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“En glad maskin” – erfarenheter av svenskspråkiga robotar i…

Välkommen att ta del av erfarenheter och reflektioner kring sociala robotar på svenska i vården tillsammans med Åbo Akademi/Experience Lab och Arcada.

Åbo Akademi/Experience Lab och Arcada har i drygt två års tid samarbetat kring projektet MäRI (Människa och Robot-Interaktion) som strävat efter att ta fram evidensbaserad kunskap kring hur vårdtagare och vårdstuderanden upplever mötet med en social, humanoid robot. Projektet finansieras av Svenska Kulturfonden.

ENG:

Welcome to explore experiences and reflections on social robots in healthcare in Swedish, together with Åbo Akademi/Experience Lab and Arcada.

For over two years, Åbo Akademi/Experience Lab and Arcada have collaborated on the MäRI project (Human and Robot Interaction) which aimed to develop evidence-based knowledge on how care recipients and healthcare students perceive interactions with a social humanoid robot. The project is funded by the Svenska Kulturfonden.

Den 11.5. 2022 berättar vi om arbetet i Märi på flera sätt – på förmiddagen håller vi ett livestreamat webinarium och på eftermiddagen ges du möjlighet att fysiskt bekanta dig med robotarna och den applikation som skapats. I Vasa kan du komma till Experience Lab och i Helsingfors till Arcada.

Dagen av avgiftsfri, men kräver anmälan.

Webinarium 11.5. kl 09.30-11 på YouTube, https://www.youtube.com/user/mediacityfinland

Program

Introduktion till samarbetsprojektet Märi -sociala robotar som agenter i vården

Presentation av robotarna och utvecklingsprocessen för att ta fram en applikation för tandvården

  • Flossa – en robotapplikation för tandvården

Mattias Wingren, Sören Andersson, Åbo Akademi/Experience Lab

Dennis Biström, Kristoffer Kuvaja Adolfsson, Johan Penttinen, Arcada

Erfarenheter och reflektioner från projektet

  • Upplevelser av att tala med en svenskspråkig robot – Susanne Hägglund, Åbo Akademi/Experience Lab
  • Hur kan roboten hjälpa? – Christa Tigerstedt, Arcada

Forskare och företagare Linda Mannila ger en kommentar till projektet

Moderator: Yvonne Backholm-Nyberg, verksamhetschef, Åbo Akademi/Experience Lab


Workshops 11.5 kl 13-15

Åbo Akademi/Experience Lab, Strandgatan 2, 65100 Vasa

I  Experience Lab kommer deltagarna att få träffa tre robotar, – Nao, Pepper och Furhat. Deltagarna får interagera med dem och utforska olika användningsfall  i vården för alla de här tre robotarna. 

Du kan välja att delta antingen kl 13-14 eller 14-15. Antalet platser är begränsat pga utrymmets beskaffenhet.

Arcada, Robolab, Jan-Magnus Janssons plats 1, 00550 Helsingfors

På Arcada får deltagarna testa på ‘robot whispering’ i praktiken. Detta betyder att man får insikter hur dessa plattformer fungerar och vad de kan erbjuda idag.  Deltagarna kommer att interagera med tre sociala robotar:  Alf, Snow och Amy.  Deltagarna kommer även att få testa vår FLOSSA applikation.

Du kan välja att delta antingen kl 13-14 eller 14-15. Antalet platser är begränsat pga utrymmets beskaffenhet.

Hela dagen är avgiftsfri, men kräver att du anmäler dig här:

News

Hulis jee me tu nö? (översatt från Malaxmål: hur…

Preliminära resultat från våra studier kring humanoida sociala robotar på svenska i vården visar att det är viktigt för en del österbottningar att robotarna kan förstå dialektala uttryck och att robotarna talar finlandssvenska. Dessvärre finns varken finlandssvenskan eller dialekter med bland de språk som det satsas stort på globalt i utvecklingen av taligenkänningsalgoritmer. I projekten MäRI och TaFiDiAi jobbar vi med att inkludera finlandssvenskar i processen att ta med svenskan i automatiseringen och robotiseringen. I det här inlägget skriver vår kollega Leonardo Espinosa Leal vid Arcada att det är det enda rätta att ta med minoritetsspråken i utvecklingen av interaktiva digitala tjänster, och det redan från start.

Inclusion in Human-Robot interaction 

Artificial intelligence has become the modern paradigm in almost all areas of knowledge. Significant advances in fields like deep neural networks (Goodfellow, 2016) have created algorithms able to rival humans in areas as never before, including vision (LeCun, 1995), language (Greff, 2016), and many others. Nowadays, machines are capable the defeating the human masters on almost any board game (Silver, 2018).  

Performing tasks at the human level means that somehow humans can be replaced or repurposed in less repetitive tasks. Ignoring philosophical or sociological discussions about how this technological revolution can impact, positively or negatively, the human population in the near or far future in general, it is clear that one of the goals of these advances is the creation of fully autonomous and intelligent embodied agents. 

The advances in robotics made by companies such as Boston Dynamics or SoftBank Robotics seem to bring the ancient dreams of creating artificial humanoids into reality. The secret source of these humanoid machines’ success is, apart from the advances in models, hardware, or software, done by highly skilled technical and theoretical experts, the endless homunculus amount of data generated by simple digital users.  

Yes, you muggle! In most cases, the human’s digital footprint has been responsible for creating and tagging data (sometimes on purpose, in others as a side subproduct of our web surfing). Data that have helped train these human-level deep learning algorithms. And here is where the problem arises. Powerful tech companies have expanded their services and products created with inherited inequalities within that data.  

The digital gap among different societies has allowed the creation of biased datasets. Modern estimations argue that more than half the global population has access to the internet; however, studies have shown that digital skills and access vary by region and gender. For instance, a 2019 study showed that 55% of men used the internet in the USA while only 48% of women did so. Moreover, only 44% of the population in the developing world and 20% of the people in the least developed world currently have internet access, in contrast to developed regions where over 85% of people have access. Similar inequalities can be found in other areas, such as age group, education level, and socioeconomic demographic information (Statista, 2019; Pew 2019).  

The landmark moment in the history of deep learning is the ImageNet Large Scale Visual Recognition Challenge (ILSVRC) of 2012, won by Alex Krizhevsky (Krizhevsky, 2012). Here, GPU-powered Neural Networks enter the research sphere. ImageNet was an international contest where several research groups competed by bringing their best computer vision algorithms trying to reach the lowest classification error. ImageNet consists of 14,197,122 images organized into 21,841 subcategories. This dataset was compiled by Fei-Fei Li’s group at Stanford (Deng, 2009). This huge dataset has been the reference and the ground truth for new computer vision developments; however, it has been acknowledged recently that it contains flows and biases (Yang, 2020).  

Other specific fields use a limited number of standard datasets, for instance, in Indoor Scene Recognition (MIT Indoor Scenes or Stanford 3D Indoor Scene Dataset); Face recognition (WIDER Face or IMDb-Face); Autonomous driving (Waymo Open Dataset or Virtual KITTI ). A quick inspection will tell us how western-urban-male-centric biased are these datasets. I encourage the reader to check the site https://paperswithcode.com/dataset, just filter by language to see how English is the dominant language by far, compared to the second in the list. 

It is acknowledged that big tech players: GAMMAs (Google, Amazon, Meta (Facebook), Microsoft, Apple) or BATXs (Baidu, Alibaba, Tencent, and Xiaomi) are, with some academic institutions, the primary source of datasets for training artificial intelligence algorithms. These companies overlap in different digital markets and become active competitors in products and services in the digital world. A quick look at the origin of these giant digital behemoths shows implicitly that, in terms of language, English and Chinese are their main interests. Unfortunately, with its diversity of languages, Europe is lagging behind in developing technological products, exposing its citizens to a new linguistic cybercolonialism. 

Natural Language Processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. The goal is a computer capable of “understanding” the contents of documents, including the contextual nuances of the language within them (Wikipedia, 2021). NLP is expected to become an essential player for improving the experience in Human-Robot Interaction (HRI). In the future, robotic assistants are expected to replace specific human labor or tasks. The success in the interaction between humans and robotic assistants is linked to the inclusion of populations not covered by products with technological limitations in language.  

A local case 
 

Finland is a small country in terms of population. Finnish is the primary language globally; only around 5.4 million Finnish-speaking natives are located mainly in the nordic areas (Kotus, 2021). Different academic institutions have made enormous efforts to develop several NLP products in the local Finnish language (Virtanen, 2019; Hämäläinen, 2021). The second official language of Finland is a regional variant of Swedish. Finland has approximately 296,000 Swedish speakers. Globally, about 9 million people speak Swedish as their first language (Kotus, 2021). Due to closeness with Sweden, the primary candidate for creating services are the tools developed using the Swedish language from Sweden (Malmsten, 2020). Although inside the Finnish Swedish community, there are identified four regions where the Finnish Swedish dialects are spoken (Ostrobothnia, the autonomous island province of Åland, Åboland, and Nyland (Uusimaa)), from these, there are ten identified dialects (Kotus, 2021a).  

Development and study of Finnish Swedish population within Human-Robot Interaction real is a necessary step for developing more inclusive products and services. For instance, a successful campaign named donate your speech was launched in 2020, supported by the Finnish Broadcasting Company (YLE), to encourage Finnish speakers to create a large dataset for training speech recognition algorithms in Finnish (Donate, 2020). Similar initiatives funded by Svenska Kulturfonden have been launched recently, including the MäRI and TaFiDiaAI initiatives led by Arcada and Experience Lab that aim specifically to study and develop products for HRI within the Finnish Swedish speaking population in a Healthcare setup. TaFiDiaAI has been the first initiative for collecting specifically Finnish Swedish dialects (see http://snacka.fi/). More recently, Yle Svenska, supported by Svenska literature, has launched a similar initiative at a significant scale for collecting speech data (Donera, 2021) 

These aforementioned initiatives are the first step for the inclusion of minorities within the Finnish society, there are a lot of challenges ahead, but digitalization and automatization are unavoidable; however, we agree that for an ethical and inclusive future, we need to take into account from the beginning, the creation of products and services that include all populations from scratch. In conjunction with the digital industries, researchers and academia must join synergies to build a more inclusive society where AI benefits all its citizens. 

Bibliography 

Deng, J., Dong, W., Socher, R., Li, L. J., Li, K., & Fei-Fei, L. (2009, June). Imagenet: A large-scale hierarchical image database. In 2009 IEEE conference on computer vision and pattern recognition (pp. 248-255). IEEE. 

Donate your speech. 2020. https://lahjoitapuhetta.fi/ 

Donera Prat, 2021. https://www.kielipankki.fi/news/the-swedish-version-of-the-donate-speech-campaign-has-started-online/ 

Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT press. 

Greff, K., Srivastava, R. K., Koutník, J., Steunebrink, B. R., & Schmidhuber, J. (2016). LSTM: A search space odyssey. IEEE transactions on neural networks and learning systems, 28(10), 2222-2232. 

Hämäläinen, M., Alnajjar, K., Partanen, N., & Rueter, J. (2021). Finnish Dialect Identification: The Effect of Audio and Text. arXiv preprint arXiv:2111.03800. 

Kotus — Kotimaisten kielten keskus (The Institute for the Languages of Finland), 2021. https://www.kotus.fi/en/on_language/languages_of_finland 

Kotus — Kotimaisten kielten keskus (The Institute for the Languages of Finland), 2021a. https://www.kotus.fi/en/on_language/dialects/swedish_dialects_in_finland_7542 

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems, 25, 1097-1105. 

LeCun, Y., & Bengio, Y. (1995). Convolutional networks for images, speech, and time series. The handbook of brain theory and neural networks, 3361(10), 1995. 

Malmsten, M., Börjeson, L., & Haffenden, C. (2020). Playing with Words at the National Library of Sweden–Making a Swedish BERT. arXiv preprint arXiv:2007.01658. 

Pew Research Center: Internet & Technology. (2019). Internet/broadband fact sheet. https://www.pewresearch.org/internet/fact-sheet/internet-broadband/ 

Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., Guez, A., … & Hassabis, D. (2018). A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play. Science, 362(6419), 1140-1144. 

Statista (2020). Internet usage rate worldwide in 2019, by gender and market maturity. https://www.statista.com/statistics/333871/gender-distribution-of-internet-users-worldwide/  

Virtanen, A., Kanerva, J., Ilo, R., Luoma, J., Luotolahti, J., Salakoski, T., … & Pyysalo, S. (2019). Multilingual is not enough: BERT for Finnish. arXiv preprint arXiv:1912.07076. 

Wikipedia (2021). Natural language processing. https://en.wikipedia.org/wiki/Natural_language_processing 

Yang, K., Qinami, K., Fei-Fei, L., Deng, J., & Russakovsky, O. (2020, January). Towards fairer datasets: Filtering and balancing the distribution of the people subtree in the imagenet hierarchy. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (pp. 547-558). 

News

Hippo-resultaten är klara

Nu är resultaten från vår studie om hur lärare och elever upplever de digitala lärmiljöerna och läromedlen som formar de digitala lärstigar som uppstått i covid-19 pandemins kölvatten klar. Du kan ta del av hela rapporten på finansiärens webbsida (på finska):

https://www.mediaalantutkimussaatio.fi/tutkimukset/tutkimushankkeet/hippo-hybridi-oppimispolku/

Här nedan hittar du rekommendationslistorna som projektet gav upphov till på svenska.

News

Co-creating online – what works and what doesn’t?

In March 2020, the pandemic hit and limited face to face interactions. These physical meetings were taken for granted as a basis for co-creation, and had to be re-thought almost over night. This disruption saw the birth of new ways of working together and many distance-based collaborative tools for co-creation were put to use.

It did, however, leave us all with a feeling of uncertainty about the future and the role that open social innovation can play in regional development. But never questioning the need for engaging citizens – just finding new ways of doing it.

More research based good practices are needed to overcome this uncertainty, and that is why our project is now conducting an evaluation of the open social innovation activities in the shadow of COVID-19.

The study is carried out by Experience Lab of Åbo Akademi University in Finland, together with all project partners.

  • So far, developers and innovators have tackled the changed conditions “on the run”, with varying results. As some of the new practices are likely to live on when the pandemic fades, now is the time to take a moment and reflect on our experiences – and then look forward and make use of the best pieces. In fact, the exchange of experience is at the core of developing OSI – which is what OSIRIS is about anyway, project manager Kimmo Rautanen explains.

The study has two parts – a survey among the stakeholders in all partner regions and a semi-structured deep interview with key project staff and stakeholders.

  • The interviews will be conducted over Zoom, and the survey is completely online as well – so the study is an example of virtual co-creation in itself. The main aim is to find out how the participants have experienced working together online, which is critical information when new co-creation processes are designed, says Rautanen.
  • The study will also result in a checklist for moving your co-creation activities online, a list of do’s and don’ts, project member Yvonne Backholm states.

This study will contribute to the understanding of if and how methods of open social innovation and co-creation can move online, thus getting everyone onboard in the post-pandemic recovery towards a green and digital future.

Projects - Finished

DIGI-MODE

The purpose of the DIGI-MODE project is to promote the increased usage of digital tools and in particular Virtual Reality solutions to companies located in Ostrobothnia. This is mainly achieved through the planning, development, demonstrations and validation of so-called digital twins. Three major digital twins will be developed in cooperation with local companies from different business sectors: The manufacturing industry, the real estate and construction sector and the energy sector.

A digital twin is a real-time virtual representation of a physical object or process. Digital twins can visualize data from different types of sensors, such as energy meters, water meters, cameras and other IoT devices. Using digital twins, it’s possible to streamline remote working, cooperation and maintenance. This is something which has grown increasingly relevant over the last few years.

The DIGI-MODE project is a collaboration between the University of Vaasa, VAMK, Novia UAS and Åbo Akademi. The project will make use of the existing infrastructure available at the University of Vaasa, Technobothnia, the Design Centre MUOVA (VAMK) and Experience lab at Åbo Akademi.

Results – Architectural Masser

More information at: http://www.digi-mode.eu/

Projects - Finished

Qvarken Game Lab

One of the biggest challenges in establishing the gaming industry in peripheral areas lies within the startup scene, working in a regional context where there is limited experience and few financiers. By establishing the cross-border competence center Qvarken Game Lab, this gap in the Botnia-Atlantica program area is compensated for.

The project’s focus is on gathering, refining, and advancing knowledge about the gaming industry to strengthen the gaming sector both cross-border and locally. The ambition of this intensive implementation project is for the initiative to develop and establish itself during the project period and then continue to grow independently after the project’s conclusion.

The project’s activities involve coordinating actors in a cross-border competence center for game development to gather education, research, and industry resources to collectively enhance innovation in the gaming industry and its interaction with other sectors and the surrounding society. This is achieved by creating meeting places for creative workshops, working on market-oriented gaming innovations with a focus on concrete results, strategically addressing gender equality issues in the gaming industry, and promoting collaboration between the gaming sector and other industries.

The overall goal and purpose of the project is to stimulate the establishment of a sustainable environment for game development and related activities through collaboration and interaction among project partners within the Botnia-Atlantica region’s innovation system. This is accomplished through various processes:


Establish Qvarken Game Lab

The goal of the competence center Qvarken Game Labs is to foster growth among gaming companies in the regions within the Botnia-Atlantica program area where the industry is currently lacking. This is achieved by networking, enhancing innovation and competitiveness through mentorship and expert knowledge, organizing creative spaces like game jams and hackathons, and working with venture capital to facilitate potential investments.

Research & Education

Qvarken Game Lab aims to strengthen and tailor the education available in the program area to better align with the gaming industry’s needs. This is accomplished through discussions between educational providers and the industry in coordinating the competence center. Relevant research and education are enhanced through collaboration with the competence center to elevate innovation and competitiveness.

This is facilitated through access to the User Experience Laboratory (Experience Lab), where gaming entities gain access to UX design expertise, research-based design methods, as well as equipment and techniques for testing the usability and user experience of their products. This occurs at various stages of development concerning the target audience.

Gender Equality & Inclusion

Qvarken Game Lab advocates for increased gender equality within the gaming industry. Since women are significantly underrepresented in gaming companies, the competence center strategically engages in initiatives to change attitudes and practices related to gender equality within the gaming sector. The focus is on leveraging the innovators, experts, and inspirers present in the regions.

Upon the conclusion of the project in June 2022, the competence center has developed or initiated the following processes:

  • Conducted a pilot initiative connecting a network of actors within the gaming industry, identifying effective methods and processes to enhance the gaming industry’s innovation capacity in the Botnia-Atlantica program area.
  • Strengthened the readiness of innovation system actors to contribute research and expertise to the competence center and to evolve collaboratively.
  • Ensured that gender equality, diversity, and accessibility permeate all parts of the project, contributing to a stronger competence center.

Experience Lab contributes by bringing expertise in user-centered design and research-based knowledge and methods in game development. Moreover, it connects to the growing research in gaming at the university and the networks associated with it.

digitalt på distans Projects - Finished

Digital Innovation Processes at a Distance

The aim of the project is to:

Evaluate virtual co-creation processes based on the needs of regional actors regarding innovation work and open innovation (both process and tools) from a user perspective, and based on this knowledge,

Develop concepts for digitally based co-creation with a good user experience. The concept development will result in concrete tools and processes for implementation and application in various contexts, with examples in the form of validated best practices.

The project includes the following actions:

A preliminary study in the form of interviews with 10-15 key persons in companies and organizations working with innovation and development.

Implementation of 2-3 pilot experiments with tools identified to address challenges in the process.

Compilation of a checklist for virtual innovation processes based on the results.

Presented through a workshop for interested companies and organizations.

The project results in:

Verified knowledge about the user experience of co-creation with digital tools – both the usability of the tools, the content experience, and the social experience – and the processes in which these tools are included.

Improved development processes that consider the needs and expectations of all participants and lead to better results.

This also supports and develops participants’ learning and innovation capacity.

Support in the form of concrete manuals and checklists on how the work is conducted and how to handle challenges along the way, as well as strengthened regional, context-adapted competence that can lead to the development of new services, improvement of existing services, and identification of development opportunities.

Contact us:

Kimmo Rautanen

Yvonne Backholm-Nyberg

Ruxe Projects - Finished

RUXE

RUXE

The project’s objective is to find the best solution for conducting user experience studies of digital solutions entirely remotely. The need for remote testing has arisen due to the pandemic, which has made physical activities, both in the laboratory and on-site at companies, impossible. However, even without a pandemic, this development is essential to find a smooth and cost-effective way for companies and organizations to evaluate their digital solutions before launching them on a global market.

Remote testing also supports the transition to a digital and low-carbon society, where the significance of geographic location decreases.

During the project period, tests of various digital solutions are carried out in collaboration with four companies in the region and researchers in the environment, in the form of pilot studies, to find the solution that best meets the needs and provides the most reliable results to ensure a good user experience of the product/service/solution.

The project is co-financed by the Ostrobothnia Region Association.

Project Leader: Sören Andersson, soren.andersson@abo.fi

Projects - Finished

Speech Recognition for Finnish-Swedish Dialects through Artificial Intelligence –…

Speech Recognition for Finnish-Swedish Dialects through Artificial Intelligence – TaFiDiAi

Åbo Akademi/Experience Lab collaborates with Arcada University of Applied Sciences and StageZero Technologies in a research and development project on the topic of speech recognition of Finnish-Swedish dialects. The project has received funding from the Swedish Cultural Foundation and is led by Arcada.

The goal is to collect open-access speech samples from various Finnish-Swedish dialects in different parts of Swedish-speaking Finland. Based on this data, the project partners develop speech recognition algorithms, which are then evaluated together with Finnish-Swedish end-users.

The purpose is to explore how well the study participants perceive themselves and their dialect to be understood by the system and how reliable and competent they perceive the system to be. The guiding principle is to increase understanding of human perception and usage of robots and automated systems, as this knowledge can contribute to the development of artificial intelligence and its integration into society.

The project is conducted by Leonardo Espinosa at Arcada, Susanne Hägglund and Sören Andersson at Experience Lab/Åbo Akademi, and Thomas Forss at StageZero Technologies.

[SV]

Taligenkänning för Finlandssvenska Dialekter genom Artificiell Intelligens – TaFiDiAi

Åbo Akademi/Experience Lab samarbetar med yrkeshögskolan Arcada och StageZero Technologies i ett forsknings- och utvecklingsprojekt på temat taligenkänning av finlandssvenska dialekter. Projektet har fått finansiering från Svenska Kulturfonden och leds av Arcada. 

Målet är att samla in open-access tal på olika finlandssvenska dialekter på olika håll i Svenskfinland. På basen av den här datan utvecklar projektparterna taligenkänningsalgoritmer som sedan utvärderas tillsammans med finlandssvenska slutanvändare.

Syftet är att utforska hur väl studiedeltagarna upplever sig och sin dialekt bli förstådda av systemet samt hur tillförlitligt och kompetent de uppfattar systemet vara. Ledstjärnan är att öka förståelsen kring människans uppfattning och användning av robotar och automatiserade system eftersom denna kunskap kan bidra till utvecklingen av artificiell intelligens och dess integration i samhället. 

Projektet genomförs av Leonardo Espinosa vid Arcada, Susanne Hägglund och Sören Andersson vid Experience Lab/Åbo Akademi samt av Thomas Forss på StageZero Technologies. 

kulturfonden
games and learning Projects - Finished

Games and Learning – a research based network

While digital games have gained some research interest, there remains untapped potential in terms of learning and education. We see a need to explore research on games to support teacher education in terms of learning in and for the future. The constant development of digital games results in a rapidly shifting environment where all actors are needed to facilitate a research-based understanding of games and learning. 

Through this project, we endeavour to create possibilities for networking and collaboration between relevant actors on a regional, national and international level. 

We aim to strengthen the field of games and learning at the Faculty of Education and Welfare studies at ÅAU through collaboration. We identify research gaps and the needs from those working in the field, strengthen networks as well as design the pilot phase of this research project.  

We also aim to create ecosystems with relevant actors – researchers, teachers/schools/organisations and game developers. Through this project we combine the competence on games and learning as well as other relevant areas at the Faculty of Education and Welfare studies; Experience Lab, Matilda Ståhl’s research as well as other game-oriented research endeavours (e.g., Tandem på spel and Redit).  

The project has two phases: 1) the networking and piloting phase and 2) the implementation phase. Likewise, the project has two main areas – research as well as networking and collaboration, which in turn creates a supportive and engaging environment for developing new ideas.  Through creating a network based is Ostrobothnia with national and international collaborations and networks, we strengthen the research environment and the teacher education at the faculty. Further, as part of the project, we have together with Dr Mariana Rocha (Dublin Technological University) established “Games and Learning – an International Junior Researchers Network”, see more information below. 

Our short-term goal is to create a platform for research on games and learning. In terms of long-term goals, we aim to support the creation of international research projects where the results are employed in teacher education and the educational field at large.  

Research coordinator: Matilda Ståhl, matilda.stahl@abo.fi 

Project manager: Yvonne Backholm-Nyberg, yvonne.backholm@abo.fi  

Project team: Matilda Ståhl, Yvonne Backholm-Nyberg och Joachim Majors
 

Games and Learning – an International Junior Researchers Network 

The network currently consists of around ten members from six different countries, including fresh PhD-students to post-doctoral researchers. We have monthly online seminars where we present current projects and so far, we have looked at drafts for papers, posters as well as games in progress.  

If this sounds like an interesting network you would like to be part of, we are happy to announce that we are accepting new members! However, to be able to maintain a level of trust and constructive criticism during these seminars, we wish to keep the network on the smaller side with active members. Therefore, we ask anyone interested in joining our network to contact either Matilda Ståhl or Mariana Rocha by email (see information below), give a short presentation of yourself and why you would like to be included in the network! 

Matilda Ståhl, Åbo Akademi University 
matilda.stahl@abo.fi 

Mariana Rocha, Dublin Technological University
Mariana.Rocha@TUDublin.ie