para localizar las fuentes de la varianza se emplea un Análisis de Componentes Principales y para detectar las semejanzas se utiliza un Análisis Cluster. A pesar de las diferencias sistemáticas entre disciplinas, las componentes principales explican el 78% de la varianza total. Existen categorías de Ciencias que están más próximas, desde el punto de vista estadístico, de algunas Ciencias Sociales que del resto de Ciencias y viceversa

Esqueletos paralelos para la técnica de ramificación y acotación

En un gran número de problemas combinatorios, el tiempo empleado para obtener una solución usando un computador secuencial es muy alto. Una forma de solventar este inconveniente consiste en utilizar la computación paralela. En un computador paralelo, varios procesadores colaboran para resolver simultáneamente un problema en una fracción del tiemp requerido por un sólo procesador. Entre los componentes claves necesarios para que sea posible la aplicación de la computación paralela están la arquitectura, el sistema operativo, los compiladores de lenguajes de programación, y, el más importante de todos, el algoritmo paralelo. Ningún problema se puede resolver en paralelo sin un algoritmo paralelo, puesto que los algoritmos paralelos son el núcleo de la computación paralela. El objetivo de la memoria de tesis doctoral era el desarrollo de una metodología de trabajo para abordar la resolución de problemas de optimización combinatoria mediante la técnica de Ramificación y Acotación utilizando paralelismo. Partiendo de casos concretos se generalizó una forma de trabajar que dio lugar a la resolución de problemas diversos. Para ello, se utilizó el concepto de esqueleto presentado por Murray Cole en 1987

Indicador bibliométrico basado en el índice h

The <i>h</i> index has become one of the most widely used bibliometric indicators for estimating the success of researchers and predicting the impact of their work in the future. This is mainly due to its simplicity, since it is a single indicator that combines production and impact, and can easily be determined by any researcher. It also eliminates the bias caused by the long tail of citation distribution. However, this indicator has limitations, in that it fails to discriminate between researchers with different publishing habits and, as a result, it penalizes those with a more selective output characterized by a relatively low number of frequently cited documents, as opposed to authors with a high number of publications. This paper proposes a solution that would take into consideration the citations of those publications with a high probability of increasing the future <i>h</i> index values.<br><br>El índice <i>h</i> se ha convertido en uno de los indicadores bibliométricos más empleados para estimar el éxito del trabajo realizado por un investigador y predecir el impacto de su producción en el futuro. Esto se debe principalmente a dos razones. En primer lugar, a su simplicidad, dado que se trata de un único indicador que combina producción e impacto, y puede ser determinado fácilmente por cualquier investigador. En segundo lugar, a que elimina los sesgos provocados por las colas de la distribución de citas. Sin embargo, este indicador presenta limitaciones al discriminar entre investigadores con diferentes hábitos de publicación, penalizando a aquellos más selectivos, que no destacan por el número de publicaciones pero sí por el alto número de citas recibidas, frente a los grandes productores. En este trabajo se proponen soluciones que consideran las citas de aquellos artículos que pueden contribuir, con una alta probabilidad, a incrementar el valor del índice <i>h</i> en el futuro

Collaboration Effect by Co-Authorship on Academic Citation and Social Attention of Research

Academic citation and social attention measure different dimensions of the impact of research results. Both measures do not correlate with each other, and they are influenced by many factors. Among these factors are the field of research, the type of access, and co-authorship. In this study, the increase in the impact due to co-authorship in scientific articles disaggregated by field of research and access type, was quantified. For this, the citations and social attention accumulated until the year 2021 by a total of 244,880 research articles published in the year 2018, were analyzed. The data source was Dimensions.ai, and the units of study were research articles in Economics, History and Archaeology, and Mathematics. As the main results, a small proportion of the articles received a large part of the citations and most of the social attention. Both citations and social attention increased, in general, with the number of co-authors. Thus, the greater the number of co-authors, the greater the probability of being cited in academic articles and mentioned on social media. The advantage in citation and social attention due to collaboration is independent of the access type for the publication. Furthermore, although collaboration with an additional co-author is in general positive in terms of citation and social attention, these positive effects reduce as the number of co-authors increases

Collaboration Effect by Co-Authorship on Academic Citation and Social Attention of Research

Academic citation and social attention measure different dimensions of the impact of research results. Both measures do not correlate with each other, and they are influenced by many factors. Among these factors are the field of research, the type of access, and co-authorship. In this study, the increase in the impact due to co-authorship in scientific articles disaggregated by field of research and access type, was quantified. For this, the citations and social attention accumulated until the year 2021 by a total of 244,880 research articles published in the year 2018, were analyzed. The data source was Dimensions.ai, and the units of study were research articles in Economics, History and Archaeology, and Mathematics. As the main results, a small proportion of the articles received a large part of the citations and most of the social attention. Both citations and social attention increased, in general, with the number of co-authors. Thus, the greater the number of co-authors, the greater the probability of being cited in academic articles and mentioned on social media. The advantage in citation and social attention due to collaboration is independent of the access type for the publication. Furthermore, although collaboration with an additional co-author is in general positive in terms of citation and social attention, these positive effects reduce as the number of co-authors increases