Application of Artificial Intelligence and Computer Vision for Automated Assessment of Practical Activities in Higher Technical Education
DOI:
https://doi.org/10.63688/j1k4f290Keywords:
inteligencia artificial, visión computacional, evaluación automatizada, educación técnica superior, aprendizaje prácticoAbstract
The purpose of this study was to analyze the application of artificial intelligence and computer vision in the automated assessment of practical activities in higher technical education. The research was conducted through a systematic literature review based on the PRISMA model, which allowed the identification, selection, and analysis of studies related to automated assessment, visual recognition, and intelligent technologies applied to technical educational contexts. The documentary search was carried out in indexed databases such as Scopus, Web of Science, IEEE Xplore, SpringerOpen, and MDPI, considering scientific publications from 2018 to 2024. After the screening process and the application of inclusion and exclusion criteria, 16 scientific articles were selected for the final analysis.
The findings showed that automated systems achieve high levels of accuracy compared to human assessment, promoting more objective, consistent, and efficient evaluation processes. Likewise, computer vision and deep learning algorithms were found to enable real-time supervision of practical activities, technical motion tracking, and immediate feedback on student performance. In addition, automated assessment contributes to optimizing teaching time and strengthening academic monitoring processes based on measurable evidence.
Nevertheless, the reviewed studies also revealed challenges related to technological infrastructure, data quality, and teacher training for the proper implementation of these tools. In conclusion, the integration of artificial intelligence and computer vision represents an innovative strategy with strong potential to transform practical assessment processes in higher technical education by promoting efficiency, objectivity, and the development of technical competencies.
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Copyright (c) 2026 Beatriz Estefanía Pérez Peñafiel, Andrea Patricia Sánchez Zumba, Estefanía Jacqueline Sánchez Tenesaca, Dennys Mauricio Coronel Vallejo (Autor/a)
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