How does thinking complexity grow?

Theo Dawson
4 min readDec 3, 2017


Today, we face an unprecedented level of complexity and change. Our ability to succeed in a complex and rapidly changing environment increases along with growth in the complexity of our thinking.

The rate at which complex thinking grows is affected by a wide range of factors. Twin studies suggest that about 50% of this rate is likely to be predicted by genetic factors. The remaining variation is explained by environmental factors, including the environment in the womb, the home environment, parenting quality, educational quality & fit, economic status, diet, personal learning habits, and even aspects of personality.

My colleagues and I measure the growth of thinking complexity on a scale called the “Lectical Scale.” This scale represents something called hierarchical complexity. The following video provides a quick descriptions of its levels.

Each level on the Lectical Scale takes longer to traverse than the previous level. This is because development through each successive level involves constructing increasingly elaborated and abstract (complex) “knowledge networks.” Don’t be fooled by what looks like slow growth at the higher levels, though. A little growth can have an important impact. For example, small advances within level 11, can make a big difference in a leader’s capacity to work effectively with complexity.

The graphs on the left show possible learning trajectories— first, for the lifespan and second, for ages 10–60. Note that the highest age shown on these graphs is 60. (This does not mean that individuals cannot develop after the age of 60.)

The yellow circle in each graph represents the Lectical Score of an individual and the confidence interval around that score. That’s the range in which a person’s “true score” would most likely fall. When interpreting any test score, you should keep the confidence interval in mind.*

Test results are not tidy

When we measure development over short time spans, it does not look smooth. The kind of pattern shown in the graph below is more common. However, we have found that growth appears a bit smoother for adults than for children. We suspect this is because children are less likely to do their best work on every testing occasion. For example, relative to adults, children are more easily distracted, more likely to be taking an assessment against their will, and less likely to be able to compensate for the effects of stress, a bad day, or lack of sleep.

Factors that affect the rate of development

A number of factors affect the rate and quality of an individual’s development. These include:

  • The test-taker’s current developmental trajectory. (A person whose history places her on the green curve in the first two graphs is unlikely to jump to the blue curve.)
  • How well the individual’s current knowledge is networked—how deeply it is understood.
  • The amount of reflective activity (especially VCoLing) the individual typically engages in (no reflective activity, no growth).
  • Participation in deliberate learning activities that include lots of reflective activity (especially VCoLing).
  • Participating in supported learning (coaching, mentoring) after a long period of time away from formal education (can create a spurt).

You can learn more about how learning & development work on YouTube, at LecticaLive, and if you’d like to take a really deep dive, in a course called FOLA.

  • Test developers should report confidence intervals. If you cannot find any information about confidence intervals for a particular test or measurement system, look for information about statistical reliability (often referred to as Alpha). If you know Alpha, you can make your own estimate of confidence interval. To learn how, read the article, Test reliability: How high should it be?



Theo Dawson

Award-winning educator, scholar, & consultant, Dr. Theo Dawson, discusses a wide range of topics related to learning and development.