Training in Digital Pedagogy and AI Integration for Educators
This 36-hour, 12-week training programme is designed for educators who want to move beyond traditional teaching models and redesign their practice for the realities of the digital and AI era. The course integrates cutting-edge pedagogy, cognitive science, Universal Design for Learning (UDL), and practical AI tools, guiding participants step by step from theoretical foundations to concrete digital products and a re-engineered course of their own.
Across the first six weeks, the focus is on the pedagogical transformation required in 21st-century education. Participants begin by critically examining how current schooling structures misalign with learner cognition, societal demands, and AI-mediated environments (Week 1: Rethinking Teaching and Learning in the 21st Century). They then learn to design robust learning descriptors aligned with Bloom’s Taxonomy, EQF levels, and DigComp (Week 2), grounding their courses in measurable, competence-based outcomes. Building on this, the course explores what neuroscience and learning sciences tell us about attention, memory, motivation, and emotion in learning (Week 3). In Weeks 4–6, participants design Project-Based Learning (PBL) experiences, explore authentic assessment strategies, and apply Universal Design for Learning (UDL) principles to support variability, accessibility, and equity in their classrooms.
From Week 7 onward, the course transitions into the digital and AI integration strand. Participants are introduced to AI tools for course design (Week 7), including how to use AI to support curriculum mapping, activity design, and differentiation. In Week 8, they explore AI for assessment and feedback, experimenting with tools that can support formative feedback, rubric-based evaluation, and reflective prompts while maintaining academic integrity and ethical use. Week 9 focuses on AI-assisted content creation, where participants design multimodal learning resources (texts, visuals, interactive materials) that enhance learner engagement. In Week 10, the emphasis shifts to AI in research support, from literature scanning and idea generation to structuring research questions and analysing data responsibly. Week 11introduces AI-supported video creation, enabling educators to design short instructional or explainer videos to embed in their courses. Finally, in Week 12, participants learn how to design and structure e-portfolios, both as a personal professional showcase and as a pedagogical tool for their own students.
Throughout the programme, the methodology is explicitly Project-Based Learning (PBL). Participants do not only hear about innovation; they practice it. Each week, they complete small, practice-based digital tasks (e.g., rewriting learning outcomes, drafting a PBL unit, designing an authentic assessment, creating AI-assisted content). These weekly outputs feed into a capstone project: the re-engineering of a course they currently teach, aligning it with 21st-century pedagogy, UDL, PBL, authentic assessment, and AI integration.
Final Outputs and E-Portfolio
By the end of the course, each participant will:
- Submit a structured e-portfolio documenting their learning journey, including:
- Redesigned learning outcomes aligned with Bloom, EQF, and DigComp
- A PBL-based course unit or module
- An authentic assessment plan (with rubrics and/or criteria)
- Evidence of applying UDL principles
- AI-assisted materials (course design artefacts, feedback prototypes, content, videos)
- Present a re-engineered version of a course they teach, showing:
- How the course has been transformed to match 21st-century pedagogical principles
- How AI tools and digital resources are meaningfully integrated
- How assessment and evidence of learning are captured through authentic tasks and e-portfolios
This training is not a generic “tools workshop”; it is a coherent, research-informed redesign journey that supports educators in becoming confident, critical, and creative users of AI, while grounding all digital innovation in solid pedagogy and learning science.


