Education design collaborations — the space in between
“Every problem-solving effort must begin with creating a representation for the problem — a problem space in which the search for the solution can take place” (Simon, 1969, p. 108).
When we design in complex systems such as higher education, we often need to create problem spaces for design of problems as well as ways of solving them — that is, we cannot assume that “we know the problem before we start investigating, and that it remains the same as it is investigated (Lury, 2020, p. 2).
These problem spaces act as boundaries and structures for what we are trying to achieve, but also the space itself and problem generation must remain fluid throughout the design process.
Problem spaces also support thinking in action — a lot of ideas surface through active joint exploration of problems and the problem space.
In education design, I utilise collaborative whiteboards such as Mural and Miro to frame the problem space and “constraints” (Cynefin.io, 2022) that guide the process of designing a wide range of learning experiences.
Constraints can enable and restrict the education design process. From one perspective, constraints can create the necessary boundaries around the problem space, and on the other hand they can act as drivers to propel the ideation.
For example, different learning experiences, such as courses or subjects in a degree, microcredentials, continuous professional development offerings (CPDs) and Massive Open Online Courses (MOOCs) have certain characteristics. These can include duration, audiences, volume of learning, assessment, requirements of the accreditation bodies and more. All of these characteristics need to be defined and thought through.
However, there is a lot of flexibility and context around how we approach each design process, how it progresses and what is generated in a way of outcomes. Problems and problem spaces always emerge, re-emerge and shift. Therefore, the design process needs to be adaptable, resilient and keep evolving with problem generation.
There are process-related constraints as well, such as project timelines, team structure and expertise, broader institutional requirements and so on. These need to be clearly identified at the start, and taken into account as teams progress through the design.
Documents such as storyboards and templates provide useful structure to the design process. However, the documentation, similar to collaborative white boards, needs to be adapted to each problem space and the problems we are trying to solve.
In terms of supporting the conditions for productive exploration of the problem and problem space, I find it is important to be very clear about which constraints are fixed (such as institutional rules on assessment), and which ones are adaptable (such as concepts covered in different parts of a course).
Overall, I find the process involves continuous zooming in and out of problems and problem spaces. Zooming in involves delving into specifics of what is being designed, and how joint work is approached and structured. Zooming out is about keeping the bigger picture in mind — what are the problems we are trying to solve, how do they fit into the broader context, and how do we problematise the space we are working in.
References
Cynefin.io (2022, March 17). Constraints. https://cynefin.io/wiki/Constraints
Lury, C. (2020). Problem spaces: How and why methodology matters. John Wiley & Sons.
Simon, H. A. (1996). The sciences of the artificial. 3-rd edition. Cambridge, MA.
