Learning Analytics and Big Data in the Transverse Programming Algorithms Course on an E-Learning Platform with University Students

Autor: Nancy Edith Ochoa Guevara, Carmelo de Jesús Montas Ventura, Martha Nicolasa Amaya Becerra, María Isabel Lara Saiz, Olga Lucía Martínez Paredes
Jazyk: English<br />Spanish; Castilian
Rok vydání: 2024
Předmět:
Zdroj: RHS Revista Humanismo y Sociedad, Vol 12, Iss 1, Pp 1-17 (2024)
Druh dokumentu: article
ISSN: 2339-4196
DOI: 10.22209/rhs.v12n1a07
Popis: This research is based on the problem of academic lag in higher education institutions as a result of the COVID-19 pandemic. Additionally, – due to the growth in the number of students specifically in the Faculty of Engineering – this analysis seeks to evaluate the relevance of the Transversal Programming Algorithms course taught on an e-learning platform or in some cases using a blended approach, a situation that generated discomfort at the time for students and teachers. The objective of this study was to analyze the contribution of Learning Analytics and big data methodologies to the continuous improvement of the Transversal Programming Algorithms course taught online. To achieve this, qualitative methodology and data analytics were applied to the information collected during the exhaustive monitoring conducted on the academic behavior of the students of the course and the technical management of the teacher. The results of the analysis of the data obtained demonstrate that the personalized teaching applied in the remote course contributes to bringing students and teachers closer together. Furthermore, it generates in them feelings of belonging, encouragement and hope. This indicates that the innovation applied in the course is the solution to the paralysis that, during the pandemic, prevented the university from moving towards the goal of the desired educational improvement.
Databáze: Directory of Open Access Journals