Artículos y presentaciones en Congresos LIFIA
URI permanente para esta colecciónhttps://digital.cic.gba.gob.ar/handle/11746/543
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Acceso Abierto Una marco de contribución funcional para la Ingeniería de Software Cuántico(2026) Pezzini, María Cecilia; Pons, Claudia Fabiana; Bibbo, Luis MarianoLa Ingeniería de Software Cuántico (Q-SE) requiere herramientas que permitan analizar de manera reproducible y cuantitativa el comportamiento funcional de algoritmos cuánticos, más allá de su corrección global. En este trabajo se presenta SMEF (Software Engineering Module Evaluation Framework), un marco de atribución funcional basado en valores de Shapley, orientado a cuantificar la contribución de bloques funcionales dentro de una implementación cuántica bajo métricas explícitas definidas por el analista. El marco evalúa configuraciones parciales del circuito que preservan el orden físico de ejecución, permitiendo descomponer el comportamiento global en contribuciones funcionales atribuibles a cada bloque, en coherencia con la semántica operacional del algoritmo y con las propiedades axiomáticas del mecanismo de atribución empleado. SMEF no busca reinterpretar la dinámica cuántica subyacente, sino proporcionar métricas funcionales reproducibles y comparables, útiles para actividades propias de la Q-SE, tales como auditoría, validación, comparación sistemática de implementaciones y detección de anomalías funcionales. La propuesta se valida mediante dos casos de estudio: (i) la búsqueda sobre hipercubos del algoritmo SKW y (ii) la etapa de estimación de fase (QPE) del algoritmo de Shor. En ambos casos, los perfiles de contribución obtenidos resultan coherentes con el rol funcional esperado de los bloques analizados y permiten identificar desviaciones funcionales sin necesidad de inspeccionar el circuito a nivel de compuertas. - Artículo
Acceso Abierto Convergencia de Inteligencia Artificial y Blockchain para el fortalecimiento de la seguridad en plataformas FinTech(2026) Ibarra, Gabriel A.; Gindre, FranciscoLa convergencia entre inteligencia artificial (IA) y tecnología blockchain se ha consolidado como un eje central de la seguridad financiera en el ecosistema FinTech. Este trabajo se basa en un análisis sistemático de la literatura que examina el aporte de ambas tecnologías en áreas críticas como la detección de fraudes, la protección de datos sensibles, el cumplimiento regulatorio (KYC/AML), la trazabilidad y la gestión de riesgos. Los resultados muestran que la integración de IA y blockchain fortalece la resiliencia de las plataformas financieras y optimiza procesos regulatorios, aunque persisten desafíos de escalabilidad, interoperabilidad, sesgos algorítmicos y marcos regulatorios incompletos. El trabajo sintetiza el estado actual, las principales limitaciones y las oportunidades de estas tecnologías para mejorar la seguridad en Fin- Tech. - Artículo
Acceso Abierto How Mobile UX Smells Affect Interaction Efficiency: A Multi-Metric Empirical Study(2026) Raverta, Claudio; Grigera, Julián; Gardey, Juan Cruz; Garrido, AlejandraThe concept of UX smells has been recently studied as a systematic way to detect predefined user interaction issues and fix them with cataloged solutions. Most of the existing literature about UX smells focuses on desktop web applications, while there are only a few works ad- dressing the mobile web. Although specific UX smells for mobile interac- tions have been proposed, there are no objective evaluations to determine their impact on the perceived UX. In this work, we evaluated 6 mobile UX smells (3 from the literature and 3 new proposals) with respect to efficiency in use. We conducted an online evaluation with 72 participants in 3 real websites, each one with a set of specific mobile UX Smells. In this evaluation, we compared each website to a refactored version of it- self, i.e. with proposed fixes for each of the smells. To do this, we ran a between-subject experiment in which participants completed 10 every- day tasks on the websites while we measured their efficiency in terms of task completion time and number of user interaction events. As a comple- mentary post-hoc analysis, we also grouped temporally close interaction events into interaction bursts, providing an additional efficiency-related perspective. All the captured metrics were compared in the default ver- sion of the websites vs. their refactored counterparts. Results showed that in most cases (15/20), either the time to complete the task or the amount of interaction events were higher in the presence of UX smells. Moreover, in 7 of the cases, the observed differences were statistically significant (p<0.05). The burst-based analysis was consistent with these trends. - Documento de conferencia
Acceso Abierto You Are What You Click: Web Interaction Analysis for User Profile Detection(2025) Loza Bonora, Leonardo Germán; Grigera, Julián; Garrido, AlejandraEvaluation of web user interaction serves various purposes like analysis and evolution of UX, but it requires significant resources. To reduce the time and cost associated with such assessments, several automated solutions have been developed to analyze interactions by capturing logs. However, many of these approaches assume that all users interact similarly, disregarding individual characteristics such as mouse and keyboard movement speeds. Additionally, they often overlook the time required for analysis. We propose that identifying a user’s interaction profile can enhance the quality of automated log analysis. To achieve this, in this proposal interactive user profiles on the web will be studied and defined. Through experimentation, we will analyze real user behavior and its relationship with these profiles. Finally, the detection of user profiles and interactive characteristics will be automated, considering key variables such as detection speed and prediction accuracy. - Documento de conferencia
Acceso Abierto SIDTER: Prototype Early diagnosis system for respiratory diseases assisted by AI with human supervision in the process(2026) Manquillo, Juan Sebastián; Muñoz Carvajal, Sebastián; Giraldo Muñoz, Juan Diego; Restrepo, Yeison Daniel; Beru, Robert Alejandro; Mogollon, Yilmar; López Erazo, Oscar Santiago; López Erazo, Juliana Maria; Delle Ville, Juliana; Muñoz, Luis Freddy; Antonelli, Leandro; Collazos, CésarHuman health is a fundamental pillar of individual and collective well-being, as it determines people’s ability to reach their potential, contribute to social progress and carry out daily activities. According to the World Health Organization (WHO), health implies not only the absence of disease, but also a complete state of physical, mental and social well-being. Respiratory diseases such as influenza, the common cold, COPD, asthma, pneumonia and allergic rhinitis significantly impact human health by compromising respiratory function, generating acute symptoms and causing chronic complications. These conditions reduce physical capacity, impair quality of life and generate socioeconomic burdens. Early and accurate diagnosis is essential to mitigate their impact, as diseases such as COPD affect more than 200 million people worldwide. However, challenges such as limited access to medical care, unspecified symptoms, continuous exposure to risk factors and delays in referral to specialized centers still persist. In this context, artificial intelligence (AI) presents itself as a key ally for early diagnosis, improving clinical accuracy and optimizing time-consuming tasks. In response to these challenges, SIDTER is presented: a prototype AI-assisted early diagnosis system for respiratory diseases with medical supervision and validation. It aims to support physicians, improve clinical diagnostic capabilities and strengthen patient-physician interaction. - Documento de conferencia
Acceso Abierto CAMS-F: Extending the Context-Aware Mobile Systems Framework for Cross-Platform Development with Flutter, Firebase, and Google Maps(2025) Herrera Herrera, Nelson; Rivera, Richard; Gomez-Torres, Estevan; Challiol, CeciliaThe growing complexity of mobile ecosystems demands frameworks that simultaneously address cross-platform compatibility (iOS, Android, and web) and advanced context-awareness. This paper presents CAMS-F, an evolution of the Context-Aware Mobile Systems (CAMS) framework, which integrates Model-Driven Development (MDD) with modern cloud services to overcome existing limitations in the development of multiplatform context-aware applications. CAMS-F introduces three key innovations: a domain-specific language (DSL) for declarative context modeling with automated Flutter/Dart code generation; native integration of essential cloud services, including Firebase Firestore for real-time data management, Firebase Cloud Messaging for notifications, and Google Maps API for high-precision geolocation; and Infrastructure-as-Code (IaC) deployment via Terraform or Pulumi for reproducible and scalable cloud provisioning. A logistics case study was conducted to validate the framework's capabilities. The results demonstrate a 35% reduction in development time compared to native approaches, real-time adaptation to IoT sensor data with latencies below two seconds, scalability to support 10,000 concurrent devices, and geolocation accuracy of up to 98% under operational conditions. These outcomes position CAMS-F as a viable and efficient solution for domains requiring robust cross-platform context processing, including smart city infrastructure, logistics optimization, and real-time monitoring systems. By combining enhanced developer productivity through MDD with high operational performance via optimized cloud integration, CAMS-F addresses critical gaps in current cross-platform development paradigms. - Documento de conferencia
Acceso Abierto Evaluating Large Language Models for the Generation of Unit Tests with Equivalence Partitions and Boundary Values(2025) Rodríguez, Martín; Rossi, Gustavo Héctor; Fernández, AlejandroThe design and implementation of unit tests is a complex task many programmers neglect. This research evaluates the potential of Large Language Models (LLMs) in automatically generating test cases, comparing them with manual tests. An optimized prompt was developed, that integrates code and requirements, covering critical cases such as equivalence partitions and boundary values. The strengths and weaknesses of LLMs versus trained programmers were compared through quantitative metrics and manual qualitative analysis. The results show that the effectiveness of LLMs depends on well-designed prompts, robust implementation, and precise requirements. Although flexible and promising, LLMs still require human supervision. This work highlights the importance of manual qualitative analysis as an essential complement to automation in unit test evaluation. - Documento de conferencia
Acceso Abierto Bootstrapping IoT Provisioning with PoMA(2026) Gutierrez, Lucas; Balaguer, FedericoThe proliferation of Internet of Things (IoT) devices across diverse environments demands a robust, user-friendly, and efficient deployment strategy. Conventional setup methods typically involve complex, multi-step procedures that require specialized tools or technical expertise, increasing deployment time, operational costs, and the likelihood of human error. This paper introduces PoMA (Poor Man’s API), a lightweight protocol and accompanying library designed to simplify and accelerate the on-site configuration and initial connection of IoT devices. PoMA relies on three core commands and can operate over localized temporary wireless links—such as Bluetooth Low Energy or temporary Wi-Fi access points—or through Short Messaging Service (SMS). Each communication channel can be configured to different security levels based on the deployment scenario. The proposed solution provides a standardized, simple, and secure foundation for rapid IoT field installation. rapid IoT field installation. - Documento de conferencia
Acceso Abierto A collaborative and pattern-based training approach to knowledge acquisition and decision-making during the design of Software Architectures courses: A case study(2024) Pantoja Yepez, Wilson Libardo; Bibbo, Luis Mariano; Hurtado Alegría, Julio ArielThis article describes a collaborative learning experience on Software Architecture (SA) between Universidad del Cauca (UNICAUCA) in Colombia and Universidad Nacional de la Plata (UNPL) in Argentina. The goal was to apply and evaluate training patterns, identifying effective practices for replication in other contexts. During the planning phase, both universities compared learning objectives, curricula, and teaching strategies to find common ground for improving student training. Selected training patterns were implemented, and their impact on professors and students was measured. As an integrating activity, a global development experience was carried out in the final part of the course, merging the work teams of the two educational institutions in a development iteration. The evaluation of this experience focused on the competencies achieved through the training patterns, their perceived usefulness, and ease of use based on the Technology Acceptance Model (TAM). The training addressed industry needs for software architecture design skills despite challenges such as the abstract nature of architectures, prerequisite knowledge, difficulty in recreating realistic project environments, team collaboration challenges, and resource limitations. A catalog of training patterns was proposed to provide quality training. These patterns help simulate industry-like environments and structure architectural knowledge for incremental learning. The ability to make architectural decisions is developed over time and through multiple project experiences, emphasizing the need for practical, well-structured training programs. - Documento de conferencia
Acceso Abierto MilkFlow - Monitoreo inteligente de datos lecheros: una solución basada en IoT y aprendizaje automático(2025) Medina Perafan, Jarol Herney; Moncayo, Sebastián; Cabezas, Jojan; Rodriguez, Hugo; Melenje, Salomón; Garces, Andres; Giraldo, Michael; Anama, Jonathan; Chanchi, Eric Daniel; Bolaños Zuñiga, Andres Felipe; López Erazo, Oscar Santiago; Muñoz, Luis Freddy; Ortega Erazo, Juan Camilo; Delle Ville, Juliana; Antonelli, LeandroMilkflow es una plataforma inteligente diseñada para optimizar y mejorar la forma en que se gestionan los procesos productivos dentro de las lecherías. Reúne en un sistema todos los datos e información clave sobre salud, raza, peso, producción de leche y calidad, brindando a los productores una visión completa y actualizada de su lechería. El proyecto propone una solución basada en Inteligencia Artificial (IA) e Internet de las Cosas (IoT) para fortalecer la autonomía y sostenibilidad de los productores. A través de sensores IoT, el sistema monitorea variables como temperatura y humedad para evaluar las condiciones del entorno, mientras que algoritmos de IA predicen la producción de leche, que ayuda a la toma de decisiones. Con una interfaz intuitiva y funcionalidades adaptables, MilkFlow impulsa una gestión moderna y eficiente, contribuyendo a la transformación digital del sector ganadero. - Documento de conferencia
Acceso Abierto Hoja de ruta para aprender computación cuántica(2025) Tomatis, Facundo; Miglierini, Facundo; Rosenfeld, Ricardo; Fernández, AlejandroLa computación cuántica surge como un paradigma de procesamiento de información radicalmente distinto al clásico, al apoyarse en fenómenos propios de la mecánica cuántica —como la superposición y el entrelazamiento— para operar con cubits en lugar de bits. Los recientes avances en el desarrollo de computadores cuánticos han despertado un creciente interés entre estudiantes, docentes, investigadores y profesionales de la informática clásica. Estos se enfrentan a desafíos únicos, no solo por la incipiente madurez de la tecnología cuántica, sino también por la necesidad de ampliar su formación en varios frentes. Comprender el álgebra y la física subyacentes, abordar nuevas nociones de complejidad computacional y explorar dominios de aplicación en los que la computación clásica tiene poca presencia son algunos de los principales retos que deben afrontar. En respuesta a estos retos surge una oferta de literatura y de propuestas educativas que, además de dinámica, es muy variada en enfoque y nivel de complejidad. Definir y sostener un recorrido de aprendizaje ajustado a las expectativas y bases de cada individuo constituye un primer desafío, a veces inexpugnable. En este artículo se presentan avances en pos de entender mejor dicho desafío, tomando como base las experiencias de dos estudiantes avanzados de grado de informática que abordaron el tema mediante estrategias y fuentes de consulta distintas.Dicho análisis busca extraer lecciones sobre los métodos de apropiación de conocimientos en este campo emergente de la informática, con especial énfasis en estudiantes provenientes de la computación tradicional. - Documento de conferencia
Acceso Abierto Assessing the Migration from FaaS to IaaS: Cost, Performance, and Challenges in AWS(2025) Casaburi, Julián; Urbieta, Mario Matías; Firmenich, SergioIn cloud-native environments, service model selection is crit- ical for optimizing both operational and economic outcomes. This study investigates the migration from a serverless Function-as-a-Service (FaaS) model, specifically AWS Lambda, to a monolithic solution deployed on Amazon EC2. We examine this transition to evaluate cost savings, per- formance improvements, and architectural considerations across various scenarios. Our findings indicate that migrating to Infrastructure-as-a- Service (IaaS) can offer notable cost benefits in specific contexts, though it also introduces infrastructure management requirements. This work provides insights into migration decisions and practical considerations when transitioning from FaaS to IaaS-based models. - Artículo
Acceso Abierto Lineamientos para la construcción de dispositivos de ciencia participativa en ríos urbanos con una mirada desde el sur global(2026) Torres, Diego; Katzer, Leticia; Cochero, Joaquín; Dalponte Ayastuy, MaríaLa ciencia participativa, también llamada ciencia ciudadana, es una práctica de ciencia abierta en la que personas con y sin afiliación a instituciones científicas colaboran en un proyecto científico. Es muy utilizada para el relevamiento de diferentes variables en ciudades y particularmente en ríos. Varios proyectos de ciencia participativa a nivel global utilizan dispositivos digitales para llevar a cabo la producción de conocimiento, principalmente usando los teléfonos inteligentes como herramienta tecnológica de vinculación. Sin embargo, existen desarrollos regionales en Latinoamérica que se posicionan en un nicho similar y que su construcción se realiza desde el registro de los países y proyectos propios del sur global. ¿Cuáles son los registros propios del sur global? ¿Cómo poder pensar lineamientos para dispositivos que reflejen las motivaciones y preocupaciones del "Sur global”? Este trabajo presenta una reflexión epistemológica-metodológica con una serie de guías para poder enriquecer a la ciencia participativa desde un análisis conjunto con la etnografía colaborativa situada a través de cinco categorías: agentividad, co-construcción, colectividad, interinstitucionalidad, e instrumentación. Así nos preguntamos: ¿De qué manera la etnografía colaborativa puede diversificar y enriquecer las formas de la ciencia participativa? ¿Qué características específicas del sur global proponen una impronta particular a la construcción científica participativa? ¿Cuántas de estas características pueden ser incorporadas y de qué forma en un dispositivo digital? En este trabajo se realiza un análisis sobre diferentes dispositivos digitales propios del sur global.. - Artículo
Acceso Abierto Yahp!: Yet Another Haptic Probe(2026) Tau, Martín Ezequiel; Gutierrez, Lucas; Rodríguez, Andrés; Balaguer, FedericoCharacterizing the relationship between vibratory stimuli and user responses is a complex challenge due to varying skin sensitivity across body areas and the onset of stimulus saturation. Achieving an optimal balance between body location, actuator types, and haptic cues is often a demanding and error-prone process. This paper presents Yahp! (Yet Another Haptic Probe), an open-source tool developed through a collaboration between the National University of La Plata and Stream S.A. to systematically design and execute user perception tests for industrial haptic alerts. Yahp! facilitates the evaluation of actuator settings and body locations through a modular architecture consisting of formal experiment definitions, a results database, a mobile trial director, and a generic haptic device utilizing a low-level messaging protocol. To demonstrate the tool’s utility, we present two experiments focusing on haptic bracelets and sleeves. Our preliminary results indicate that while 10% vibration intensity is consistently below the detection threshold, higher intensities are reliably perceived within an average of 3.5 seconds. Furthermore, the studies revealed significant detectability asymmetries during intensity transitions and confirmed the impact of sensory saturation on cue recognition. These findings suggest that Yahp! is an effective platform for defining the symbolic language of haptic interfaces in real-world applications. - Artículo
Acceso Abierto Explicabilidad en algoritmos de búsqueda cuántica en hipercubo con valores de Shapley(2025) Pezzin, María Cecilia; Pons, Claudia Fabiana; Bibbo, Luis MarianoEste trabajo analiza la explicabilidad del algoritmo de búsqueda basado en caminatas cuánticas acuñadas sobre el hipercubo, integrando la metodología SMEF-E (Shapley–Matrix Explainability Framework – Energy). El enfoque combina teoría de juegos cooperativos con funciones de valor Hamiltonianas, con el fin de atribuir la contribución funcional y energética del oráculo, la moneda de Grover y el operador flip-flop durante la evolución del algoritmo. La descomposición mediante valores de Shapley permite interpretar de manera cuantitativa cómo se genera la interferencia constructiva y cómo se redistribuye la energía a medida que se alcanza la probabilidad de éxito óptima. Los resultados experimentales validan los modelos teóricos y aportan transparencia sobre los mecanismos internos que sustentan la ventaja cuántica en búsqueda espacial. - Documento de conferencia
Acceso Abierto Rule-Based Matching for Real Estate Features Detection(2025) Ibañez Gutkin, Mateo Agustín; Pagano, Álvaro A.; Bazzana Tanevitch, Luciana; Torres, DiegoMost of the information about real estate for sale in the Buenos Aires province, Argentina is unstructured, which means that it does not always follow the same format, making extraction a challenging process. Variability in wording, human errors, noise, and incomplete data further complicate the task. Given the large volume of information available, automated techniques are required to transform unstructured text into structured data. This article presents an approach to extract attribute-value pairs from the information contained in the property listings for the province of Buenos Aires, in order to incorporate this data into a knowledge graph. The approach uses pattern-based information extraction for 17 features with an exhaustive evaluation over two datasets: a ground truth labeled by experts and a dataset containing a real-world use case. The results demonstrates accurate values. - Documento de conferencia
Acceso Abierto Inteligencia artificial y blockchain: impactos en la mejora de la seguridad en plataformas Fintech(2025) Ibarra, Gabriel Alejandro; Gindre, FranciscoLa convergencia de inteligencia artificial (IA) y blockchain está revolucionando el sector Fintech al ofrecer soluciones innovadoras en seguridad, cumplimiento normativo y transparencia operativa. Esta revision sistemática de la literatura abarco 667 estudios publicados entre 2010 y 2024, seleccionando alrededor de 175 artículos relevantes. Los resultados preliminares resaltan que estas tecnologías permitiría optimizar procesos críticos como ‘Know Your Customer’ (KYC) y la prevención de fraudes, aunque enfrentan limitaciones en escalabilidad e interoperabilidad, así como desafíos regulatorios. El objetivo de trabajo es proporcionar una perspectiva integral sobre el impacto actual y futuro de estas tecnologías en Fintech. - Documento de conferencia
Acceso Abierto CAMS-X: Extending the Context-Aware Mobile Systems Framework for Cross-Platform Development with Ionic(2025) Gómez-Torres, Estevan Ricardo; Bernis, Christian P.; Valdivieso, Wellington; Baldeón Andrade, Alexander Omar; Challiol, CeciliaThe rapid evolution of mobile applications has led to an increasing demand for solutions that can operate seamlessly across multiple platforms, including iOS, Android, and web, while maintaining context-aware capabilities. In response to this need, we present CAMS-X, an extension of the Context-Aware Mobile Systems (CAMS) framework, designed to simplify the development of cross-platform, context-aware applications using Ionic. CAMS-X leverages a Domain-Specific Language (DSL) for modeling contextual information and business rules, while automating code generation for multiplatform applications through Ionic and Angular. The framework integrates cloud services such as Azure Maps for geolocation, IoT Hub for sensor data management, and Twilio for contextual notifications, ensuring consistent functionality across platforms. Additionally, CAMS-X employs Infrastructure-as-Code (IaC) tools like Pulumi and Terraform to automate cloud resource provisioning, reducing deployment complexity and improving scalability. A case study on package tracking demonstrates CAMS-X's ability to dynamically adjust application behavior in real time based on contextual data from IoT sensors and geolocation services. Evaluation results show a 40% reduction in development time compared to traditional methods, with support for up to 10,000 IoT devices simultaneously. CAMS-X represents a significant advancement in the development of intelligent, cross-platform mobile applications, offering a robust and flexible solution for industries such as logistics, smart cities, and real-time monitoring. Future work includes expanding support for additional IoT capabilities, integrating AI-driven decision-making tools, and further enhancing the DSL to support more complex use cases. - Artículo
Acceso Abierto Systematic mapping of non-functional requirements and their impacts in architectures for artificial intelligence(2026) Astaiza, Yefry; López Erazo, Oscar Santiago; Muñoz, Luis Freddy; Delle Ville, Juliana; Maltempo, Giuliana; Antonelli, Leandro; Hurtado, Julio Ariel; Collazos, Cesar; Ruiz, Pablo; Agredo, VanessaArtificial intelligence (AI) is a branch of computer science that seeks algorithms capable of learning, reasoning, adapting, and performing tasks in a human-like manner. Software is determined by a set of functional requirements (FRs) and non-functional requirements (NFRs). NFRs, such as scalability, security, performance, and usability, define how a system should function beyond its basic functionalities. The architecture must be designed to meet these NFRs, ensuring system efficiency and reliability while maintaining a flexible and modularstructure.Project-specific requirements, technological advancements, and the domain greatly influence the variety of NFRs and architectures that will be essential for the development of AI-based systems. Selecting an appropriate architecture is a processintrinsically guided by the prioritized NFRs. This systematic mapping seeks to provide the NFRs, architectures, and how these impact the selection of architectures for AI-based systemsand a taxonomy. Theevidence gathered shows that NFRs tend to prioritize security, scalability, and accuracy. At the architectural level, there is a similar trend toward patterns such as microservices and lambda. Finally, in terms of impact, microservices is highly influenced by reliability and scalability, workflow orchestration by transparency and explainability, and federated learning by sensitive data security. - Artículo
Acceso Abierto Aceptación e integración de ChatGPT en la educación universitaria: análisis de percepciones docentes en la carrera de Ingeniería Agronómica y estudiantiles en la asignatura Microbiología Agrícola y de los Bioinsumos de la UNNOBA(2025) De Benedetto, Juan Pablo; Pons, Claudia FabianaEste trabajo se inscribe en un perfil de investigación-acción, al implementar una intervención pedagógica en el aula y relevar sistemáticamente las percepciones de estudiantes y docentes sobre su desarrollo. En este marco, se analiza la aceptación e integración de ChatGPT como herramienta pedagógica en la educación universitaria, a partir de una experiencia concreta desarrollada en la Universidad Nacional del Noroeste de la Provincia de Buenos Aires (UNNOBA). Se aplicóuna actividad práctica con estudiantes de Microbiología Agrícola y de los Bioinsumos, y una encuesta a docentes de la carrera de Ingeniería Agronómica. Los resultados indican que los estudiantes valoraron positivamente la utilidad, precisión y facilidad de uso de ChatGPT, destacando su aporte a la comprensión de conceptos, el análisis crítico y el trabajo en equipo. Por su parte, los docentes mostraron mayor cautela, con menor frecuencia de uso y preocupaciones vinculadas al plagio y a la dependencia tecnológica. Sin embargo, reconocen el potencial de la herramienta y expresaron interés en recibir capacitación. La investigación evidencia una brecha entre el entusiasmo estudiantil y la apropiación docente, y resalta la necesidad de acompañamiento institucional y formación crítica para una integración efectiva de la inteligencia artificial en el ámbito académico.