Insight Into: Education & Conceptualization Part 3

In the last article, I provided a brief discussion of why simply acquiring data is insufficient for education. A student must be able to understand the data you are communicating. I noted that this requires a style of thinking that focuses on concepts and ideas instead of rote memorization. This type of thinking, however, is a learned skill, not a natural talent.

In IRI's work with developing communities, we have determined that teaching someone how to think conceptually requires at least the following learning cycle:

1. Introduce ideas
2. Prompt the learner to think about (analyze) the data provided in 1
3. Encourage the learner to synthesize concepts (their own take on the data) based on their understanding and perception
4. Prompt the learner to analyze the new concepts
1. Prompt the learner to compare the concepts to the other ideas they have
2. Promote learner-driven identification of inconsistencies and errors in the ideas
3. Do not correct the learner - the self-identification of errors is critical
5. Encourage the learner to synthesize concepts based on their analysis
6. Repeat as necessary (many, many, many times) to develop the habit of reflection, analysis, synthesis, and self-correction

This is a gross oversimplification of the system, but it is sufficient to point out one of the key points of conflict between teaching people how to think (promoting analysis and understanding), and simply teaching them what to think (providing data). The crux of the difficulty lies in point 4.3 - emphasizing self-correction over instructional correction.

As I mentioned in the first article of this series, the goal of education is, in part, to make sure the learner has correct information. To that end, error is the enemy, and must be corrected so that the student doesn't learn bad information. Yet in order to think in a way that promotes understanding, students must be able to think through issues without correction, and, from a traditional educational perspective, this is unnerving. The tendency of a teacher to correct error is, in many cases, nearly automatic. Thus, a tension arises between the need to impart correct data, and the need to train students in ways of processing that data. It can be extremely hard, in a classroom context, to find a way to balance the two. In some disciplines (often literature or philosophy), the emphasis gets placed on developing understanding, but many times lacks a sense that some things may be correct or incorrect. Other disciplines (medicine, the previously mentioned nuclear power plant management) take a very dim view of errors, as these can cost lives. Yet all disciplines need both elements of education to flourish, because without both, you can't have students who understand new information. Without that balance, you either get students who can play with ideas, yet divorce them from operations in reality (pure analysis), or you get students who are locked into calcified systems of understanding that they can't innovate on (pure data).* To truly be effective, education must include both of these elements, yet they seem mutually exclusive (good thinking = tolerating error, good data = eliminating error).

Next article, I will look into some ways to, perhaps, reconcile these two systems so that students can both be good thinkers, and learn good information.

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*I am comparing extremes here for emphasis. Most people have some degree of both elements in their thinking, though these elements may still be imbalanced. That said, I have personally met examples of both extremes, so I can say with confidence that they really do exist. This is a real thing.