Automatic tutoring system to support cross-disciplinary training in Big Data

Producció científica: Article en revista indexadaArticleAvaluat per experts

10 Cites (Scopus)


During the last decade, Big Data has emerged as a powerful alternative to address latent challenges in scalable data management. The ever-growing amount and rapid evolution of tools, techniques, and technologies associated to Big Data require a broad skill set and deep knowledge of several domains—ranging from engineering to business, including computer science, networking, or analytics among others—which complicate the conception and deployment of academic programs and methodologies able to effectively train students in this discipline. The purpose of this paper is to propose a learning and teaching framework committed to train masters’ students in Big Data by conceiving an intelligent tutoring system aimed to (1) automatically tracking students’ progress, (2) effectively exploiting the diversity of their backgrounds, and (3) assisting the teaching staff on the course operation. Obtained results endorse the feasibility of this proposal and encourage practitioners to use this approach in other domains.

Idioma originalAnglès
Pàgines (de-a)1818-1852
Nombre de pàgines35
RevistaJournal of Supercomputing
Estat de la publicacióPublicada - de febr. 2021


Navegar pels temes de recerca de 'Automatic tutoring system to support cross-disciplinary training in Big Data'. Junts formen un fingerprint únic.

Com citar-ho