In this example, assume that we have a training program that was developed using Concept Mapping.

Each statement on the map represents a specific topic that should be covered in the training. For quality control purposes, we monitor the training program each time it is given, rating how much each topic was emphasized. We wouldn’t expect that every topic could or should receive equal emphasis--more important topics should be emphasized more. For our initial pattern match, we might use our implementation measure for the first two times the training was carried out. The left side of the ladder graph would show the relative emphases for Time 1, while the right side would show it for Time 2. The ladder graph would show at a glance how consistent the implementation was across the two trainings. We would immediately be able to see in which areas (i.e., clusters) there might have been an inconsistency. This information would be useful for the instructional designers or the instructors as they try to develop a consistent, high-quality training program. The pattern matching correlation provides a metric that describes the consistency level. Over successive implementations of the program, we might continue to examine the consistency pattern match. If the correlation suddenly falls below an agreed-upon level (e.g., .7), the training can be temporarily stopped so that we might look at where (i.e., what clusters) there is a disconnect and explore what might have caused it (e.g., change in instructor, setting, or participant population).