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.

中文翻译：

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支持大数据跨学科培训的自动辅导系统

在过去十年中，大数据已成为解决可扩展数据管理中潜在挑战的强大替代方案。与大数据相关的工具、技术和技术的数量和快速发展需要广泛的技能和对多个领域的深入了解——从工程到商业，包括计算机科学、网络或分析等——这使数据复杂化能够有效培训学生在该学科中的学术课程和方法的概念和部署。本文的目的是提出一个致力于培养大数据硕士生的学习和教学框架，通过构想一个智能辅导系统，旨在（1）自动跟踪学生的进步，（2）有效地利用他们背景的多样性，(3) 协助教职员工进行课程运作。获得的结果证实了该提议的可行性，并鼓励从业者在其他领域使用这种方法。