Online Workshops: AI and Education. Across Seasonal School for Humans and Technology

Del 9 al 13 de novembre se celebrarà a la UdG l’Across Seasonal School on Artificial Intelligence and Education. Aquesta activitat està adreçada principalment a estudiants. Tot i això, es convida al professorat que hi estigui interessat a participar en els workshops online que s’organitzaran.
Si tens interès a assistir a alguna sessió, cal que enviïs un correu a seasonalschool.aieducation@udg.edu per notificar la teva assistència.

Day 1 – November 9th, 2026
Humans, AI, and Cross-Border Education
12:00–13:30 Workshop (online): What Does a Grade Still Tell Us? Assessing Learning
Outcomes in the Era of AI, by Milana Damjenić Mihaldžić (University of Banja Luka)

When almost every university student uses generative AI, a grade no longer speaks for itself. An excellent take-home report may show what a student has learned, what they can produce with a tool, or how well they can direct and check that tool, and the grade alone cannot tell these apart. This online workshop treats the problem as a question of evidence.
Every score is produced under particular conditions, and AI is now one of them. We look at what different kinds of assessment evidence can and cannot support, and why integrity is better secured by design than by detection. We also look at how AI lets us give more weight to students’ process and thinking, including self-assessment and explaining their reasoning, and how to keep assessment transparent and fair.

Day 2 – November 10th, 2026
AI Literacy, Critical Thinking, and Local LLMs
11:30–13:00 Workshop (online): AI literacy and critical use of generative AI, by Borislav
Vukojevic (UNIBL)

Generative AI is already embedded in how students learn and how professionals work, yet most people still use it as a magic answer machine.
This hands-on workshop introduces the 10 Golden Rules of working with generative AI, a practical framework developed through training with journalists, educators, and students across Southeast Europe. Participants test the rules live on a frontier model: probing its limits, spotting hallucinations and bias, and learning to brief AI as an independent expert rather than query it like a search engine.
Working in small groups, they apply the framework to a task from their own field and leavewith a usable artefact and a checklist they can use the next day. No technical background is required.

Day 3 – November 11th, 2026
Physical AI, Robotics, and Learning by Doing
09:00–10:30 Workshop (online): Design Fiction: Artifacts from the AI-media future, by Lewis
Chuang (TUC)

This is a 90-minute online workshop in which you’ll use design fiction to explore how AI may reshape the media we make and consume.
Working in small groups, you’ll set a media domain, an AI development, and a time and place, then build a believable text object (e.g., brochure, news article, terms & regulation, job advert) from that world. Partway through, a surprise twist will challenge your assumptions. You’ll encounter artifacts from each other’s settings as if you had stumbled across them in that future, leaving questions and reactions for their creators. We’ll close with a group discussion on what felt uncomfortably plausible and what these objects reveal about choices we face today. No design or art skills are needed, only curiosity and a willingness to imagine.

Day 4 – November 12th, 2026
AI, Images, Media, and UX
12:00–13:30 Workshop (online): AI agents in higher education: from conversation to
practical workflows, by Borislav Vukojevic (UNIBL)

This hands-on workshop explores how to move from asking AI questions to designing workflows in which AI agents carry out tasks under human supervision.
Through examples from teaching, research, and academic administration, participants will learn to define a goal, provide relevant sources and instructions, connect tools, and establish checkpoints for reviewing results. The session will address the difference between a chatbot and an agent, as well as practical questions of accuracy, privacy, and academic integrity. Participants will map a task from their own work into a simple agent-assisted workflow, identifying what can be delegated and which decisions must remain with a person. They will leave with a reusable workflow outline and a checklist for evaluating its results. No programming background is required.

Participen en l’organització d’aquesta activitat la Facultat de Turisme i l’Institut de Recerca en Turisme