Students' academic performance is a key factor for educational institutions and society, which is an important indicator of the quality of the teaching-learning process and the appropriation of knowledge. Its analysis allows an understanding of the behavior of students and teachers, generating valuable knowledge for making timely academic decisions. In this study, the following phases were carried out: (i) identification of factors that influence the academic performance of engineering university students, (ii) early prediction of academic success, and (iii) identification of use patterns in a virtual learning environment (VLE). The Knowledge Discovery in Databases (KDD) methodology was applied based on predictive and descriptive data mining techniques, using academic and socioeconomic data and interactions (resources and activities) with the VLE. The tools and programming languages ​​used were Pentaho Data Integration for data integration and processing; Jupyter Notebook, Python, and Scikit-Learn for correlation analysis and prediction modeling; and R Studio for the clustering task. The results show that VLE resources such as files, links, and activities such as participation in forums are factors that lead to good academic performance. On the other hand, it was possible to make predictions of academic success (pass or not) with an accuracy greater than 95% and to identify the main patterns of use of the VLE. The group with excellent academic performance (grades 9 to 10) is recognized for using file-type resources and high participation in class and forum activities.

Although there are many studies on the main factors that lead to failure in implanting Enterprise I.T. Applications (EITA), EITA projects still have a high failure rate within the different implantation phases. In this literature review, several factors of failure in the implantation of EITA were analyzed, as well as various cases where there was a failed implantation of an EITA, to collect the different common causes and have a basis of recurring factors to be considered for future projects. The method used in the research was a literature review and a search for cases from 2015, where the common point is the failure in the implantation of EITAs. Subsequently, it was found that the factors detailed in the case studies are related to factors reviewed in the literature review, which means that these factors are recurrent and common. Finally, it was concluded that quality, management, time, and financial aspects are the factors that were generally relevant in the cases analyzed and that, despite the type or extent of the project, identifying these factors will determine early on the success or failure of the project.

This study aims to evaluate the Integrated University Information System (SIIU) at Universidad Técnica del Norte by applying the DeLone and McLean Information Systems Success Model. The SIIU plays a crucial role in academic management by integrating key modules, such as executive, faculty, and student portfolios. Despite its long-standing implementation, a comprehensive assessment of the system's performance and its impact on academic activities had not been conducted until now. The research specifically focuses on assessing the SIIU's impact from the students' perspective, applying the six dimensions of the DeLone and McLean model: system quality, information quality, service quality, use/intention to use, user satisfaction, and net impacts. Four assessments were carried out over two years (May 2022, February 2023, July 2023, and July 2024), using a 28-item survey to measure these dimensions.The findings confirm the validity of the DeLone and McLean model in evaluating information systems and reveal a positive trend in students' perceptions of the "SIIU – Student Portfolio" over the past years. The results also provide a detailed breakdown of the system's strengths, weaknesses, and areas for improvement, as experienced by students. These insights offer valuable guidance for the SIIU management team, facilitating targeted improvements to optimize the system’s contribution to the university’s academic environment.