Generative Artificial Intelligence as a Tool for Pedagogical Innovation in Higher Education
The course “Generative Artificial Intelligence as a Tool for Pedagogical Innovation in Higher Education” aims to provide comprehensive and in-depth training on generative Artificial Intelligence (AI) technologies, with a specific focus on its application as a tool for pedagogical innovation in the academic context.
Goals
- Understand the underlying concepts and techniques that power generative AI systems, including artificial neural networks, deep learning, and generative algorithms;
- Learn how to use and implement generative AI tools in real scenarios, from creating personalized teaching material to carrying out research projects that use AI to generate new knowledge and skills;
- Use generative AI to create intelligent tutors, automatic feedback systems and personalized e-learning platforms that innovate and improve the teaching and learning experience;
- Integrate elements of gamification and augmented/virtual reality (AR/VR) to make learning more interactive and engaging;
- Acquire skills to train generative AI models, validate and evaluate their performance, and implement continuous improvements;
- Assess the ethical, legal and social impacts of using generative AI in education, including privacy, security and equity issues;
- Encourage collaboration between curricular areas and foster a culture of innovation, using generative AI as a tool to address complex challenges and explore new frontiers of knowledge;
- Reflect on how AI technologies can be used in a sustainable and inclusive way, ensuring that they benefit all learners equitably.
Contents
- Fundamentals of Artificial Intelligence
- Introduction to AI and Generative AI: History, Concepts and Evolution
- Machine Learning, Deep Learning and Natural Language Processing
- Development of teaching skills for the pedagogical integration of generative AI and its tools
- Generative Language Models
- Prompt engineering
- Chatbots: ChatGPT, CoPilot and Gemini
- Practical applications of Generative AI: (re)creation of text and translation
- Practical applications of Generative AI: presentations
- Practical applications of Generative AI: image
- Practical applications of Generative AI: sound and video
- Practical applications of Generative AI: tests and exercises
- Practical applications of Generative AI: research and work support
- Ethical and social reflection on the pedagogical use of generative AI
- Pedagogical innovation with generative AI: case studies and best practices
Methodology
The course is online, combining synchronous and asynchronous classes through CIP e-learning platform. It includes:
- Plenary sessions and hands-on workshops;
- Case study analysis and practice-based experiences;
- Reflective strategies on ethical, conscious, and sustainable uses of generative AI;
- Self-diagnosis of teaching practices, self-reformulation of actions, and final self-reflection.
The approach is dynamic, practical, and centered on the development of academic professionalism
Assessment
Assessment is continuous and includes:
- Diagnostic assessment at the beginning;
- Formative assessment throughout the course;
- Summative assessment at the end.
Final grading (0–20 scale) is weighted as follows:
- Training tasks reflecting the learner’s pathway: 50%;
- Quality of participation in synchronous and asynchronous sessions: 20%;
- Final self-reflection: 30%.
Successful participants receive a certificate issued by the Pedagogical Innovation Centre of the Polytechnic of Porto
Bibliography
- Anderson, T., & Dron, J. (2011). Three generations of distance education pedagogy. The International Review of Research in Open and Distributed Learning, 12(3), 80-97. https://doi.org/10.19173/irrodl.v12i3.890
- Baker, R. S., & Siemens, G. (2014). Educational data mining and learning analytics. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 253-272). Cambridge University Press. https://doi.org/10.1017/CBO9781139519526.016
- Chen, X., Zou, D., Xie, H., Cheng, G., & Liu, C. (2020). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
- Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence Unleashed: An argument for AI in Education. Pearson.
- Queirós, R. (2026). IA e Chatbots: um guia prático ao alcance de todos. FCA Editora. ISBN: 978-972-722-950-5
- Roll, I., & Wylie, R. (2016). Evolution and revolution in artificial intelligence in education. International Journal of Artificial Intelligence in Education, 26(2), 582–599. https://doi.org/10.1007/s40593-016-0110-3
- Tegmark, M. (2017). Life 3.0: Being Human in the Age of Artificial Intelligence. Alfred A. Knopf.
- Woolf, B. P. (2010). Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning. Morgan Kaufmann