Jari Jussila & Anne-Mari Järvenpää
Building on the idea that all teachers participate in the research activities of a university, HAMK Design Factory has taken the initiative to integrate research activities into teaching from the very beginning. In 2018, the TULEVA (Future Business Intelligence to Speed Up SMEs’ Business Development) project was launched to increase the resiliency of the business development of small and medium-sized enterprises (SMEs) through future knowledge and business intelligence. In parallel to the research project, a data analytics course was organized for the first time in 2019, where students created solutions for the data analytics challenges of the SMEs involved in the research & development project. This work has continued in the projects VÄLKKY (Green Smart Services in Developing Circular Economy SMEs) and DIVA (Data and Innovation to Support Green Transition in the Food Industry). This article reports some of our key findings on integrating data analytics research into the teaching activities of Häme University of Applied Sciences (HAMK).
Data analytics research and teaching
Digital solutions in the bioeconomy and circular economy are some of the key research areas of the HAMK Smart Research Unit. The projects TULEVA (2018–2020), VÄLKKY (2021–2023) and DIVA (2021–2023) RDI have been integrated into teaching at HAMK Design Factory, especially in the data analytics module. The data analytics module is embedded in the curriculum of the Bioeconomy Engineering Degree Program, but the students participating in data analytics courses have not been limited to that degree program.
During the years 2019–2022, interdisciplinary student teams have been formed from the bioeconomy engineering, sustainable development, electrical and automation engineering, and farming degree programs. In addition, for the last two years, Forssa Vocational Institute Information and Telecommunications Technology students have also participated in the projects.
The integration of research into teaching has been done at many levels. In the TULEVA project, we investigated the data analytics challenges of circular economy SMEs and the opportunities for future knowledge (Järvenpää et al., 2020) and business intelligence (Järvenpää & Jussila, 26.7.2021) to support their business development. This research was done by interviewing and conducting workshops with the SMEs. Based on the interviews and workshops, some of the SMEs participating in the TULEVA project also posed challenges for students to solve in the 2019 edition of the data analytics project.
One important piece of feedback from the SMEs was that companies also need help with the data analytics tools and materials that can support the implementation of data analytics solutions in their company. After the completion of the data analytics project and company interviews, the lessons learned were documented in a lightweight data analytics guide for SMEs (Jussila et al., 2019). The feedback gained from the companies informed the development of the data analytics module for the year 2020.
In 2020, we decided to focus on the data analytics module around the Microsoft Power BI tool to streamline the implementation of the data analytics project results in the participating companies. That year, Loimi-Hämeen Jätehuolto Oy, Cool-Finland Oy, and Envor Group Oy (which was participating in the TULEVA research project at the time) and Stera Technologies Oy published data and data analytics challenges for students to solve. The more systematic and research-based development of data analytics teaching began in 2020 when the HAMK Edu LearnWell research team joined to investigate learning and learning experiences in Design Factory implementations (Lahdenperä et al., 2022). Data analytics research from an industry perspective continued in the VÄLKKY research project that began in 2021. Participating companies in 2021 were Envor Group Oy, Loimi-Hämeen Jätehuolto Oy, Kiertokapula Oy, Stera Technologies Oy and Seniortek Oy. In 2022, the participating companies were Envor Group Oy, Stera Technologies, OlutMylly Oy and Enermix Oy.
Research-informed development of teaching and learning
In the VÄLKKY research project, we have investigated data-driven decision-making in circular economy SMEs (Järvenpää et al., 2021; Järvenpää et al., 2022b), barriers and practical challenges for data-driven decision-making in circular economy SMEs (Järvenpää et al., 2023) and how Design Factory students can support developing the data analytics capabilities of circular economy SMEs (Järvenpää et al., 2022a).
The interviews and workshops conducted with the circular economy SMEs have increased our understanding of the needs of SMEs and have given valuable insight into how teaching can be improved from the perspective of the companies. Most notably, challenges related to transferring the student data analytics project solutions into practice were mentioned by several of the companies. This led to methodological development, where we introduced a new phase in the design thinking for the data analytics process used in student projects. This new phase called share results was added to the typical design thinking process we have used in student projects, and it was added as a requirement for the students to provide instructions on how the prototype can be implemented in the company (Figure 1). The seventh week of the eight-week student projects was reserved for creating the instructions and information package for the company to be able to make use of the solution developed by the students.
In 2022, the companies that distributed data analytics challenges to data analytics projects represented three different research & development projects: VÄLKKY, DIVA and ÄlyKaupunki, which focuses on promoting low carbon in smart city infrastructure by utilizing artificial intelligence. The teaching team consisted of HAMK Design Factory, HAMK Smart and HAMK Bioeconomy Engineering staff.
Key findings on integrating data analytics research into teaching activities
Planning and development of teaching can benefit from research in several ways. The benefits of integrating data analytics research into teaching include:
- Keeping up with recent developments in the field
- Building and deepening relationships with industry
- Understanding the data analytics needs and challenges of the industry
- Finding out what is needed from the company perspective to utilize results and benefit from student projects
- The iterative development of courses and modules based on researched and documented findings
The relatively obvious benefit of the integration of research and teaching is that teachers can keep up-to-date on technological developments in the field. For example, what the most used analytics and business intelligence platforms are, what is new in the platforms and what the most sought-after data analytics skills are by the industry based on studies. Research makes it possible for teachers to build relationships with industry and, by doing projects multiple times with the same company, also deepen those relationships. Understanding the data analytics needs and challenges of the industry requires interaction with the company, which can be significantly increased with research, for example, via observations and interviews of company personnel and ethnographic research. Research is also good for finding out the benefits and value of student projects from the company perspective, which often requires interviews after the student projects are completed. Finally, the iterative development of courses is made easier when teachers have research findings about the student perspective and industry perspective on making projects together.
Research and the development of teaching will continue in cooperation with companies for the fifth time with the data analytics projects in the spring of 2023. The data analytics study module has evolved to meet the needs of SMEs, and with the help of increased customer understanding, it is possible to implement more demanding and useful cooperation with companies. However, the previous experience of collaboration is useful for SMEs as well to be able to design the development challenge better and by doing so, they will get more useful results from the collaboration (Järvenpää at al., 2022a). Funding for the OPTIMA (Logistics Optimization for Material Streams in Circular Economy) project has recently been granted. OPTIMA will provide support for SMEs to utilize data on material flow management and optimization in the years 2023–2024. OPTIMA will be funded by the European Regional Development Fund.
Jari Jussila, D.Sc. (Tech.), is the Director of HAMK Design Factory. Jari Jussila has been co-creating interdisciplinary learning experiences in HAMK Design Factory and School of Entrepreneurship, Business and Technology at Häme University of Applied Sciences.
Anne-Mari Järvenpää holds a MEng degree in Industrial Service Business (2010) and a BEng degree in Information Technology (2005) from the Häme University of Applied Sciences (HAMK), Finland. Her research topic relates to the circular economy and data analytics. She is working as a senior lecturer at HAMK in the Degree Programme in Information and Communication Technology, Bioeconomy.
Jussila, J., Saari, J., Närhi, J., Järvenpää, A.-M. (2019). Data-analytiikan opas pk-yrityksille 2.0. https://www.hamk.fi/wp-content/uploads/2019/01/TULEVA_kevytopas_data-analytiikka.pdf
Järvenpää, A.-M., Kunttu, I., & Mäntyneva, M. (2020). Using foresight to shape future expectations in circular economy SMEs. Technology Innovation Management Review, 10(7). http://doi.org/10.22215/timreview/1374
Järvenpää, A.-M., Jussila, J. (26.7.2021). Datasta apua yritysten toimintaan. Forssan lehti.
Järvenpää, A.-M., Kunttu, I., Jussila, J., & Mäntyneva, M. (April 2021). Data-Driven Decision-Making in Circular Economy SMEs in Finland. In The International Research & Innovation Forum (pp. 371–382). Springer, Cham.
Järvenpää, A-M., Jussila, J., Kunttu, I. (2022a). Developing data analytics capabilities for circular economy SMEs by Design Factory student projects. In L. Bitetti; I. Bitran; S. Conn; J. Fishburn; E. Huizingh; M. Torkkeli; J. Yang (Eds.), Proceedings of the XXXIII ISPIM Innovation Conference “Innovating in a Digital World” [5-8 June 2022]. International Society for Professional Innovation Management.
Järvenpää, A.-M., Jussila, J., & Kunttu, I. (2022b). Data ei vastaa tarpeisiin. Uusiouutiset 5/2022.
Järvenpää, A.-M, Jussila, J., Kunttu, I. (2023). Barriers and practical challenges for data-driven decision-making in circular economy SMEs [Manuscript submitted for publication]. In A. Visvizi, O. Troisi, M. Grimaldi (Eds.), Big Data and Decision-Making: Applications and Uses in the Public and Private Sector. Emerald Publishing UK.
Lahdenperä, J., Jussila, J., Järvenpää, A.-M., & Postareff, L. (2022). Design Factory-Supporting technology students’ learning of general competences through university-industry collaboration. LUMAT: International Journal on Math, Science and Technology Education, 10(1), 127-150. https://doi.org/10.31129/LUMAT.10.1.1672