A Digital Assistant for the Vocational Guidance of Peruvian Students Using the LLaMA
Received: 18 July 2025 | Revised: 8 September 2025 and 19 September 2025 | Accepted: 20 September 2025 | Online: 8 December 2025
Corresponding author: Lenis Wong
Abstract
Vocational guidance is very useful in helping students make informed academic and professional choices worldwide. However, in Peru, many young people do not have access to this type of specialized support, contributing to issues such as school dropout and poor career decision-making. To help address this gap, we developed a digital assistant software that provides vocational guidance in Spanish using the Large Language Model Meta Artificial Intelligence (LLaMA) 3.2 3B. The development process followed a four-phase methodology. First, Holland's test was selected as the psychometric tool. Second, we trained and optimized LLaMA 3.2 3B using specialized vocational guidance datasets, enabling the system to correctly interpret test responses. Third, we designed and implemented a mobile application that allows students to interact with a digital assistant via voice or text messages. Finally, we conducted a usability and effectiveness evaluation of the system with 40 students from a public high school. By comparing the assistant's recommendations to those provided by an expert psychologist, we obtained a concordance rate of 75.83%, while 80% of participating students were able to use the system without external assistance. These findings indicate that the proposed digital assistant has strong potential to serve as an effective and accessible tool for vocational guidance in Peru.
Keywords:
english, vocational guidance, digital assistant, LLaMA, fine-tunning, Holland's testDownloads
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Copyright (c) 2025 Abel Cierto, Branco Villegas, Lenis Wong
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