91ÇàÇà²Ý

News

FITech Network University's new project increases the network’s capabilities in continuous learning

FITech's new FITech FORWARD project aims to develop the member universities’ ability to create offerings of continuous learning and micro-credentials to meet the current skill needs in the field of technology. Besides Aalto University, also Tampere University, University of Oulu, and University of Vaasa are involved in the project.
Person in front of a laptop.

The project deepens cooperation between universities

The FITech FORWARD project aims to improve the capabilities of FITech’s member universities and their staff to combine research knowledge and education offerings to address the skill needs of individual learners and the engineering fields more broadly.

Aalto University acts as the main implementer of the project. Also Tampere University, University of Oulu, and University of Vaasa are involved in the project. The project started in April 2025, and its content is coordinated by project manager Jaakko Hyytiä, who is part of the FITech team at Aalto University. The project will last until the end of year 2027.

Micro-credentials allow flexible learning

The project develops a model for information management and integration, which will help create paths for micro-credentials and expert development. Micro-credentials are, as the name suggests, short learning opportunities that are shorter than traditional degrees and allow learners to develop their knowledge, skills, and competencies flexibly.

During the project, a unified practice considering national guidelines for identifying micro-credentials will be established at FITech member universities. Additionally, the project will develop a model to integrate continuous learning and offerings of micro-credentials into the teaching planning processes of FITech member universities and the rapid dissemination of new research information.

As a result of the project

  • micro-credentials will become an integral part of the teaching planning processes and research communication in FITech universities
  • university staff will have the expertise and methods to produce micro-credentials in collaboration with other universities
  • learners will find suitable education and benefit from diverse, seamless learning opportunities
  • the Finnish technology industry will benefit from the increased skill level and expansion
     

FITech FORWARD is part of the Innovation and Skills in Finland 2021-2027 structural fund program ESF+ measures, which carry out the national theme of continuous learning. The project is funded by the Northern Ostrobothnia Centre for Economic Development, Transport and the Environment (ELY Centre).

Co-funded by the European Union.

Further information

Jaakko Hyytiä

Project manager
  • Updated:
  • Published:
Share
URL copied!

Read more news

Opiskelijanaisia jäätelöllä Korkeakoulunaukiolla. Kuva: Aalto-yliopisto / Petri Anttila
Studies Published:

Summer digest for doctoral students

Suggestions and reminders for the summer months
Näkymä Otaniemen kampuksen keskiöstä
Campus Published:

Research result: Customer satisfaction with Aalto University campus premises remains high

ACRE assesses the satisfaction of its facility tenants through a customer satisfaction survey. Read about the results of the latest survey.
A person walks past a colourful mural on a brick wall, illuminated by street lamps and electric lines overhead.
Cooperation, Research & Art, University Published:

New Academy Research Fellows and Academy Projects

A total of 44 Aalto researchers received Academy Research Fellowship and Academy Project funding from the Research Council of Finland – congratulations to all!
Two interconnected circular loops; one blue labelled 'Simulation DBTL loop', one brown labelled 'Real-world DBTL loop'.
Awards and Recognition, Press releases, Research & Art Published:

A revolution for R&D with the missing link of machine learning — project envisions human-AI expert teams to solve grand challenges

Samuel Kaski receives ERC Advanced Grant to develop new machine learning that is robust, generalisable and engages human experts.