Enhancing engineering education through link prediction in social networks
- Autores: Ángel Ferreira-Santiago, Cornelio Yáñez-Márquez, Itzamá López Yáñez, Oscar Camacho-Nieto, Mario Aldape-Pérez, Amadeo-José Argüelles-Cruz
- Localización: The International journal of engineering education, ISSN-e 0949-149X, Vol. 32, no. Extra 4, 2016, págs. 1566-1578
- Idioma: inglés
- Texto completo no disponible (Saber más ...)
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Resumen
In recent years the world has been a witness to a brutal onslaught of emergent technologies. As such it is not surprising thatsocial networking has permeated through practically every human activity with amazing speed. Educational systems havenot lagged behind; and not only is that true, but it is also evident that social networks have ostensibly penetrated inengineering education. This relevant and irrefutable fact has generated the necessity of posing systematic research activitieson a worldwide scale that are related to this topic. In this context the topic covered in this paper is Social Network Researchrelated to Engineering Education. Specifically, our research concerns the way or ways in which link prediction in socialnetworks is able to improve teaching-learning processes in engineering education. A suitably natural environment for theapplication of such research is that of scholarly publications related to computer science, particularly networks. The resultsof our research are promising; they facilitate valuable information regarding the tendencies of the actors immersed inengineering education, be they students or faculty members.
