Strategic focus

Arcada's overall strategic aim is to build Nordic bridges to be globally relevant and to create smart, digital solutions for a dynamic working life. Nordic cooperation for global relevance and smart digital solutions are Arcada’s vehicles to stay relevant in a changing world. AI and machine learning, Health and Welfare as well as Circular Economy are our core fields of research through which we aim to maintain and grow welfare in society.

Researchers

Arcada is a research intensive University of Applied Sciences. Several teachers are currently doctoral candidates at different universities.

Research at Arcada

At Arcada we conduct both basic and applied research. Arcada provides an innovative environment with a focus on research-based innovation for business and the public sectors. We emphasise the connections between research and teaching involving students and the surrounding society in our projects.

We create smart solutions for a sustainable future.

The core areas of Arcada's research are artificial intelligence, health and welfare, and circular economy. We work with both national and international partners to respond to future needs for expertise in smart technology and sustainability.

Laboratory for Trustworthy AI

Artificial Intelligence (AI) presents new opportunities and challenges for our societies. To understand what AI means, we must go beyond innovation to apprehend how to employ decision-making technology in an ethical, mindful, and sustainable way. It is crucial to increase understanding of practices for Trustworthy AI.

MEDA

Media and Education in the Digital Age (MEDA) is a programme that addresses the challenges, risks and opportunities associated to the use of media in the great variety of social practices that are usually included in the broader definition of educational practices.

CP - North

CP-North: Living life with cerebral palsy in the Nordic countries is a research project involving all five Nordic countries.

Teaching and learning of practical skills in social and health care in challenging times

When communities worldwide were closed in the spring of 2020 as the COVID-19 disease pandemic hit the world, the consequences for higher education in Europe were extensive. In a flash, higher education activities were moved online without enough time for neither preparation nor planning. Both students and the universities' staff had to adapt to major changes in daily life. Follow-ups and evaluations showed that the universities coped with the change surprisingly well, but also that the challenges in teaching and learning were many, both for students and staff – this shows the newly Arcada and Ditepract published Best Practice Guide on the topic.

Pedagogical development work

Can Machine Learning aid in finding key factors to improve the Finnish healthcare system?

Finland is in the process of change in our health care system. The Nordic well-fare system is challenged in Finland, for instance, due to difficulties in attracting nurses, changing demographics in Finland, and a general pressure to reduce costs in the whole public sector. This poses severe challenges for the entire healthcare sector. Can Machine Learning (i.e., the subfield of Artificial Intelligence, which focuses on having a machine imitate intelligent human behavior) be used to understand relationships between different critical properties of our healthcare system? Yes, it can! An excellent example of how this can be done is found in a scientific paper by Hu et al. (2020), where the authors investigated nurses' willingness to report errors in a specific geographical area of the US.

Publication