Abstract

Data in the educational context are becoming increasingly important in decision-making and teaching-learning processes. Similar to the industrial context, educational institutions are adopting data-processing technologies at all levels. To achieve representative results, the processes of extraction, transformation and uploading of educational data should be ubiquitous because, without useful data, either internal or external, it is difficult to perform a proper analysis and to obtain unbiased educational results. It should be noted that the source and type of data are heterogeneous and that the analytical processes can be so diverse that it opens up a practical problem of management and access to the data generated. At the same time, ensuring the privacy, identity, confidentiality and security of students and their data is a “sine qua non” condition for complying with the legal issues involved while achieving the required ethical premises. This work proposes a modular and scalable data system architecture that solves the complexity of data management and access. On the one hand, it allows educational institutions to collect any data generated in both the teaching-learning and management processes. On the other hand, it will enable external access to this data under appropriate privacy and security conditions.

Highlights

  • One of the projects is based on the extraction of indicators to validate the viability of implemented initial version of Salle, the educational warehouse which the educational methodology thatanwas applied in La

  • It follows an end-toand adapted to a subsequent end path gradually; initially, theproject existingaims datatoare understood and stored of so Learning Management Systems (LMS)

  • Interaction with the educational its analysis fullest, applying all ETL, Learning Record Store (LRS), Data Intelligence and Visualization (DIV) and of the projects is based on the extraction of indicators to validate the viability of Data Access Interface (DAI) One modules

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Summary

Introduction

The industrial revolution 4.0, where big data is considered the core, fosters great advances in the technification, digitalization and datafication of the business sector. As. Marciano et al said, “We are just at the beginning of this co-evolutionary path leading toward an epochal revolution. “We are just at the beginning of this co-evolutionary path leading toward an epochal revolution This process is affecting all sectors and all countries.” [1]. Some technologies such as big data, artificial intelligence and machine learning stand out in this revolution, all becoming increasingly present in society in various forms, such as platforms or mobile apps due to the adoption of cloud computing by the business sector.

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