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Coordinating institution: Polytechnic Institute of Maia – IPMAIA

BIP coordinators:

Luís Miguel Barbosa Proença

Célia Maria Martins Soares

Target audience: students from the partner institutions

Virtual mobility period: starting 1 May 2026

Physical mobility period: 6-10 July 2026

Description and objectives

Artificial intelligence (AI) and the intensive use of large volumes of available data (often referred to as “big data") offer a vast array of new business models and opportunities to optimise existing processes. This is not limited to the field of technology or related areas: traditional business sectors, governments, and individuals can also make use of these technologies, for example to diagnose machinery defects, estimate taxes, or find suitable clothing when shopping online.

This wide-scale application will result in a significant transformation of society, as many existing jobs and businesses will become obsolete or, at the very least, change drastically, while at the same time new opportunities emerge.

It is therefore crucial that students from all fields are exposed to these developments at an early stage and encouraged to reflect on the potential changes and limitations of AI and big data. At the same time, the global speed of adaptation varies due to cultural, legal, or other circumstances (such as language), which makes it important to exchange experiences and perspectives internationally.

After completion of the programme, students will:

•  have a more detailed understanding of the possible technological applications and limitations of AI and big data;
•  understand the transformational impact of these trends, both on business and on society as a whole;
•  have developed a perspective on how the economy and the workforce will adapt to these changes and evaluate the consequences;
• be aware of potential ethical conflicts and the risk of discrimination;
• be able to identify secondary effects such as the gaming of systems or changes in implicit social norms.

Methodology

To maximise the learning experience and the positive impact of the intercultural learning environment, strong emphasis is placed on minimising traditional expository methods. As such, following an introductory session, students are assigned to international teams, where they research a given topic under the guidance of the lecturers and collaboratively prepare a compelling presentation. These presentations are delivered on site during the workshop and serve as the basis for further discussion with the other teams. To broaden the experience further, a study visit to INESC TEC – Institute for Systems and Computer Engineering, Technology and Science is planned, alongside additional excursions designed to enrich the cultural experience and encourage discussion on historical developments and potential future changes. The course concludes with a reflective report on the learning outcomes, to be published in a forum that once again provides space for discussion.

This programme offers a variety of benefits beyond the course workload, including:

• networking opportunities for students and lecturers, enabling further exchange and collaboration;
• exposure of students and lecturers to different cultures;
• ​strengthening of formal ties between the participating institutions;
• a diverse learning experience for students, both in terms of methods and content;
• teaching experience for the associated lecturers and trainers.

ECTS awarded: 3

Virtual component of the BIP

The virtual component is designed to provide participants with the necessary theoretical background and collaborative framework to prepare for the on-site activities.

Synchronous online teaching will consist of a series of short lectures and interactive discussions led by academic staff from the participating institutions. Topics will include:

•  introduction to AI and Big Data;
• differences and similarities in relation to previous technological changes;
• societal implications of AI;
• how AI machines learn;
• human and machine decision-making;
• AI-driven storytelling;
• new business models;
• ethical challenges;
• protection of human rights.
  

Participants will subsequently engage in virtual teamwork, combining guided collaboration with autonomous work. International teams will conduct research on one of the assigned topics and prepare a half-day workshop to be delivered during the physical phase.

This virtual phase therefore combines individual preparation, online teaching, and guided international collaboration, ensuring that all participants are well prepared for the in-person component of the BIP.

Final evaluation

• Group presentations (50%)
• Individual report (50%)

Programme workload

Total Workload: 75 hours

• Physical component: 34 h
• Virtual component: online sessions: 4h; online guided team collaboration: 15h
• Autonomous work: 17h
• Individual report: 5h

For further information, please contact gri@maieutica.pt  ​