Breaking through the disciplinary barrier with practical mapping

by Steven E. Wallis. PhD and Bernadette Wright, PhD

Evaluations are often guided by some kind of diagram—such as a logic model, theory of change, or “practical map” —that shows the goals we want to achieve and what it takes to get there. Here, we’ll use these terms interchangeably but mostly call them “maps.” Maps are useful because they show your surroundings– where things are in relation to each other (and to you).

Real-world problems—such as poverty, justice, and health—have many causes. Issues are worsened or improved by political, economic, and technological factors, to name a few. So, to solve these issues, we need knowledge from many disciplines.

Many factors across disciplines contribute to real-world problems and solutions

However, many programs (and so their evaluations) lack the range of interdisciplinary knowledge needed to solve big problems. We’ve found that mapping is useful for incorporating interdisciplinary knowledge into our evaluations.

“Practical mapping” is a straight-forward approach for using concepts and connections to integrate knowledge across and between disciplines, to support effective action.

Practical mapping is based on research showing that we are better at understanding situations and reaching desired goals when our knowledge is more “structured.” We can see the structure of our knowledge by diagramming it to create a map. Here is a simple hypothetical example of a map showing concepts (in boxes) connected by causal arrows. (This simple example is not intended to be a complete or accurate map.)

Each box represents something that can be described and measured in the real world (a variable). Each arrow represents the cause-and-effect relationship between the boxes (to the best of our collective understanding).

Simple example of a practical map

(From: Practical Mapping for Applied Research and program Evaluation, p. 182)

We can “read” each arrow on the map as “more of this causes more of that.” Starting at the bottom and moving up to the right, you can see that, according to this map, the more taxes that are paid to the state, the more funds there will be for educational programs – and so on.

We’ve often seen researchers look for information on their narrow topic and miss many valuable studies from other fields because different studies use different terms to describe the same thing. Instead, in our research and practice, we find we can be more effective by looking at how the concept in each box is measured, and if research has inferred any causal relationships between the concepts. That “common language” of measurement and causality for practical mapping is key to supporting interdisciplinary collaboration.

The information you’ll use to make your map can come from a variety of sources, such as academic research, trade publications, interviews with experts, and stakeholders. Maps can show knowledge from qualitative, quantitative, or mixed methods. As in any knowledge pursuit, more data sources are better.

In the above (hypothetical) example, the light-shaded boxes come from research related to the business community while the darker-shaded boxes are from researchers in education. The darkest boxes are where their research overlaps – the concepts are of direct relevance to researchers from both fields – where their research results overlap and so where their perspective maps may be synthesized.

To create a map for your research topic, start by reading the text found in the research results from your sources. Find the concepts (whatever was measured); then identify the causal relationships. For example, a report from the business side might say something like, “When our businesses grow from collaborative marketing, we will need to hire more workers.” That might “translate” into our language of boxes and arrows as you see in the above figure’s upper-right hand corner.

Once you get used to the mapping process, you can more easily create maps incorporating research results from other disciplines. And, you can more easily collaborate with scholars and practitioners from other disciplines to help them create maps and merge them with yours to create a more complete picture.

Also, you can use these kinds of maps to conduct more effective evaluations—and more effective action—in a few ways.

• First, incorporating your interdisciplinary map into your “logic model” (“map”) to better understand the organization and context under evaluation.

• Second, in conducting the evaluation, your map may be used to show what parts of the process are more closely related to each discipline. So, you can easily identify which experts to contact for advice in collecting data (business or education, in the above simple example).

• Third, by understanding the overlaps, you can more easily show the client where they can focus their collaborative efforts to improve program results.

For more information, and step-by-step instructions, see our book, Practical Mapping for Applied Research and Program Evaluation.