Student-Centred Teaching with Generative AI

Objectives
Develop key competencies for Higher Education teachers to design and implement teaching-learning processes mediated by generative AI, promoting active learning methods and the application of ethical criteria.
At the end of the program, teachers will have redesigned their current courses and created educational assistants with AIGen, making their teaching practices more efficient and active.

Contents
This programme has been jointly designed by the Columbus Association and the Tecnológico de Monterrey teams in response to the growing presence of generative artificial intelligence in higher education and the concrete questions it raises for teaching practice.

Rather than positioning AI as a substitute for teaching, the programme places the educator at the centre of all pedagogical decisions. Generative AI is approached as a flexible tool that can enhance learning design, assessment, and student engagement, only when its use is pedagogically relevant and aligned with learning objectives. Throughout the programme, participants critically examine when, why, and how AI can add value to the learning experience.

The programme is structured in two complementary modules.
- Module 1 focuses on the practical use of generative AI to support active teaching and learning: from educational prompting and activity design to course development and assessment. Participants learn by doing, applying AI directly to their own courses while reflecting on opportunities and risks.
- Module 2 deepens this approach by guiding participants in the intentional design of innovative learning experiences mediated by AI. With a strong emphasis on ethics, context, and student characteristics, this module supports educators in integrating AI tools, such as Tutors and Agents, only when they clearly add value to the teaching and learning process.
Across both modules, the programme is grounded in a shared perspective: AI is a pedagogical resource, not a pedagogical driver. Meaningful integration requires critical judgment, instructional design expertise, and a clear understanding of learning goals. By the end of the programme, participants will be equipped with technical skills and the pedagogical criteria needed to make informed decisions about the use of AI in higher education.

Evaluation | Challenge-Based Approach
To obtain the certificate, participants must complete an evaluation process composed of attendance at synchronous sessions (30%), two exams at the end of each module (35%), and two practical challenges (35%) in which teachers apply their learning directly to their own courses.
Evaluation is closely linked to active participation in the live sessions, where most of the learning takes place through a learning-by-doing approach that combines individual work, group activities, and guided practice.
The programme adopts a challenge-based evaluation model to ensure learning is hands-on, applied, and connected to day-to-day teaching practice: in Module 1, participants use generative AI to optimise teaching tasks such as course design, active learning activities, and assessment; in Module 2, they design a complete learning experience that intentionally integrates an AI artefact, responding to a real contextual need and supported by pedagogical and ethical justification.

Target
Two sessions were scheduled between February and May. The teachers targeted by the training initiative were invited via a dedicated email campaign.