{"id":259,"date":"2025-09-25T19:37:50","date_gmt":"2025-09-25T18:37:50","guid":{"rendered":"https:\/\/www.everydayinstitute.se\/?p=259"},"modified":"2026-05-13T10:39:07","modified_gmt":"2026-05-13T09:39:07","slug":"2-historical-background","status":"publish","type":"post","link":"https:\/\/www.everydayinstitute.se\/en\/method\/2-historical-background\/","title":{"rendered":"2) A Historical Perspective: How It Began and Its Scientific Roots"},"content":{"rendered":"\n

The methodological journey behind DAS began with equal parts frustration and curiosity. My doctoral studies at Chalmers started in 2009 with a deeply personal question: What had my teachers actually done to me as a student ten years earlier? I had been transformed into an entrepreneur in the haulage industry through a world-unique Master\u2019s programme called the School of Entrepreneurship. The teachers paired my group with an innovator in vehicle diagnostics, which completely changed the course of my life. I became a growth entrepreneur in the transport sector. A decade later, I returned to Chalmers to try to understand why. My job as a doctoral student became to work out why this education had such powerful effects on so many people. But traditional scientific methods frustrated me. Interviews and surveys were not enough to make visible\u2014let alone explain\u2014the powerful identity journeys we saw in practice every year, and which I myself had experienced.<\/p>\n\n\n\n

That’s why I began experimenting with emotion-based digital micro-reflection. The first attempts were small and craft-like. It was initially extremely time-consuming to ask students to write down what they had just done via their mobile phones, how it felt, and why it turned out the way it did. But when we began reading these voices in clusters, we sensed a new kind of close-up science: close to the action, close to the feeling, close to the critical decisions.<\/p>\n\n\n\n

As a doctoral student, I often looked back through history of science to see if others had pointed out a similar path before. There were century-old threads of ideas about practice-based science and design of change, from early pragmatism to modern design science research and action research. There was also a contemporary wave of technology in the form of social media platforms that made it possible to collect many short texts in a steady stream and to respond quickly. From that intersection, a methodology was born with clear steps and a new language for everyday learning.<\/p>\n\n\n\n

This chapter tells the story of how it all took shape and how we can understand it today. The first studies, why we dared to try something of our own, how the roots of ideas stretched backwards and how they bound together theory and practice into a usable whole. Figure 2 below sketches our journey and some of the ideas that carried it forward. The figure shows that two parties besides Chalmers have been particularly important for this journey\u2014Uddevalla Municipality and the Swedish National Agency for Education. Without them, DAS would not exist today. They believed in us when no one else did.<\/p>\n\n\n\n

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Figure 2.<\/em><\/strong>The journey behind DAS.<\/em><\/p>\n\n\n\n

2.1 A Methodological Innovation at Chalmers<\/h2>\n\n\n\n

It all really began with two simple questions to 13 students at the School of Entrepreneurship: How do you feel? Why? Every time something significant happened in their work, we asked them to write a few lines immediately, before memory had time to rearrange the details. In a short time, we had a growing web of micro-narratives that made it possible to follow experiences in real time. When we later analysed the material, we saw patterns that often otherwise remain silent: which situations sparked energy, what provoked, and which events recurred among those who made progress.<\/p>\n\n\n\n

From this grew our first published study, where we could formulate conclusions about the connection between emotionally charged events and the development of different competencies. Somewhere there, DAS was also born: emotional action in a real environment, reflection in the moment, and collective interpretation of recurring patterns. We understood that this could be useful for more people, but only if we held fast to the simplicity of the questions and respect for participants’ voices.<\/p>\n\n\n\n

In Figure 2.1 below from the first published study, we can see how emotional events over time drove the analysis forward and gave us a new kind of detailed overview.<\/p>\n\n\n\n

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Figure 2.1.<\/em><\/strong> This figure comes from the research article “An emotion based approach to assessing entrepreneurial education” published in the International Journal of Management Education in 2014.<\/em><\/p>\n\n\n\n

Read more:<\/strong><\/p>\n\n\n\n

Lack\u00e9us, M. (2014). An emotion based approach to assessing entrepreneurial education. International Journal of Management Education, 12(3), 374-396.<\/p>\n\n\n\n

Lack\u00e9us, M. (2015). Entrepreneurship in Education – What, Why, When, How. OECD Publishing.<\/p>\n\n\n\n

2.2 An Entirely New Educational Research Tradition Took Shape\u2014Value Creation Pedagogy<\/h2>\n\n\n\n

With new glasses, we saw new things. What carried students’ engagement was rarely the dream of their own legal entity in the form of a company to be started, but rather the moments when their work created something that mattered greatly to someone else. When they wrote about these moments, the texts changed tone: the feelings became stronger, the contexts clearer and the lessons deeper. There and then we began to talk about creating value for others as learning, not just as a new pedagogical concept but also as an observable mechanism. When students made their own efforts that helped others, and reflected openly on how it went, a kind of learning emerged that reached further. Figure 2.2 below is from my book about our research on value creation pedagogy<\/em> in primary and secondary schools, and metaphorically illustrates how small actions, rightly placed, can move learning to a great extent.<\/p>\n\n\n\n

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Figure 2.2.<\/em><\/strong> Students creating value for others as a lever for strengthened learning (Lack\u00e9us, 2022).<\/em><\/p>\n\n\n\n

The insight spread and took hold in different environments, far beyond its first home. But what emerged was not only a new pedagogical idea, but also a new scientific method that made it possible to see things previously hidden by overly crude measurements or vague memory images. When the new method was clarified, anyone could begin to study their own practice, discover which actions actually make a difference, and formulate principles for getting more of it. The democratisation of science’s tools lay precisely in this: giving anyone the opportunity to transform everyday work into testable knowledge.<\/p>\n\n\n\n

Read more:<\/strong><\/p>\n\n\n\n

Lack\u00e9us, M. (2022). Den v\u00e4rdeskapande eleven. [The Value-Creating Student].  Chapter 1.<\/p>\n\n\n\n

2.3 How DAS Developed Over a Decade<\/h2>\n\n\n\n

The method took shape layer by layer, as more and more people wanted to try it. From vocational teachers came a sharp focus on action tasks. The doing had to be concrete, feasible and meaningful in everyday life. From university students’ ways of reasoning about their own reflections came the idea of collective analysis, where many anonymised quotes are read together to see new patterns. From collaborations with primary schools, a matrix emerged where action tasks meet tags, first drawn manually in Excel, then generated automatically with a click. In a long-term development process with school leaders who believed in us, support for analysis was gradually built, and later AI functions that could cluster texts and suggest themes and even action plans without replacing human judgement.<\/p>\n\n\n\n

The small details that make the method robust\u2014reasonable rhythm, quick comments, design of content\u2014came from different practical projects with shifting demands. Along the way, an important insight grew\u2014it is the emotional actions that build the hard-to-capture capabilities. When we mapped entrepreneurial competencies, we saw how action tasks that directed attention outward gave faster learning curves than abstract competency lists for learning objectives. When we followed vocational students, the doing became the leading indicator of what they actually learned. The method thus became not just a way to collect data, but also a language for shaping behaviours that lead to deep learning. Table 2.3 below is from research together with my own students and shows which actions best drive the development of the so-called entrepreneurial competencies in the specific context they find themselves in.<\/p>\n\n\n\n

Read more:<\/strong><\/p>\n\n\n\n

Lack\u00e9us, M. (2025a). From EntreComp to EntreAct: Sixteen validated design principles for making people more entrepreneurial In B. Derre & Y. Baggen (Eds.), \u201cEmpowering the next generation of entrepreneurial change agents\u201d. Springer.<\/p>\n\n\n\n

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Figur 2.3.<\/em><\/strong> A matrix showing the connection between what students at Chalmers School of Entrepreneurship are asked to do concretely, and what they learn from this (Lack\u00e9us, 2025a)<\/em><\/p>\n\n\n\n

2.4 How the IT Tool Developed Over a Decade<\/h2>\n\n\n\n

To work with the method at a larger scale required more than good will. The IT tool Loopme was built to more easily collect many short reflections in a social flow and provide space for quick dialogue. The first years were mostly about data collection: lowering thresholds, making it easy to write in the moment, and keeping order with tags and feelings. Gradually, social functions emerged and also different ways to sort, filter and invite.<\/p>\n\n\n\n

A decisive shift came in 2015 when action tasks became mandatory in the design, which made usage more sustainable over time and the data more comparable. During the second decade, from 2022 onwards, the development of Loopme has increasingly revolved around analysis support: overviews that can be generated in seconds, heat maps that show where effects gather, quote clusters that give patterns a human voice, and AI support that saves time without taking command. Over time, we gained more and more synergies when the platform supported both participants’ reflections and leaders’ analytical capacity\u2014it spurred both these parties. We learned that technology’s role is to make the scientific work easier, not bigger. In Figure 2.4 below from a book chapter in an American methods book, we can see how functions and design in Loopme matured over time.<\/p>\n\n\n\n

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Figure 2.4.<\/em><\/strong> Figure from chapter in a scientific methods book (Lack\u00e9us, 2020).<\/em><\/p>\n\n\n\n

Read more:<\/strong><\/p>\n\n\n\n

Lack\u00e9us, M. (2020). Collecting digital research data through social media platforms: can \u2018scientific social media\u2019 disrupt entrepreneurship research methods? . In W. B. Gartner & B. Teague (Eds.), Research Handbook of Entrepreneurial Behavior, Practice, and Process. Edward Elgar Publishing.<\/p>\n\n\n\n

2.5 Trying to Help Each Other in Everyday Life\u2014Roots in Clinical Action Research<\/h2>\n\n\n\n

When I searched for words for what we were doing, I found them partly at home. Our research division at Chalmers has a long tradition of clinical action research<\/em>. For us, it’s about standing close to practice\u2014the “clients”, helping where it hurts for them and simultaneously learning systematically. It’s not only in healthcare that one works “clinically”\u2014everyone who has clients they try to help is fundamentally a clinician. Teachers, lawyers, social workers, architects, consultants and others. Action research gave us a form\u2014many people try different types of actions together, change and understanding grow collectively, and the knowledge is returned to those who created it.<\/p>\n\n\n\n

In DAS, these ideas took a more concrete form. Action tasks became the unit for a helping action, and the reflection afterwards became the clinical journal where we could follow processes, reactions and results. When several groups work in parallel, comparisons become possible without losing context. The collegial conversation moves from the room to the text and back again, and the question shifts from who is right or wrong, to what actually works here and now. The method obliges\u2014helping is the first task, interpretation comes later. That’s precisely why the data becomes better. People notice when the purpose is learning and improvement rather than control and follow-up. See Figure 2.5 below which compares classic action research with our action task-based way of working and how both move in the same direction, but with different tools in hand.
<\/strong><\/p>\n\n\n\n

Table 2.5.<\/em><\/strong> How DAS develops clinical action research as a phenomenon.<\/em><\/p>\n\n\n\n

Classic features of action research<\/strong><\/td>Comparison with DAS<\/strong><\/td>How DAS develops action research<\/strong><\/td><\/tr>
Collaboration between researchers and practitioners<\/strong><\/td>Researchers can participate, but practitioners can also work in scientific ways on their own<\/td>Clarified process removes the requirement that researchers must be involved in the work, which lowers the cost<\/td><\/tr>
Oral learning dialogue among practitioners in focus groups<\/strong><\/td>Written, structured and confidential learning dialogue, with written confidential feedback<\/td>Dialogue documented in writing and more confidential, research becomes more rigorous, time is saved<\/td><\/tr>
There are many different ways to conduct action research<\/strong><\/td>Clear methodological choices, work processes and techniques for data collection and analysis<\/td>Simpler and less diffuse for practitioners to participate, greater chance of making theoretical contributions<\/td><\/tr>
Reflection occurs orally in groups, some time after completed action<\/strong><\/td>Reflection occurs individually, in writing and as soon as possible after completed action<\/td>More reflections become deeper and in the present, and are not coloured by other participants’ experiences<\/td><\/tr>
Focus on problem-solving and dialogue between researchers and practitioners<\/strong><\/td>Focus on experiments and subsequent structured documentation and collective analysis<\/td>Better conditions to meet critics’ high demands for scientific rigour and scrutiny<\/td><\/tr>
A broad flora of different data collection methods<\/strong><\/td>All data is collected via a form for deep reflection after completed action<\/td>Great time saving but still improved analytical capacity through mixed structured data<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Read more:<\/strong><\/p>\n\n\n\n

Schein, E. H. (1993). Legitimating clinical research in the study of organizational culture. Journal of counseling & development, 71(6), 703-708.<\/p>\n\n\n\n

Lack\u00e9us, M. (2021). Den vetenskapande l\u00e4raren. [The Inquiring Teacher]. Chapter 6.<\/p>\n\n\n\n

2.6 Designing Actions That Can Work\u2014Roots in Pragmatism and Design<\/h2>\n\n\n\n

We humans like to find universal truths, facts and principles that work everywhere. However, there is a shortage of such truths in complex everyday working life. A more useful perspective is pragmatism\u2014to practically test different ideas’ value in practice, to see knowledge and action as necessarily united. DAS is about precisely this. We design actions that might work in a complex practice. Instead of asking ourselves “What works?” for everyone everywhere, we ask ourselves “What works, for whom, when, how and why?”.<\/p>\n\n\n\n

An action task in DAS is thus a kind of hypothesis about what can help people, a social experiment. It must then be tested practically by each individual person in their unique situation. When we formulate such action tasks, we engage in a kind of design work. We design principles that can be more or less useful in different situations, for different people. How well an action task works in practice, each participant then judges after the attempt.<\/p>\n\n\n\n

Pragmatism may sound self-evident, but the fact is that we humans constantly fall into the trap of reducing complex situations to universal truths and mathematical relationships. As soon as easily measurable key figures and numbers are demanded, perhaps in the form of KPIs, we should be on our guard. Philosophy of science scholars call this misstep positivism<\/em>. It’s not about being overly positive, but rather about only dealing with established facts. Since there is a shortage of such facts in a complex reality, one is easily fooled. Design science research is here an alternative scientific approach to traditional research that focuses on law-bound observable facts, see Figure 2.6 below.<\/p>\n\n\n\n

Read more:<\/strong><\/p>\n\n\n\n

Romme, A. G. L. (2003). Making a difference: Organization as design. Organization Science, 14(5), 558-573.<\/p>\n\n\n\n

Table 2.6.<\/em><\/strong> Differences between traditional research and design science research (the table is based on an article by Romme, 2003).<\/em><\/p>\n\n\n\n

 <\/strong><\/td>Traditional research<\/td>Design science research<\/td><\/tr>
Study object<\/td>Naturally occurring phenomena<\/td>Artificial phenomena created by humans<\/td><\/tr>
Goal<\/td>Analyse, describe and explain what exists today<\/td>Creatively change, design and create what does not yet exist but should exist<\/td><\/tr>
Result<\/td>Patterns, laws, relationships between different forces and variables<\/td>Recommendations, design principles, solutions, useful actionable knowledge<\/td><\/tr>
Form<\/td>“In a situation A, if B happens, then C often follows”<\/td>“In a situation A, if you want to achieve B, do C”<\/td><\/tr>
Research ideal<\/td>Objective, observing, analytical, emotionally detached<\/td>Pragmatic, action-based, situation-adapted, engaged<\/td><\/tr>
Challenges<\/td>How to be practically relevant?<\/td>How to conduct rigorous research?<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

2.7 Collecting People’s Thoughts in Writing\u2014Roots in Experience Sampling<\/h2>\n\n\n\n

The core of DAS data collection is simple but effective: let people write when something has just happened. A 50-year-old research tradition called experience sampling<\/em> gave us the logic and discipline. Experience sampling is a classic data collection method in psychological research where participants at random or predetermined times in everyday life briefly report what they are doing, how they feel and in what context, so that experiences are captured in real time. The written format has several advantages. It makes thinking visible, it scales without losing nuance, and it can be read again, alone and together. When the reflection also contains feelings, it becomes not just a report, but also a temperature gauge of energy and friction.<\/p>\n\n\n\n

We therefore ask not only for participants’ reflection on what happened, but also on how it felt and why they thought it turned out the way it did. Over time, this becomes a form of written collegial learning, where participants’ texts become shared knowledge that can be sorted, quoted and recirculated.<\/p>\n\n\n\n

When the same people write many times over time, the value becomes even greater. This is called working longitudinally<\/em> and means we see shifts in behaviours, language, motives and soft factors. Then one can follow both personal learning curves and organisational shifts. It’s not about replacing conversation or numbers, but about giving them a stable backbone. Figure 2.7 compares writing, speech and numbers and shows why text in the moment gives a particular kind of evidence.<\/p>\n\n\n\n

Read more:<\/strong><\/p>\n\n\n\n

Lack\u00e9us, M. (2021). Den vetenskapande l\u00e4raren. [The Inquiring Teacher].  Chapter 7.<\/p>\n\n\n\n

Larson, R., & Csikszentmihalyi, M. (1983). The experience sampling method. In M. Csikszentmihalyi (Ed.), Flow and the Foundations of Positive Psychology: The Collected Works of Mihaly Csikszentmihalyi (pp. 21-34). Springer Nature.<\/p>\n\n\n\n

Stone, A. A., Shiffman, S. S., & DeVries, M. W. (2003). 2 – Ecological momentary assessment. In D. Kahneman, E. Diener, & N. Schwarz (Eds.), Well-being: The foundations of hedonic psychology. Russell Sage Foundation.<\/p>\n\n\n\n

Table 2.7.<\/em><\/strong> Comparison between oral, written and number-based communication (table from Lack\u00e9us, 2021, p.130).<\/em><\/p>\n\n\n\n

 <\/em><\/td>Oral communication<\/strong><\/td>Written communication<\/strong><\/td>Communication through numbers<\/strong><\/td><\/tr>
Depth of understanding<\/strong><\/td>Very large<\/em><\/td>Large<\/em><\/td>Small<\/em><\/td><\/tr>
Time spent in production<\/strong><\/td>Small<\/em><\/td>Small<\/em><\/td>Small<\/em><\/td><\/tr>
Time spent in analysis<\/strong><\/td>Very large<\/em><\/td>Medium<\/em><\/td>Medium to small<\/em><\/td><\/tr>
Spreadability<\/strong><\/td>Small<\/em><\/td>Medium to large<\/em><\/td>Large<\/em><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

2.8 Analysing Cause-Effect Relationships\u2014Roots in Critical Realism<\/h2>\n\n\n\n

To understand a phenomenon in depth requires more than measurement\u2014it requires a language for cause-effect relationships. The philosophy of science tradition of critical realism<\/em> gave us that language. We connect actions to subsequent reflection at the micro level and then look for recurring patterns that can be explained by underlying forces\u2014expectations that change behaviours, visibility that creates responsibility, small risks that tempt initiative.<\/p>\n\n\n\n

Let’s take an example of an action task: “End the meeting with a 60-second round about what became clear”. In team A, the tag “clarity” increases and the feeling moves towards positive. The effect may be that the turn-taking makes it easier to speak. In team B, the effect is absent. The effect is perhaps blocked by low psychological safety. When we then read quotes in clusters and place them alongside tags and feelings, such differences become visible: same action task, different outcomes, different active forces.<\/p>\n\n\n\n

This illustrates something that in critical realism is called mechanisms<\/em>, not just correlations<\/em> as it’s called in statistics. Visualisations help us see these mechanisms without simplifying away the human aspects. The heat map over action tasks and tags shows where effects gather, while the quotes give the underlying mechanisms voice and contour. We interpret cautiously and formulate a testable design principle: “In context C, do intervention I to achieve outcome O, because mechanism M works there.” (cf. CIMO as described in section 1.5). Then we test whether the principle holds in the next cycle. That’s how mechanisms for cause and effect become more than words: they become decisions and changes that make a difference in the real world. Figure 2.8 is called Coleman’s boat, a classic figure in critical realism that shows how we move from structure to individual and back again in our interpretation of what we study.<\/p>\n\n\n\n

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Figur 2.8.<\/em><\/strong> DAS is about trying to explore cause-effect patterns at the micro level (figure revised from Lack\u00e9us, 2021, p.90)<\/em><\/p>\n\n\n\n

Read more:<\/strong><\/p>\n\n\n\n

Elster, J. (1989). Nuts and bolts for the social sciences. Cambridge Univ Press.<\/p>\n\n\n\n

Lack\u00e9us, M. (2021). Den vetenskapande l\u00e4raren. [The Inquiring Teacher]. Chapter 5.<\/p>\n\n\n\n

Ylikoski, P. (2019). Mechanism-based theorizing and generalization from case studies. Studies in History and Philosophy of Science, 78, 14-22.<\/p>\n\n\n\n

2.9 We Build a Research-Informed Learning Organisation<\/h2>\n\n\n\n

The dream of a learning organisation has existed for a long time, but often it has remained value-based words. With DAS, the dream becomes more possible to achieve. When people get to reflect confidentially about sensitive questions in their everyday work, when leaders mirror with respect and when patterns are read together, then the tone of conversation changes. We move from defence to exploration, from what the researcher Donald Sch\u00f6n calls a Model 1 organisation towards a Model 2 organisation, see Figure 2.9 below. Small decisions are made more often and closer to the floor, and knowledge circulates through so-called communities of practice<\/em> that share action tasks and design principles across boundaries.<\/p>\n\n\n\n

In the long term, what we call a \u201clagom\u201d-scientific<\/em> research-informed<\/em> culture<\/em> emerges where evidence doesn’t mean heavy reports, but visible patterns that help us do the next thing better. We get an organisation that both produces value for its customers or users, and simultaneously learns deeply about how value comes into being, in the midst of the flow. However, it requires courage to dare to write honestly, patience to read and discipline to persist, but the reward is a way of working that lasts. The three steps in DAS are then layered on each other into a structure that carries\u2014not as a template from above, but as a shared craft for learning-oriented value creation.<\/p>\n\n\n\n

Read more:<\/strong><\/p>\n\n\n\n

Argyris, C., & Sch\u00f6n, D. A. (1978). Organizational Learning: A theory of Action perspective. Addison-Wesley Publishing Company, Inc.<\/p>\n\n\n\n

Lack\u00e9us, M. (2021). Den vetenskapande l\u00e4raren. [The inquiring teacher] Chapter 6.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Figure 2.9.<\/em><\/strong> A vision for a learning organisation proposed by the researchers Argyris and Sch\u00f6n in the 1970s (Argyris & Sch\u00f6n, 1978).<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

The methodological journey behind DAS began with equal parts frustration and curiosity. My doctoral studies at Chalmers started in 2009 with a deeply personal question: What had my teachers actually done to me as a student ten years earlier? 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