Clase 1: Indagación y Escritura Académica Asistida con IA (8/4/2026)

Bienvenida y Presentación del Curso

Introducción al Curso

• Paula de Lepiane da la bienvenida a los participantes, agradeciendo su presencia y reconociendo la diversidad de experiencias previas en el ámbito académico.

• Se presenta a Pedro Figueroa como el profesor encargado del curso, quien se conecta desde Río Tercero, Córdoba.

Objetivos del Curso

• El curso se centrará en herramientas específicas para apoyar la investigación y producción académica, especialmente para quienes trabajan en escritura e investigación.

• Se enfatiza que las herramientas no reemplazarán el trabajo académico, sino que servirán como apoyo.

Estructura del Curso

Detalles Logísticos

• Las sesiones serán grabadas y compartidas en un aula virtual; se proporcionarán materiales adicionales durante el curso.

• El curso consta de cuatro encuentros programados para abril, cada uno con una duración de una hora y media.

Actividades Complementarias

• Se mencionan actividades diseñadas para cerrar el proceso de aprendizaje, no solo enfocándose en obtener un certificado.

Enfoque Académico

Interacción y Participación

• Pedro destaca la importancia de crear un ambiente participativo donde se fomente el diálogo abierto entre los asistentes.

• La intención es dejar más preguntas que respuestas a lo largo del curso, promoviendo así una reflexión crítica sobre los temas tratados.

Temas a Tratar

Contenido del Curso

• La primera clase abordará cómo la inteligencia artificial (IA) impacta la producción de conocimiento y sus desafíos asociados.

• Las siguientes clases incluirán indagación efectiva, procesamiento de información y escritura académica asistida por IA.

Inclusividad del Curso

Público Objetivo

• El curso está diseñado no solo para investigadores científicos o académicos, sino también para educadores que participan en procesos de indagación y escritura académica.

Actividades Iniciales

Encuesta Interactiva

• Se propone una actividad interactiva donde los participantes deben identificar elementos esenciales para investigar en contextos académicos mediante una nube de palabras.

Reflexiones sobre Investigación

Resultados Iniciales

• Los participantes comparten diversas perspectivas sobre lo esencial para investigar; se destacan conceptos como fuentes confiables e integridad metodológica.

Desafíos Actuales en Investigación

Impacto de la IA

• La introducción de IA plantea nuevos desafíos tanto externos como internos; es crucial actualizarse ante estas tecnologías emergentes.

Cambio Paradigmático

Integración Tecnológica

• La tecnología no debe ser vista como enemiga; ya forma parte integral de nuestras rutinas diarias y afecta nuestra manera de producir conocimiento.

• Es importante reconocer cómo estas herramientas pueden transformar nuestras prácticas investigativas sin sustituir el juicio humano.

Understanding the Impact of Artificial Intelligence in Education

The Rapid Advancement of Technology

• The rapid evolution of technology allows for the condensation of centuries of knowledge into a video generated by artificial intelligence in under a minute.

Critical Perspectives on Generative AI

• It is essential to approach discussions about generative AI critically and reflectively, recognizing that it is not solely responsible for academic challenges faced by educational institutions.

Defining Artificial Intelligence

• A definition from UNESCO (2019) describes AI as machines capable of imitating human intelligence functionalities such as perception, learning, reasoning, problem-solving, language interaction, and creative production.

Human-like Functionality in Machines

• AI aims to act like humans without revealing its machine nature; it can take various forms but strives to produce results similar or superior to human capabilities.

Interaction with AI in Real-Time Settings

• In virtual meetings, approximately 10% of participants may be machines contributing to the overall interaction and process discovery related to AI definitions.

The Historical Context and Evolution of AI

Origins and Development Timeline

• The concept of artificial intelligence has been discussed since 1956 as the science behind creating intelligent machines, culminating in tools like ChatGPT emerging around 2022.

The Explosion of ChatGPT's Popularity

• Following its launch on November 30, 2022, ChatGPT gained over 100 million users within two months—significantly faster than previous platforms like TikTok or Instagram. This rapid adoption raised questions about its implications for education.

Exploring the Landscape Beyond ChatGPT

Diversity in AI Tools Available

• There exists an overwhelming number of generative AI tools beyond just ChatGPT; resources are available across nearly 450 categories with varying access models (free or subscription-based).

Evaluating Tool Effectiveness

• Users must develop criteria for evaluating which tools serve their needs best while avoiding extremes in judgment regarding their utility or potential harm. Continuous experimentation is encouraged due to ongoing transformations in technology.

Ethical Considerations and Biases in AI

Understanding Biases

• Biases inherent in AI arise from the data they are trained on; this reflects diverse human perspectives rather than being negative traits themselves. Researchers should utilize multiple tools to gain comprehensive insights due to differing biases among them.

Ethical Framework Necessities

• Key ethical considerations include authorship attribution, transparency, validation processes, and ensuring equitable outcomes from AI-generated content before use. These elements are crucial for maintaining integrity within educational contexts.

Practical Applications: Using Generative AI Effectively

Appropriation and Contextualization

• Users must understand how to appropriate generative AI effectively by defining clear objectives for its use while contextualizing information provided by these systems based on specific needs or situations encountered during research tasks.

Verification Processes

• Verifying outputs from generative AI is essential; users should confirm accuracy before relying on generated content for academic purposes or decision-making processes within their work environments.

Engaging with Generative AI: A Practical Exercise

Interactive Inquiry Process

• An example exercise illustrates how one might engage with generative AI by posing complex questions that require nuanced responses rather than simple queries—emphasizing dialogue over mere information retrieval through iterative questioning strategies involving context shifts based on expertise levels sought after during interactions with the tool itself.

Conclusion: Shaping Knowledge Through Collaboration with Generative Tools

• Ultimately engaging deeply with generative tools fosters collaborative knowledge creation where users guide inquiry processes rather than passively accepting initial outputs—transforming interactions into meaningful dialogues that enhance understanding across disciplines.

Exploring the Role of AI in Academic Research

The Nature of AI as a Collaborative Tool

• The discussion begins with the idea that AI serves as a tool for enhancing human capabilities, emphasizing its role in dialogue and knowledge expansion.

• Participants agree on the concept of co-creation, highlighting the challenge it poses to traditional academic practices and the need for active engagement with technology.

Utilizing Chatbots for Enhanced Learning

• Introduction of POE, a platform featuring various chatbots designed to facilitate experimentation with different perspectives and responses.

• POE offers both free and paid versions, showcasing an extensive range of chatbot engines available for users to explore.

Comparing Responses from Different Chatbots

• The speaker notes the vast number of conversational chatbots available, including lesser-known options like Mistral and Deepsek.

• Demonstration of using POE to compare responses from multiple chatbots on the same prompt, illustrating how diverse answers can inform research.

Implications for Academic Integrity

• Emphasizes the importance of controlling chatbot responses by gathering multiple perspectives to enrich academic discussions.

• Highlights that some chatbots offer free access while others require payment, presenting opportunities for varied usage in research contexts.

Challenges in Adapting to New Technologies

• Discussion about subscription models for tools like POE versus single-use platforms like ChatGPT, stressing flexibility in choosing resources based on evolving needs.

• Acknowledgment that rapid changes in technology complicate decision-making regarding which tools to invest in or utilize.

Transformative Potential of AI in Research

• The conversation shifts towards understanding AI's capacity to replicate human-like functions such as deep reflection and complex data analysis.

• Concerns are raised about misinformation generated by AI due to its ability to process large datasets quickly.

Redefining Knowledge Production

• Questions arise regarding whether AI is a replacement or ally within academia; all three roles (replacement, ally, threat) are considered valid perspectives.

• Example provided about academic journals struggling with increased submissions due to AI-generated content raises concerns over quality control.

Paradigm Shift Due to Digital Revolution

• Historical context is given regarding how technology has always influenced research processes but emphasizes that current advancements mark a significant turning point.

Expanding Research Horizons through Interdisciplinarity

• Discusses how AI allows researchers to formulate new hypotheses and democratize inquiry while also risking widening existing inequalities among scholars.

Enhancing Human Capabilities with Technology

• Reiterates that rather than replacing researchers, AI can amplify cognitive abilities and creativity essential for scientific advancement.

Ethical Considerations Surrounding AI Use

• It’s crucial not only to embrace technological advancements but also maintain ethical standards inherent in scientific inquiry.

Navigating Changes in Educational Practices

• Calls attention to necessary adaptations within educational frameworks as they integrate new technologies into teaching methodologies.

Future Directions: Integrating AI Responsibly

• Concludes with reflections on how educators must rethink their approaches toward knowledge production while leveraging generative technologies effectively.