El sistema educativo en tiempos de pandemia ha tenido que transformarse de forma urgente e imprevista a una modalidad virtual. En este trabajo se presenta un estudio exploratorio sobre las principales dificultades encontradas por las instituciones educativas en Iberoamérica y algunas estrategias utilizadas en los procesos de enseñanza aprendizaje. Asimismo, teniendo en cuenta el análisis previo, se propone un modelo de evaluación a considerar en los planes de contingencia debido a la emergencia sanitaria.

The Social Network Analysis (SNA) techniques allow modelling and analysing the interaction among individuals based on their attributes and relationships. This approach has been used by several researchers in order to measure the social processes in collaborative learning experiences. But oftentimes such measures were calculated at the final state of experiences, what may be hardly representative of students' behaviours during the learning processes. Therefore, a temporal dimension in SNA metrics may extend and improve the understanding about students' interactions in a collaborative scenario. In this respect, this paper presents a systematic review about SNA metrics used for analysing CSCL scenarios and proposes to trace the behaviour of such metrics during experiences through the inclusion of a temporal dimension. In order to expose this approach, a real collaborative learning experience, supported by a platform called SMLearning System, was analysed. We found that social relationships among students tend to be symmetric, i.e., there was a proportional distribution of efforts and contributions of students, which is an expected condition in a collaborative scenario. Such observations are based on the temporal behaviour of the reciprocity metric and the correlation between in- and out- degree centrality metrics measured in time.

Due to the global pandemic (COVID-19) currently facing humanity, a new environment that promotes teaching–learning is now emerging. This environment that challenges traditional teaching practices created an opportunity for the technology industry to capitalize on by developing creative e-learning platforms that empowers the teaching–learning process, during this ‘emergency’ situation. E-learning scenario is an important element to be considered, as it offers a host of benefits, such as reducing costs, allowing for education on-demand, etc., to its adopters. However, the application of this could bring some challenges, as some of the existing online platforms are not conducive to support clear communication among academic staff. This paper describes a report identifying the main problems faced by teachers and students from different countries in Latin America, when using e-learning platforms in a lockdown scenario, reporting the importance to include aspects related with emotions and awareness.

The incorporation of collaborative work in the educational field grows day after day, as does the research associated with this topic. One of the most recurring problems faced by teachers who want to employ this learning strategy is the good students group formation since this task can be complex both conceptually and computationally, especially if the aim is to automate it. Considering that group formation is key when developing activities in collaborative learning scenarios, this paper aims to propose a technique based on a genetic algorithm approach for achieving homogeneous groups, considering the students personality traits as grouping criteria, since, the aforementioned traits, have proven to be significantly predictive of academic performance and, in addition, to be associated with variables with a strong influence on academic success, such as intelligence and beliefs of self-efficacy. A controlled experiment was designed with 132 students, quantifying the personality traits through the Big Five InventoryBFI, forming working groups and developing a collaborative activity in the initial programming courses. The experiment results allowed validation, not only from a computational point of view evaluating the algorithm performance but also from a pedagogical point of view, confronting the results obtained by students: formation based on personality traits versus formation by the students preference. The highlight of the study is that the homogeneous groups generated by the proposed approach produced better academic results compared to those obtained by groups generated by the students' preference, at the moment of developing a collaborative activity.