Our DBR process

Our research method follows the development and design of a learning game called All Can Code. It’s a game which has not been implemented at the Danish market at this point in time. We as the designers of our design process are curios about how this game can enter the Danish market. It’s our main goal to analyze and dig deeper into which factors works and do not work regarding computer games. To get a better understanding about this we look at what we know works in Denmark. As mentioned in our blogpost 1 and 2 (https://pages-tdm.au.dk/didaktiskdesign/faelles-om-computerspil/ & https://pages-tdm.au.dk/didaktiskdesign/from-bird-to-frog/ ) we have moved around the big phenomenon which is gaining momentum in Denmark right now, eSport. We don’t see the game All Can Code as an eSport game or do we want it to be that because it already has its own structure and features which makes it a learning game for students and teachers. However, we are very interested about what works in Denmark and we know that eSport does and we want to find out why teachers and children are so into eSport and in general why people do play games.

To shed light to our case we are using the research method Design Based Research (DBR). It is a broad research approach initiated by, among others, Ann Brown (1992), and Allan Collings (1992). DBR is research design based, which means within the DBR that new knowledge is generated through processes that simultaneously develop, test and then improve a design. The research can therefore focus on the development of new artifacts and new uses for existing artifacts.

Our goal of using DBR is to build stronger links between education science and actual problems in the real world. The emphasis is placed on the iterative process that not only evaluate and innovate products and inventions, but at the same time systematically tries to refine innovation and produce design principles that can guide future research and development (Reeves 2006).

In our research process DBR occurs as a collaboration between practitioners and us the researchers. We do that, so we better can propose a solution method to meet the stated issues in the end of our process.

As mentioned in blog 2 (https://pages-tdm.au.dk/didaktiskdesign/from-bird-to-frog/), we have chosen a design principle called Human Centered Design. It is important in our DBR to includes design principles in order to test and make refining cycles. Data will be collected systematically in order to refine and redefine the problem, to find possible solutions and principles that best can deal with them. To end with a formed new designs and solutions which produce a continuous cycle of design-reflection-design. The result a DBR process is a set of design principles or guidelines that can be used by others who are interested in studying similar circumstances and considerations (Reeves, 2006).

Figure 1 below is our self-made DBR model also inspired by Reeves’ point of view according to a Design Based Research process.

Figure 1: Our DBR model. For bigger image follow this link: 


DBR run-through
Our understanding of DBR builds, as earlier mentioned, on Reeves theory. With this approach, we wish to create a prototype that is created on empathy and understanding from the practice of schooling using computer games. Our goal is, as stated in blog 1 and 2 to isolate and transfer certain elements of eSports used in education to the edutainment game called All Can Code.

What we have found during our interviews and observations of eSports is that the students are motivated and they use each other in different communities of practice (Wenger 2004). These communities are in part created by the way eSports is build up. Playing an eSports-title demands that you function in different roles, with a knowledge of how each role sums up a team. In this manner the individual player has an understanding of each other team members exact role and how that affects each person on the team. This, as we explained in our second blog, also coincides with Dewey’s notion of understanding and respect created by an empathic understanding of your fellow community-members (Reay:2011).

But how have we come to this understanding and how will that help us in isolating the different elements that might help other games in an educational setting?

This is where DBR comes into the picture. We have created a phased timeline, that shows how we have moved from one understanding of eSports in schools to the one we have today. This process has become a model that looks like this:

As we see in this model we have different phases that builds on one another. Knowledge created in phase one, discovery, creates the foundation for phase two and so forth. This way we ensure that the field/practice is the focalizing point of our design and it is the knowledge, feelings and point of view from them, and not ours that increases the chances of our research actually producing a prototype that betters their practice and field.

But to get a better understanding of these phases and functions the following part of this blog will explain how each phase is carried out and thought.


The phases – discovery, define, ideation, experimentation and evolution
When it comes to discovery this pretty much says what it does. We have tried to understand the practice. This has been done by prior knowledge of the field, but also reading prior texts about it. For instance, T.L. Taylors “Raising the stakes” about eSports. But to really know the feel and account for the idiographic differences between her world view and how the Danish schooling system uses computer games, we chose to do a survey, run an individual interview, conduct a focus group interview and observe a class of eSports.

With this new knowledge and map of the field we were able to find a way we might help All Can Code. As mentioned with Taylor and her nomothetic approach to eSports, we chose a point of view in which we say: How can the Danish way of using eSports in schooling help All Can Code with inspiration to better achieve success when entering the market?

The ideation phase is where we currently lie. With which methods might we isolate these elements from eSports that a learning game might achieve a higher probability of success? Building on our HCD perspective we have chosen a method called card sorting to open up the field by letting the users in the practice direct which elements have the greatest value for them. This method will be summed up in another paragraph in this blog. After doing this we wish to conduct a dot valuation in which different points are given to each element, which gives us a weighed group of elements from which we can try and create different scenarios for users to try at our final workshop at DOKK1 in May.

Next step is to locate where we might best use our methods? In classes of eSports, in classes not using computers? In both and then do a comparison between to the two and thus perhaps see where values overlap and thereby better be able to build our final prototype? Only the realm of what is possible seems limiting, so what will be wisest will be our job to find out.

This will be left blank for now. This is our actual prototype. This is how our knowledge has evolved and what we have ended up with. And that is still up for debate and change, living up to the phase-name. As knowledge is carried over from one phase to another this will be shaped as our empathy and understanding of the practice is strengthened.

Card sorting and user involvement in HCD
In HCD gaining understanding and empathy for the people we are designing for is central (Giacomin 2014). In the inspirational phase we observed a lesson in eSports (Portfolio 3

Research methods: Participant observation and action research). We are now in the process of moving from the first to the second phase in HCD, or from the second phase to the third phase in our own DBR model (figure 1). At this point we still aim to keep the people we are designing for at the center of the process. Based on our focus group interview and observations in the Discovery phase we continue to look for opportunities for design, and work to frame our insights. To do this the card sorting method (figure 2) will be used.

Figure 2: Card Sorting design method card. http://medialabamsterdam.com/toolkit/files/2015/01/MediaLAB_design_methods_toolkit.pdf

Figure 3: Copenhagen Games

The first round of card sorting will take place at the eSports event Copenhagen Games (Figure 3). Behind the title of card sorting lies several methods that can have many varied forms, purposes and have roots in different design perspectives. Wölfel & Merritt (2013) give an overview of 18 card sorting methods in Method Card Design Dimensions: A Survey of Card-Based Design Tool. Given our HCD perspective we have chosen card sorting as a way to keep the people we are designing for at the center of the process. As a method in this perspective card sorting “will help you identify what’s most important to the people you’re designing for” (IDEO.org). We will make our own cards, this from theory of learning and motivation as well as insights about eSports from our discovery phase. Each theory or empathy will have its own domain cards. In the card sorting workshop we will ask eSports practitioners to select what is most important to them within the different domains. After Copenhagen Games our plan is to go back to an eSport lesson and give the students the same cards to sort, the reason for this is to see if there is similarity between the cards that are most important when they are taught eSport and when they practise eSport. Why this focus on eSports you might ask. The answer to this is: When we start our card sorting in the eSports domain it is to locate and define aspects that make it successful, and something more and more schools in Denmark chose to have as part of the curriculum. But we don’t want it to be all about eSports therefore the cards will also be given to a standard danish school. We will have them sort the cards after what is most important to them. The plan for this is to compare what is important to eSport students, practitioners and teachers with what is important to pupils and teachers at a danish school with no eSport. If some of the cards have been deemed important by several groups we might chose to focus our future work on these insights. Factors that have been deemed important by only one or two groups can still be useful and we might continue to work with these as well. After the card sorting workshops we expect to have several ideas on the table, maybe more than are possible to take with us to the next phase, therefore we plan to take the insights from the card sorting and structure them in a dot voting system by having non-eSport teachers and pupils rank them, this “Allows for a consensus on which ideas need to be developed further and the reasons behind that.” (MediaLAB amsterdam figure 4) The dot voting method is often used as a way to decide within the design team (Tabaka 2006). Given our HCD perspective we choose to bring in the people we are designing for here as well.

Figure 4: Dot voting design method card http://medialabamsterdam.com/toolkit/method-card/dot-voting/


So now we will travel to Copenhagen to see and talk to some eSports people. Let the nerd fest begin – Happy Easter.



  • IDEO.org. Card Sorting
    http://www.designkit.org/methods/24 used 10-04-2017
  • Brown, A. L. (1992). Design experiments: Theoretical and methodological challenges in creating complex interventions in classroom settings. Journal of the Learning Sciences, 2(22), 141-178.
  • Reeves, T. (2006). Design Research from a Technology perspective. In J. V. D. Akker, K. Gravemeijer, S. McKenney & N. Nieveen (Eds.), Educational Design Research. London & New York: Routledge.
  • Portfolio 3 Research methods: Participant observation and action research 2017 not published.
  • Taylor, T. L.  (2012). Raising the Stakes: E-Sports and the Professionalization of Computer Gaming. MIT Press.
  • Tabaka, J. (2006). Collaboration explained: facilitation skills for software project leaders. Pearson Education.
  • Wenger, E. (2004) Communities of practices. Hans Reitzels.
  • Wölfel C., Merritt T. (2013) Method Card Design Dimensions: A Survey of Card-Based Design Tools. In: Kotzé P., Marsden G., Lindgaard G., Wesson J., Winckler M. (eds) Human-Computer Interaction – INTERACT 2013. INTERACT 2013. Lecture Notes in Computer Science, vol 8117. Springer, Berlin, Heidelberg

This blogpost is written by: παιχνίδι υπολογιστή

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