Networks of PhD Students and Academic Performance: A Comparison across Countries

In this article we compare regression models obtained to predict PhD students’ academic performance in the universities of Girona (Spain) and Slovenia. Explanatory variables are characteristics of PhD student’s research group understood as an egocentered social network, background and attitudinal characteristics of the PhD students and some characteristics of the supervisors. Academic performance was measured by the weighted number of publications. Two web questionnaires were designed, one for PhD students and one for their supervisors and other research group members. Most of the variables were easily comparable across universities due to the careful translation procedure and pre-tests. When direct comparison was not possible we created comparable indicators. We used a regression model in which the country was introduced as a dummy coded variable including all possible interaction effects. The optimal transformations of the main and interaction variables are discussed. Some differences between Slovenian and Girona universities emerge. Some variables like supervisor’s performance and motivation for autonomy prior to starting the PhD have the same positive effect on the PhD student’s performance in both countries. On the other hand, variables like too close supervision by the supervisor and having children have a negative influence in both countries. However, we find differences between countries when we observe the motivation for research prior to starting the PhD which increases performance in Slovenia but not in Girona. As regards network variables, frequency of supervisor advice increases performance in Slovenia and decreases it in Girona. The negative effect in Girona could be explained by the fact that additional contacts of the PhD student with his/her supervisor might indicate a higher workload in addition to or instead of a better advice about the dissertation. The number of external student’s advice relationships and social support mean contact intensity are not significant in Girona, but they have a negative effect in Slovenia. We might explain the negative effect of external advice relationships in Slovenia by saying that a lot of external advice may actually result from a lack of the more relevant internal advice

PhD Students’ Research Group Networks: a Qualitative Approach

This article examines the networks within the research groups where Spanish PhD students are pursuing their doctorate. Capó et al. (2007) used quantitative data to predict PhD students’ publishing performance from their background, attitudes, supervisors’ performance and research group networks. Variables related to the research group network had a negligible explanatory power on student performance once the remaining variables had been accounted for. In this article, a qualitative follow up of the same students is carried out using extreme case sampling and indepth interviews. The qualitative research shows networking as important for students. Out of the 115 aspects that students mention in the interviews as relevant to publishing in the qualitative research, 92 have to do with their supervisors, their research group or their network as a whole. Similarly, out of the 50 hindrances mentioned, 20 have to do with the networks or relations. The most commonly mentioned network-related topics are research group members pushing PhD students to publish, meeting researchers outside the research group, existence of other PhD students in the group, help with the PhD from group members, supervisor’s interest in the thesis, the possibility of discussing with experts on the PhD’s topic and frequent contact with the supervisor and research group members. Some of these characteristics were not, however, measured in the conventional quantitative social network survey

La adolescencia: retos para la investigación y para la sociedad europea de cara al sigol XXI

A lo largo de la última década, la adolescencia ha sido un tema de discusión política en distintos espacios europeos al más alto nivel. En una sociedad aceleradamente cambiante se percibe que la adecuada socialización de las generaciones más jóvenes constituye un reto socio-histórico que nos afecta a todos. Los cambios en que estamos sumergidos son tan plurales (demográficos, sociales, tecnológicos, económicos, políticos, etc.) que generan un amplísimo frente de nuevos dilemas éticos. La opinión de los ciudadanos de la Unión Europea se muestra preocupada por nuevos valores y destaca la preferencia por la responsabilidad en coherencia con dicha situación cambiante. Todo este macrocontexto psicosocial viene planteando nuevos retos teóricos y de investigación a la comunidad científica. De hecho las ciencias humanas y sociales han empezado a desarrollar nuevas líneas de investigación para comprender mejor las nuevas relaciones entre adultos y adolescentes y las nuevas culturas que emergen entre estos últimos, impulsadas por nuevas aspiraciones sociales compartidas por grupos más o menos amplios de la población joven. El desarrollo de técnicas e instrumentos que nos permitan comprender mejor la perspectiva del adolescente se hace más evidente si analizamos su relación con las nuevas tecnologías de la información y la comunicación. Dichas tecnologías comportan nuevos riesgos, pero también nuevas oportunidades, entre las que destaca la posibilidad de establecer nuevas formas de relación. La motivación que muestran los más jóvenes por las nuevas tecnologías constituye un gran reto a los investigadores aplicados para sugerir formas de maximizar las potencialidades latentes

PhD Students’ Research Group Social Capital in Two Countries: A Clustering Approach with Duocentred Network Measures

The article examines the structure of the collaboration networks of research groups where Slovenian and Spanish PhD students are pursuing their doctorate. The units of analysis are student-supervisor dyads. We use duocentred networks, a novel network structure appropriate for networks which are centred around a dyad. A cluster analysis reveals three typical clusters of research groups. Those which are large and belong to several institutions are labelled under a bridging social capital label. Those which are small, centred in a single institution but have high cohesion are labelled as bonding social capital. Those which are small and with low cohesion are called weak social capital groups. Academic performance of both PhD students and supervisors are highest in bridging groups and lowest in weak groups. Other variables are also found to differ according to the type of research group. At the end, some recommendations regarding academic and research policy are drawn