Conceptual modelling – Integration and Implementation Insights

Collaboration: From groan zone to growth zone

July 13, 2022May 28, 2019

By Carrie Kappel

What is the groan zone in collaboration? What can you do when you reach that point?

As researchers and practitioners engaged in transdisciplinary problem-solving, we know the value of diverse perspectives. We also know how common it is for groups to run into challenges when trying to learn from diverse ideas and come to consensus on creative solutions.

This challenging, often uncomfortable space, is called the groan zone. The term comes from Sam Kaner’s diamond model of participation shown in the figure below.

Conceptual modelling of complex topics: ConML as an example / Modelado conceptual de temas complejos: ConML como ejemplo

August 11, 2021December 11, 2018

By Cesar Gonzalez-Perez

A Spanish version of this post is available

What are conceptual models? How can conceptual modelling effectively represent complex topics and assist communication among people from different backgrounds and disciplines?

This blog post describes ConML, which stands for “Conceptual Modelling Language”. ConML is a specific modelling language that was designed to allow researchers who are not expert in information technologies to create and develop their own conceptual models. It is useful for the humanities, social sciences and experimental sciences.

Problem framing and co-creation

August 24, 2022October 27, 2016

By Graeme Nicholas

How can people with quite different ways of ‘seeing’ and thinking about a problem discover and negotiate these differences?

A key element of co-creation is joint problem definition. However, problem definition is likely to be a matter of perspective, or a matter of how each person involved ‘frames’ the problem. Differing frames are inevitable when participants bring their differing expertise and experience to a problem. Methods and processes to support co-creation, then, need to manage the coming together of people with differing ways of framing the problem, so participants can contribute to joint problem definition.

ICTAM: Bringing mental models to numerical models

August 24, 2022September 22, 2016

By Sondoss Elsawah

How can we capture the highly qualitative, subjective and rich nature of people’s thinking – their mental models – and translate it into formal quantitative data to be used in numerical models?

This cannot be addressed by a single method or software tool. We need multi-method approaches that have the capacity to take us through the learning journey of eliciting and representing people’s mental models, analysing them, and generating algorithms that can be incorporated into numerical models.

More importantly, this methodology should allow us to see in a transparent way the progression on this learning journey.