Researcher of the Month is a joint publication series of the Faculty of Education's Centres for Research CERLI and CELE, presenting one researcher once a month. In March, Senior Researcher Eero Laakkonen from CERLI takes the spotlight.
I work as a researcher in educational science research projects with a specialization in quantitative research methods. My role includes designing data collection and data processing, selecting appropriate analytical methods, conducting statistical analyses, and interpreting and reporting the results. I also contribute to writing articles and collaborate closely with colleagues in developing the overall research outputs. Typically, I work simultaneously on several projects aimed at producing research articles, covering a wide range of educational levels and themes related to learning, studying, education, and educational systems. The datasets I work with vary depending on each project’s research design: at times I analyze smaller datasets derived from experiments and interventions, while at other times I handle large‑scale survey data or extensive register‑based datasets. The nature of the data strongly influences the choice of analytical methods and the most appropriate way to carry out the analyses.
Working across multiple projects requires careful and deliberate scheduling. Beyond methodological work, I also need to allocate sufficient time to engage with the substantive content of each research topic and to review relevant previously published studies. At times this can be challenging due to the demands of my other work tasks. Similarly, the publication processes of academic journals can be difficult to predict, which occasionally adds further uncertainty to project timelines.
My workdays typically involve processing, analyzing, and modeling research data using various statistical software. My area of expertise is structural equation modeling, which provides a flexible and general framework for applying a wide range of analyses to different types of data. It is also essential in my work to stay up to date with methodological developments, new analytical applications, and software tools—most recently, the use of artificial intelligence as a support for data analysis. My workdays also include meetings with fellow researchers and writing tasks related to publications at different stages of the publication process.
In addition to my research responsibilities, I teach research methods to both undergraduate students and doctoral researchers. I also provide methodological guidance within the faculty for students working on theses and dissertations, as well as for researchers and research projects. Furthermore, I am involved in planning and implementing matters related to our faculty’s IT infrastructure, such as digital environments for staff and teaching spaces, as well as equipment acquisitions.
In my leisure time, I try to make time for exercise and unwind from work, often by reading or watching TV series. During holidays, I enjoy spending time at our cottage, where there is always some building or repair work to do, and our small forest plots keep me busy with brush clearing and maintenance.
My message to researchers planning data collection or analysis: Although research methods and analytical software have advanced considerably, the saying “garbage in – garbage out” still holds true. Ensure, through careful design and advance planning, that the data you collect will yield information directly aligned with your research questions, and verify that its properties are sufficiently representative of the underlying target population.A dataset may be large and contain a great deal of information, yet missing data or poorly functioning measures can make it difficult to use and prevent reliable conclusions from being drawn during the analysis phase. Hence, investing in careful design and data quality pays off in the form of clearer insights and more impactful research.
