This is insightful. I have indeed left huge chunks out.
But, let’s review some of the underlying reasons for all of this …
(1) One of the things happening in science education right now is a gradual epistemological transition which the inventor of concept maps, Joseph Novak, prefers to contrast with positivism and constructivism. Positivism, in his view, is the one-way discourse we see with the lecture format. It positions knowledge as purely objective, and the process of learning, in this view, is to get that objective knowledge into the minds of students.
Constructivism is the alternative view that for particularly complex topics with no obvious resolution, we should focus upon the quality of discourse rather than the conclusions of scientists. It positions learning at all stages as heavily dependent upon discourse; it strives to spread assessments out, even within the lectures themselves (like Eric Mazur’s “peer instruction”); and it emphasizes the role of concepts to the process of assimilation. In this view, a distinction is made between assimilation of new information and rote memorization. Concept maps are a necessary and proven tool for updating and modifying concepts in the brain.
(2) Physics education researchers (PER) like Eric Mazur and David Hestenes have observed very serious problems with peoples’ ability to learn basic mechanics physics principles, based upon the force concept inventory (FCI) test. The problem is the “intuitive notions” which students bring to the classes, which keep them from hurting themselves. We all develop intuitive notions in physics as a natural reaction to our observed environments. It turns out that instruction which does not address these intuitions is ineffective for about 90% of the people. What I’ve personally observed is that this is largely what distinguishes people who are able to question scientific theories from those who are not. The ones who cannot question theory failed to assimilate the knowledge into their long-term knowledge structures. Instead, what they did was create separate knowledge structures which lack interconnections with the knowledge structure they use to problem-solve in everyday life. Concept maps are perfect for addressing this problem.
(3) One of my own observations is that people do not understand what a worldview in science is. And this strongly suggests that people do not understand the structure of scientific theory itself. There are properties; concepts which contain them; propositions which relate multiple concepts; models (aka theories) which contain sets of propositions; and at the very top of all of this are worldviews – which is basically anything that is happening within the mind of a thinker.
Now, something very important can be observed online with regards to worldviews and models: People who are trying to talk about models do not like to be in the same room with people who are talking about worldviews, and vice-versa. There is a very important reason for this that doesn’t become apparent until a person studies how innovation is done in the business world: The point of building models is to converge, whereas with worldview clashes, divergence is just as valued. What this suggests is that scientific discourse is not just one process. It’s a system of systems. If our discourse system is to support the repeating innovation cycle of divergence & convergence, we cannot let one of these two processes dominate the other. In other words, they should happen in two separate places.
(4) One of the biggest problems with emergence in scientific discourse is the fact that people trying to make a case against conventional theory are given a blank text box to make their case. This basically favors conventional wisdom & the status quo, as it’s nearly impossible to undermine conventional theory from scratch with only text. It really doesn’t matter what arguments are put forward: Making a strong case requires huge amounts of text, but huge amounts of text will not be read. We have to start viewing text as having an inherent cost associated with it. Think about it this way: Text is like lots of little graphics. The mind has to interpret each of these lines and curves, and not only assemble them into characters, then words, then sentences and paragraphs, but it also has to process the meaning of all of that. When possible, we need to be using graphics to make our case.
And on top of that, there is absolutely no reason that we should be starting from scratch every time. The arguments are all out there on the web, in books, videos and scientific papers (etc). It makes no sense to repeat the same laborious process of fetching them each time. We need to build a knowledge graph, and this knowledge graph should be very carefully designed to support emergence in scientific discourse.
(5) What I would suggest is that the mathematics should be layered on top of this conceptual substructure. That’s because the large majority of people – if not everybody – organize their knowledge on the basis of the concepts, not the mathematics. The concepts are fundamental. And in fact, when paradigm changes do actually occur, they tend to involve changes to the concepts. So, until we build systems which support our own ability thoroughly reflect upon this epistemological structure to science, paradigm changes will remain unsupported by our communication technologies.
