Evaluación sistemática de la eficacia operativa y la experiencia del usuario de chatbots generativos en plataformas ITSM

The accelerated digitalization process has exposed the inadequacy of traditional tool-based IT support. In response, generative chatbots powered by large language models have emerged as a potential solution, although their actual effectiveness remains under debate. This study assessed their impact on ITSM platforms in terms of response time reduction, accuracy, and user satisfaction. A systematic review was conducted following the PRISMA 2020 guidelines, covering studies published between 2021 and 2025 in Scopus, SpringerLink, and Google Scholar. The search strategy incorporated the Boolean operator AND to combine keywords such as chatbot, conversational agent, customer support, customer service, service management systems, virtual assistants, intelligent chatbots, ITSM, operational efficiency, and productivity. Fourteen articles met the eligibility criteria. The analysis showed that chatbots reduced response times by 38 % to 68 %, achieved accuracy levels ranging from 85 % to 97 %, and increased user satisfaction by 12 to 27 percentage points. However, some studies warned that the lack of empathy limits their effectiveness when dealing with complex queries. It is concluded that, although these systems demonstrate promising performance, widespread adoption requires stronger empirical support through standardized metrics and longitudinal studies that reinforce the available evidence.La acelerada digitalización ha evidenciado la insuficiencia del soporte de TI basado en herramientas tradicionales. Ante ello, los chatbots generativos impulsados por grandes modelos de lenguaje se plantean como una solución potencial, aunque su efectividad real aún es debatida. Este estudio evaluó su impacto en plataformas ITSM en términos de reducción de tiempos de respuesta, precisión y satisfacción del usuario. Se llevó a cabo una revisión sistemática bajo el enfoque PRISMA 2020, abarcando estudios publicados entre 2021 y 2025 en Scopus, SpringerLink y Google Scholar. La estrategia de búsqueda incorporó el operador booleano AND para combinar palabras clave como chatbot, conversational agent, customer support, customer service, service management systems, virtual assistants, intelligent chatbots, ITSM, operational efficiency y productivity. Catorce artículos cumplieron con los criterios de elegibilidad. El análisis evidenció que los chatbots permitieron reducir los tiempos de respuesta entre un 38 % y 68 %, alcanzaron niveles de precisión del 85 % al 97 %, y mejoraron la satisfacción del usuario entre 12 y 27 puntos porcentuales. No obstante, algunos estudios advirtieron que la falta de empatía limita su efectividad frente a consultas complejas. Se concluye que, si bien estos sistemas muestran un desempeño prometedor, su adopción generalizada requiere mayor respaldo empírico mediante métricas estandarizadas y estudios longitudinales que fortalezcan la evidencia disponible

Inovasi Aplikasi Whatsapp Dalam Pelayanan Pembuatan Kartu Identitas Anak: Studi Kasus Pada Dinas Kependudukan dan Pencatatan Sipil Kabupatan Tangerang

This study aims to find out how public service innovation is as an effort to improve the quality of public services in making Child Identity Cards (KIA) using the Whatsapp application at the Tangerang Regency Population and Civil Registration Office and to find out the inhibiting factors in the service process for making Child Identity Cards (KIA) in Department of Population and Civil Registration of Tangerang Regency. This type of qualitative descriptive research is used in this study. researchers used a descriptive research pattern. Sources of data used in this study are primary data and secondary data. The data collection methods in this study are as follows, observation, interviews and documentation. The data analysis technique used is data reduction, data display and conclusion. The results of the study show that according to the theory of public service innovation according to Bloch (2010) it is concluded that the product indicators show consistent results. Meanwhile, the process, organizational, and communication indicators show results that are not optimal. Inhibiting factors in improving the quality of services for making Child Identity Cards (KIA) using the WhatsApp application include inadequate facilities and infrastructure, low utilization of technology and low public awareness of MCH ownership

Leveraging Large Language Model as Simulated Patients for Clinical Education

Simulated Patients (SPs) play a crucial role in clinical medical education by providing realistic scenarios for student practice. However, the high cost of training and hiring qualified SPs, along with the heavy workload and potential risks they face in consistently portraying actual patients, limit students' access to this type of clinical training. Consequently, the integration of computer program-based simulated patients has emerged as a valuable educational tool in recent years. With the rapid development of Large Language Models (LLMs), their exceptional capabilities in conversational artificial intelligence and role-playing have been demonstrated, making them a feasible option for implementing Virtual Simulated Patient (VSP). In this paper, we present an integrated model-agnostic framework called CureFun that harnesses the potential of LLMs in clinical medical education. This framework facilitates natural conversations between students and simulated patients, evaluates their dialogue, and provides suggestions to enhance students' clinical inquiry skills. Through comprehensive evaluations, our approach demonstrates more authentic and professional SP-scenario dialogue flows compared to other LLM-based chatbots, thus proving its proficiency in simulating patients. Additionally, leveraging CureFun's evaluation ability, we assess several medical LLMs and discuss the possibilities and limitations of using LLMs as virtual doctors from the perspective of their diagnostic abilities

Agentes virtuales con capacidades cognitivas utilizando IBM Watson

Resumen (castellano) En la actualidad, los avances en la tecnología informática y la creciente globalización por medio de Internet y las redes sociales han obligado a que los comercios tradicionales luchen por digitalizarse, a la par que los comercios online traten de ser cada vez más personales y cercanos a los clientes. En esto consiste el comercio electrónico conversacional, una evolución del ecosistema del comercio electrónico. Hoy en día, los chats automáticos con mensajes estándar no cumplen con los requisitos de unos clientes cada vez más exigentes con sus necesidades a la hora de solicitar alguna clase de servicio (recomendación de productos, atención personalizada y en tiempo real, etc.), y la atención humano-a-humano presenta limitaciones económicas y temporales poco rentables para un negocio. Es aquí donde interviene la principal herramienta que hace posible el comercio electrónico conversacional: los agentes virtuales con capacidades cognitivas. Este Trabajo de Fin de Grado tiene como objetivo principal el diseño y desarrollo de un sistema conversacional, Watson AV, capaz de analizar e interpretar diversos tipos de datos, incluyendo texto no estructurado y audio para interactuar con una persona y proporcionar recomendaciones individualizadas mediante la comprensión de su personalidad, su tono y emoción. El entorno de desarrollo de esta aplicación se basa en los servicios de Watson Developer Cloud alojados en la plataforma IBM Bluemix y ofrecidos a través de una API Rest. La tecnología utilizada incluye, inicialmente, IBM Watson Conversation y los servicios de Speech to Text y Text to Speech. Watson Conversation incluye su propio entorno de desarrollo a través del cual se construye la conversación indicando las intenciones (acciones) a identificar en el diálogo y las principales entidades (objetos o valores) con las que eliminar la ambigüedad en la conversación. Todos estos servicios se integran a través de Node-Red, un entorno de diseño gráfico de flujos de integración basado en node.js que permite desplegar a la aplicación en un servidor web y mantenerla accesible a través de un navegador. Aunque el asistente virtual Watson AV construido en este proyecto está enfocado a un área específica (panel de control de un automóvil), se puede ver como una base adaptativa para la construcción de agentes virtuales dedicados a diversas áreas de la sociedad.Nowadays, progress in information technology and the worldwide growth through Internet and social networks have forced traditional businesses to struggle to digitize, while online shops try to be more personal and close to the clients. This is the conversational electronic commerce, an evolution of the e-commerce ecosystem. Today, automatic chats with standard messages do not get the requirements of increasingly demanding customers with their needs when they request some kind of service (product recommendation, personalized and real-time attention, etc.), and human-to-human care has economic limits that are unprofitable for a business. Here the main tool that makes conversational electronic commerce possible intervenes: virtual agents with cognitive abilities. This bachelor thesis has as main objective the design and development of a conversational system, Watson AV, able to analyse and interpret diverse types of data, including unstructured text and audio to interact with people and to provide individualized recommendations through the understanding of their personality, tone and emotion. The development environment for this application is based on Watson Developer Cloud services hosted on the IBM Bluemix platform and offered through a Rest API. The technology used initially includes IBM Watson Conversation and the services of Speech to Text and Text to Speech. Watson Conversation includes its own development environment through which the conversation is built by indicating the intentions (actions) to be identified in the dialogue and the main entities (objects or values) with which the ambiguity in the conversation can be eliminated. These services are integrated through Node-Red, a node.js-based integration flow graphic design environment that allows you to deploy the application into a web server and keep it accessible through a browser. Although the virtual assistant Watson AV built on this project is focused on a specific area (control panel of a car), it can be seen as an adaptive base for the construction of virtual agents dedicated to various areas of society

The Second Conference on Lunar Bases and Space Activities of the 21st Century, volume 2

These 92 papers comprise a peer-reviewed selection of presentations by authors from NASA, the Lunar and Planetary Institute (LPI), industry, and academia at the Second Conference on Lunar Bases and Space Activities of the 21st Century. These papers go into more technical depth than did those published from the first NASA-sponsored symposium on the topic, held in 1984. Session topics included the following: (1) design and operation of transportation systems to, in orbit around, and on the Moon; (2) lunar base site selection; (3) design, architecture, construction, and operation of lunar bases and human habitats; (4) lunar-based scientific research and experimentation in astronomy, exobiology, and lunar geology; (5) recovery and use of lunar resources; (6) environmental and human factors of and life support technology for human presence on the Moon; and (7) program management of human exploration of the Moon and space

Assessment in Conversational Intelligent Tutoring Systems: Investigating the Incremental Value of Dialogue Moves in ElectronixTutor

In conversation-based intelligent tutoring systems (ITS), the student is asked challenging questions and there is a multiturn conversation between the computer tutor and the student in constructing an answer to the question. The initial student response after the question provides some information on what the student knows, whereas follow-up contributions of the student presumably extract more of what the student knows. This dissertation investigates the incremental value of follow-up dialogue moves in a conversation-based ITS, specifically ElectronixTutor, a prototype system that has been used in U.S. Navy electronics training. The research addresses two key questions: (1) What is the added value of follow-up dialogue moves in assessing student knowledge beyond initial responses? and (2) How do prior knowledge, student conversational performance, and curriculum-based test outcomes interact to predict the effectiveness of follow-up responses? The dataset that was analyzed consisted of 139 naval trainees on electronics who answered 34 questions with multiturn dialogues. Results show that follow-up dialogue moves significantly improved the assessment of student knowledge. Further, all learners, regardless of prior knowledge, benefited from these follow-up interactions. The study’s implications extend to ITS design, highlighting the importance of incorporating personalized, adaptive feedback based on prior knowledge and leveraging dialogue moves as core features for tracking knowledge growth. These results contribute to the broader understanding of how ITS systems can emulate human tutoring strategies to improve educational outcomes across various domains

LLM Geo-Chat Interfaces: Designing A Retrieval Augmented Generation (RAG) Model to Improve Large Language Model (LLM) Geographical Understanding, Answer Spatial Queries and Create Scottish Maps

This research explores how RAG Models can improve the Scottish geographical queries of Large Language Models (LLMs). Specifically, how the main created RAG Model GeoBot, which utilises OpenAI’s LLM GPT-4, effectively incorporates geographical data from the Gazetteer for Scotland, improving OpenAI’s ability to identify local landmarks and Scottish locations. This is supported by GeoBot’s superior Cosine Similarity and ROUGE scores compared to default GPT-4 and the created comparative no code RAG model Botsonic. However, there are still weaknesses with this approach as GeoBot performs poorly in response clarity and readability, indicating that further improvement is needed to create the strongest RAG Model methodology. GeoBot also demonstrates the viability of map generation in a RAG Model, although again some improvement could still be made to this. These results highlight the potential application of GeoBot for geospatial applications. GeoBot can be accessed through this website: https://www.geos.ed.ac.uk/dev/geobot/main. Password is ‘GIS2025!’. If this does not connect the website is now offline. The full code can be seen in the Technical Report Appendices

Plan de negocios para la implementaci?n de una empresa que brinde un portal web que permita la compra colectiva de bienes

Se presenta la elaboraci?n, dise?o y evaluaci?n del Plan de Negocios para la implementaci?n de una empresa que brinde un portal web de compras colectivas de bienes. El an?lisis ser? realizado para Lima Metropolitana. La propuesta de negocio ofrece al consumidor una opci?n adicional para realizar sus compras. Utilizando el modelo de compras colectivas y las tecnolog?as de informaci?n brinda al consumidor una nueva experiencia de compra con precios competitivos, productos de calidad y seguridad. De esta forma se puede observar que existe un mercado potencial para desarrollar un portal web de compras colectivas en el pa?s, el cual ofrezca productos tecnol?gicos de calidad a precios rebajados, juntando grupos de usuarios que buscan un mismo producto. Para tal fin se han establecido los siguientes objetivos: - Realizar el an?lisis del mercado - Detallar el entorno estrat?gico - Dise?ar el modelo de negocio - Elaborar el plan de Marketing para el negocio - Elaborar el plan de Recursos Humanos para el negocio - Elaborar el plan de Operaciones para el negocio - Elaborar el plan Econ?mico y Financiero del negocio