Social networks and cooperative learning in a MOOC

MOOCs are changing the educational landscape and gaining a lot of attention in scientific literature. However, the pedagogical design of these proposals has been called into question. It is precisely MOOCs’ social aspect, i.e. the interaction between course participants and the support for learning processes that has become one of the main topics of interest. This article presents the results of a research project carried out at the University of the Basque Country, which focused in cooperative learning and the intensive use of social networks in a MOOC. Significant data was compiled through Likert-type surveys, revealing that the use of both external and internal social networks in a massive open online course is a factor that is evaluated positively by students. We argue that the use of social networks as a learning strategy in a MOOC has an influence on academic performance and on the students' success rate. Furthermore, the participants’ age also has a bearing on the social networks they use, and we have found that the younger members tend to work with external networks such as Twitter or personal blogs, whereas the older students are more inclined to use forums from the Chamilo or Ning platforms.

Estimate of the (R)USLE rainfall erosivity factor from monthly precipitation data in mainland Spain

The need for continuous recording rain gauges makes it difficult to determine the rainfall erosivity factor (R-factor) of the (R)USLE model in areas without good temporal data coverage. In mainland Spain, the Nature Conservation Institute (ICONA) determined the R-factor at few selected pluviographs, so simple estimates of the R-factor are definitely of great interest. The objectives of this study were: (1) to identify a readily available estimate of the R-factor for mainland Spain; (2) to discuss the applicability of a single (global) estimate based on analysis of regional results; (3) to evaluate the effect of record length on estimate precision and accuracy; and (4) to validate an available regression model developed by ICONA. Four estimators based on monthly precipitation were computed at 74 rainfall stations throughout mainland Spain. The regression analysis conducted at a global level clearly showed that modified Fournier index (MFI) ranked first among all assessed indexes. Applicability of this preliminary global model across mainland Spain was evaluated by analyzing regression results obtained at a regional level. It was found that three contiguous regions of eastern Spain (Catalonia, Valencian Community and Murcia) could have a different rainfall erosivity pattern, so a new regression analysis was conducted by dividing mainland Spain into two areas: Eastern Spain and plateau-lowland area. A comparative analysis concluded that the bi-areal regression model based on MFI for a 10-year record length provided a simple, precise and accurate estimate of the R-factor in mainland Spain. Finally, validation of the regression model proposed by ICONA showed that R-ICONA index overpredicted the R-factor by approximately 19%.

What is this thing called Historical Archaeology?

Historical archaeology, in its narrow temporal sense -as an archaeology of the emergence and subsequent evolution of the Modern world- is steadily taking pace in Spanish academia. This paper aims at provoking a more robust debate through understanding how Spanish historical archaeology is placed in the international scene and some of its more relevant particularities. In so doing, the paper also stresses the strong links that have united historical and prehistorical archaeology since its inception, both in relation to the ontological, epistemological and methodological definition of the first as to the influence of socio-political issues in the latter. Such reflection is partly a situated reflection from prehistory as one of the paper’s authors has been a prehistorian for most of her professional life.