Learning Analytics to Validate Academic Performance Analysis

• Published in: International Conference on Engineering and Emerging Technologies (Online) pp. 1 - 4
• Main Authors: Oliveira, Pedro Filipe, Matos, Paulo
• Format: Conference Proceeding
• Language: English
• Published: IEEE 27.10.2023
• Subjects: academic-performance; Analytical models; coursera; dashboard; Data visualization; Education; Electronic learning; learning-analytics; Machine learning algorithms; Real-time systems; Soft sensors
• ISSN: 2831-3682
• DOI: 10.1109/ICEET60227.2023.10525855

The learning process is increasingly on the agenda. As well as the mechanisms that can be used to optimize it, both in terms of improving student performance, as well as improving teacher performance. On this subject, there has been continuous research, and increasingly trying to take advantage of technological development, and thus be able to take full advantage of technology and achieve a significant leverage in this field. This work is developed within the scope of the evaluation of school performance. Namely, with the introduction of additional and customized resources, such as thematic courses on the Coursera platform, and the utilization analysis of the e-learning platform used by the teaching institution. With this, it was possible to develop some tools, which are used as dashboards to give the teacher a greater perception of the student's learning process and performance. And if any student is in the prospect of failing, the teacher receives an immediate notification, so that he can carry out the respective follow-up, and thus be able to act proactively to avoid failure.