Artificial Intelligence Applied to Teaching and Educational Management
General Overview of the Training Course
Dates: From 13th to 17th April 2026
Timetable: 09:00 to 14:00, with a short break in between
Location: Córdoba, Spain
Venue: Avenida del Gran Capitán 12, 2rd Floor
Mode: Face-to-face
Objectives:
- Understand the current role of generative, multimodal, and autonomous AI in education.
- Train teachers to use AI in planning, assessment, and students’ autonomous learning.
- Develop skills in prompt engineering applied to education at three levels: creation, feedback, and study.
- Explore key tools (ChatGPT, Claude, Gemini, Copilot, Diffit, MagicSchool, DALL·E, HeyGen, etc.).
- Critically analyze the ethical, social, and cognitive challenges associated with AI.
- Design activities, teaching units, and resources with AI in a safe and effective way.
Competencies Participants Will Develop:
- Pedagogical integration of generative and multimodal AI.
- Design of advanced educational prompts applied to planning, assessment, and study.
- Critical use of AI: detection of errors, hallucinations, and biases.
- Creation of teaching units, activities, and audiovisual resources.
- Ability to support students in an AI-enhanced learning environment.
- Understanding of the impact of AI on assessment, motivation, and meaningful learning.
- Autonomy in the everyday use of AI to improve teaching practice.
Methodology & Assessment. Materials, Digital Tools & Learning Resources:
Methodology & Assessment:
The course applies a practical, experiential and progressive methodology, condensed into three intensive days, where participants actively learn by doing and reflecting.
Participants experience AI-supported learning from three complementary perspectives:
- Teacher as content creator
- Teacher as guide and evaluator
- Student as AI-supported learner
Learning is structured around:
- Hands-on workshops
- Real classroom scenarios
- Collaborative group work
- Guided reflection and debate
Assessment is formative and continuous, based on:
- Active participation in practical tasks and discussions
- Quality and coherence of AI-assisted educational materials
- Design of assessments (exams, rubrics, feedback) supported by AI
- Critical reflection on ethical use and the evolving role of the teacher
There is no final exam. Learning outcomes are assessed through:
- Practical production
- Peer exchange
- Self-reflection
- Final presentation of a complete AI-integrated didactic unit
Materials, Digital Tools & Learning Resources:
All materials are digital, practical and directly transferable to real educational contexts.
Participants use a curated selection of generative, multimodal and educational AI tools, such as:
- Text & pedagogical AI tools: ChatGPT, Claude, Gemini, Copilot, Diffit, MagicSchool
- Image & design tools: DALL·E, Gemini Image, Canva AI
- Video & avatar tools: HeyGen
- Audio & voice tools: ElevenLabs
- Presentation & content creation tools: Gamma and other AI-assisted platforms
Additional learning resources include:
- Instructor-designed prompts and templates
- Sample didactic units, exams, rubrics and feedback models
- Comparative analyses of AI-generated outputs
- Ethical guidelines and critical-use frameworks
- Accessibility and inclusion examples using AI
All tools are used with a pedagogical, ethical and critical approach, emphasizing:
- Safe and responsible integration
- Inclusion and accessibility
- Avoidance of over-dependence on AI
- Awareness of bias and limitations
All materials created during the course are reusable and adaptable for participants’ own teaching practice.
Day 1 – Introduction, History and the Current AI Landscape
Key Contents
- Brief history of Artificial Intelligence: from early systems to generative AI
- The current AI landscape: generative, multimodal and educational AI
- Opportunities and challenges of AI in education
- Ethical issues: reliability, bias, privacy and misinformation
Practical Activity
Use cases and open debate: “What role for AI in the classroom?
- Group discussion based on real educational scenarios
- Identification of fears, expectations and opportunities
Block 1 – AI for lesson preparation (Teacher as creator)
Participants:
- Explore and compare ChatGPT, Claude and Gemini
- Learn basic prompt engineering for teaching
- Design the first version of a lesson:
- Title and learning objectives
General structure
One learning activity
A simple evaluation rubric
Reflection
What parts of lesson planning can AI support effectively?
What should remain under the teacher’s responsibility?
Day 2 – Fundamentals, Prompt Engineering and Assessment
Key Contents
- Fundamentals of AI and how generative models work (teacher-oriented explanation)
- Prompt engineering applied to education: roles, constraints and refinement
- AI for assessment, feedback and differentiation
Practical Project – Continuation
Blocks 2 & 3 – AI as evaluation assistant and learning support
Participants:
- Create an exam or assessment task based on the lesson designed on Day 1
- Exchange exams between groups
- Act as students and:
Solve the task using AI constructively
Generate multiple student responses (strong, average, weak) using AI
Use a different AI tool to:
Correct answers
Provide feedback
Reflection
Is AI feedback accurate, fair and empathetic?
Would you trust AI fully when assessing students?
Day 3 – Multimodal AI: Images, Audio, Video and Presentations
Key Contents
- Multimodal AI in education
- Image, audio and video generation for teaching
- AI for accessibility and inclusive education
Practical Project – Continuation
Creating non-textual educational resources
Participants enrich their lesson/unit with:
- Visual materials (images, posters, infographics)
- Presentations generated with AI
- Audio or video resources (e.g. short podcast, avatar-based explanation)
Tools may include:
DALL·E, Gemini Image, Canva AI, Gamma, HeyGen, ElevenLabs
Reflection
How do these formats change student engagement?
What are the pedagogical limits of AI-generated media?
Day 4 – Designing a Complete Didactic Unit with AI
Key Contents
- Instructional design supported by AI
- Learning objectives, activities and assessment alignment
- Evaluation strategies in AI-supported learning environments
Practical Project – Completion
Full didactic unit design
- Participants finalise:
- Learning objectives
- Activities and resources
- Assessment and evaluation criteria
- Ethical and inclusive considerations
Each group prepares a short presentation of their unit.
Day 5 – Success Stories, Change Management and Future Perspectives
Key Contents
- Real cases of AI integration in schools and universities
- Managing change in educational institutions
- Resistance, adaptation and teacher leadership
- The evolving role of the teacher in the AI era
Final Activities:
Debate and reflection
- What role should teachers play in an AI-supported classroom?
- What should be encouraged, limited or prohibited?
Personal roadmap
- What will I apply immediately?
- What will I explore further?
Bonus Session
- The Exponential Era of AI: Beyond the Classroom
- Agents, automation and emerging educational scenarios
- How AI is reshaping learning, work and society
Optional Bonus
- Introductory session on AI-powered automation
- Examples with n8n, Zapier and simple AI workflows
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