Automated Academic Reporting System that Optimizes Educational Management

Abstract

In the context of digital transformation, vocational education institutions face gaps in academic management related to scheduling, learner monitoring, and the generation of reports for decision-making. This article introduces the Automated Academic Reporting System (SARA), whose objective is to describe its technical development and implementation of artificial intelligence, as well as to assess its contribution to academic management through bibliometric analysis and instructor perceptions. The research is applied in nature, with a mixed-methods approach and a descriptive–exploratory scope. SARA’s architectural framework is based on the Model–View–Controller (MVC) pattern and a NoSQL database, ensuring modular scalability and the efficient integration of more than 140,000 heterogeneous records (Excel, SOFIA Plus, JSON). For the bibliometric analysis, the Scopus database was consulted, identifying 4,922 documents processed with VOSviewer® using co-authorship analysis. In addition, semistructured interviews were conducted with seven instructors, whose responses were analyzed using natural language processing techniques to systematize perceptions. The findings highlight in the literature the relevance of frameworks for interoperability, data governance, and digital sustainability, while also revealing a positive perception of SARA regarding ease of use, reduction of administrative workload, and utility in decision-making. In conclusion, SARA is presented as a scalable and replicable tool that strengthens academic management and generates pedagogical and organizational implications from an interdisciplinary perspective.