IA para educadores: Herramientas innovadoras que revolucionan la educación

Resumen

Who is this course for?— Educators and researchers seeking to reduce time spent on routine tasks— University instructors looking to diversify classes with digital toolsWhat does the course include?Core Module:

— How neural networks work:

from machine learning to text generation— Avoiding pitfalls:

why AI makes mistakes and how to spot them— Ethical dilemmas:

copyright issues and academic integrity— Prompt engineering workshop:

learning to communicate with neural networksSpecialized module for university educators & researchers:

— Automating routine tasks:

grading assignments, generating tests, designing courses— Replicable examples of AI integration in the classroomThe course features interviews with practitioners sharing real-world experiences of implementing AI technologies in education.What will you learn?Effective AI collaboration:

— Distinguish reliable results from erroneous conclusions— Apply specialized platforms for research and text analysisAutomate routine work:

— Delegate standard (and non-standard) tasks to AI— Structure information and extract dataCreate innovatively:

— Generate personalized assignments— Make the mundane exciting through interactive formatsMaster key tools:

— Generative AI Assistants:

DeepSeek, Perplexity, Qwen, Mistral, YandexGPT, GigaChat, Neuro, LLM Arena.ru— Academic Research Tools:

Scite.ai, Undermine, Litmaps, Research Rabbit— AI-Powered Education Platforms:

Twee, Brisk Teaching, Magic SchoolYou’ll master neural networks not as a trend, but as a practical tool—with full awareness of their capabilities, pitfalls, and ethical boundaries.The course is taught online and includes recorded lectures, tests, and additional materials.Upon completing the course, participants will:

Know:

The fundamental principles of how neural networks operateThe capabilities and key application areas of AI technologies in educationThe limitations and potential risks of using AIThe main categories and examples of modern AI tools for educationPrinciples of effective interaction with AI systems (including the basics of prompt design)Ethical dilemmas and legal aspects related to AI use in academiaBe able to:

Critically evaluate AI-generated results:

distinguish reliable information from erroneous conclusionsFormulate effective prompts to solve various educational tasks using generative assistantsApply specialized AI tools for research activities (literature search, source analysis, visualization of connections)Use AI to automate routine tasks (structuring information, data extraction, test generation, grading standard assignments, course element design)Generate personalized learning materials and assignments with AICreate interactive and creative learning/working formats using AIAssess the feasibility and effectiveness of specific AI tools for solving given educational or research tasksPossess:

Skills in effective interaction with generative conversational assistants for tasks such as:

automated grading, test and assignment generation, course design, and research optimizationProficiency in using research tools for analyzing scientific literature and supporting academic researchCompetence in working with AI-powered educational platforms to optimize teaching practicesMethods for integrating AI tools into the educational process, considering their capabilities, limitations, and ethical normsAn approach to using neural networks as a practical tool while being aware of their boundaries

Programa

• Módulo 1. Introducción al Curso
¿De qué trata este curso?
Introducción. Razones para el Tecno-Optimismo
Introducción. Polaridad Regional de Opiniones
• Módulo 2. Aspectos Psicológicos de Interactuar con IA
Aspectos Psicológicos de Interactuar con IA
• Módulo 3. Fundamentos de la IA
Fundamentos de la Inteligencia Artificial y el Aprendizaje Automático
Conocimiento, Bases de Conocimiento, Grafos de Conocimiento
• Módulo 4. IA Generativa: Modelos de Lenguaje de Gran Escala (LLMs)
Cómo la IA Entiende y Genera Texto
Conceptos Básicos de la Elaboración de Instrucciones para Asistentes de IA Basados en Texto
• Módulo 5. Aspectos Éticos y Legales del Desarrollo y Uso de la IA
Regulación Legal de la IA
Ética y Políticas para el Uso de la IA
• Módulo 6. Generación de Imágenes con IA
• Módulo 7. Uso de la IA en la Investigación. Parte 1
Uso de la IA en Actividades de Investigación sin Violar Requisitos Éticos
Enfoques para Aumentar la Productividad en la Investigación
• Módulo 8. Uso de la IA en la Investigación. Parte 2
Realización de Revisiones Bibliográficas Usando Asistentes de IA
Asistentes de IA para Analizar Textos y Datos Científicos
• Módulo 9. Cómo las Redes Neuronales Apoyan a los Educadores
Preparación de Clases y Diseño de Materiales
Ejemplos de Uso de IA en Clase que Puedes Replicar
• Examen Final

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Impartido por

Anna N. Sytnik , Tatyana A. Gavrilova, Sergey Yu. Sevryukov, and Aleksandra K. Bordunos

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Materias

Artificial Intelligence