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Published February 8, 2024

Data & Metadata

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Edited By:

Editorial Salud, Ciencia y Tecnología

Title:

Data and Metadata

ISSN-L: 2953-4917

Editor's Choice
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2024-02-09 Original
Digital Challenges: The Need to Improve the Use of Information Technologies in Teaching

By Lida Vásquez-Pajuelo, Jhonny Richard Rodriguez-Barboza, Karina Raquel Bartra-Rivero, Edgar Antonio Quintanilla-Alarcón, Wilfredo Vega-Jaime, Eduardo Francisco Chavarri-Joo

In the post-pandemic scenario, a study was conducted at I.E. 50499 Justo Barrionuevo Álvarez in Cusco, Peru, to investigate the relationship between the use of information technologies and digital competencies among teachers. With a sample of 54 teachers, a structured questionnaire was administered to assess their competencies. The results revealed a direct positive correlation between the use of technologies and digital competencies, with a Spearman's Rho coefficient of 0.877, indicating a significant relationship. Correlations between the use of information technologies and the dimensions of digital competencies ranged from moderate to high. Significant correlations were observed in areas such as problem-solving (Rho=0.457), information and digital literacy (Rho=0.633), and security (Rho=0.743), among others. These findings suggest that, despite limited experience and limited knowledge of digital technologies among teachers in the institution, there is a notable relationship between the use of these technologies and their digital competencies. This study underscores the need for further training in information technologies for teachers in non-modernized urban contexts and for those who are older adults with limited prior experience in the digital domain. Enhancing digital competencies is crucial for adapting to the educational challenges in this new era of education

2024-02-08 Reviews
Overview on Data Ingestion and Schema Matching

By Oumaima El Haddadi, Max Chevalier, Bernard Dousset, Ahmad El Allaoui, Anass El Haddadi, Olivier Teste

This overview traced the evolution of data management, transitioning from traditional ETL processes to addressing contemporary challenges in Big Data, with a particular emphasis on data ingestion and schema matching. It explored the classification of data ingestion into batch, real-time, and hybrid processing, underscoring the challenges associated with data quality and heterogeneity. Central to the discussion was the role of schema mapping in data alignment, proving indispensable for linking diverse data sources. Recent advancements, notably the adoption of machine learning techniques, were significantly reshaping the landscape. The paper also addressed current challenges, including the integration of new technologies and the necessity for effective schema matching solutions, highlighting the continuously evolving nature of schema matching in the context of Big Data.

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