The Theory Of Meaningful Learning By David Ausubel

This psychologist and pedagogue developed an interesting theory about the assimilation of knowledge.

The education system is often criticized for placing too much emphasis on subjects that are considered irrelevant while omitting essential content. For example, it may be thought that the novels that are required reading in high schools fail to connect well with young students, being old and not set in the present.

This type of criticism connects with one of the most important theories of constructivist psychology: the Theory of Meaningful Learning of David Ausubel.

Who was David Ausubel?

David Paul Ausubel was a psychologist and pedagogue born in 1918 who became one of the great referents of constructivist psychology. As such, he placed great emphasis on developing teaching based on the student’s knowledge.

That is, the first step in the task of teaching should be to find out what the student knows in order to know the logic behind their way of thinking and act accordingly.

In this way, for Ausuel teaching was a process by which the student is helped to continue increasing and perfecting the knowledge he already has, instead of imposing on him a syllabus that must be memorized. Education could not be a one-way data transmission.

Meaningful learning

The idea of ​​meaningful learning that Ausubel worked with is the following: true knowledge can only be born when the new content has a meaning in light of the knowledge you already have.

In other words, learning means that new learning connects with previous ones; not because they are the same, but because they have to do with them in a way that creates a new meaning.

That is why new knowledge fits into old knowledge, but the latter, at the same time, is reconfigured by the former. In other words, neither the new learning is assimilated in the literal way in which it appears in the study plans, nor is the old knowledge unchanged. In turn, the new information assimilated makes the previous knowledge more stable and complete.

The Assimilation Theory

Assimilation Theory allows us to understand the fundamental pillar of meaningful learning: how new knowledge is integrated into old ones.

Assimilation occurs when new information is integrated into a more general cognitive structure, so that there is continuity between them and one serves as an expansion of the other.

For example, if Lamarck’s Theory is known, so that a model of evolution is already understood, then it is easier to understand the Theory of Biological Evolution inherited from Darwinism.

Obliterative assimilation

But the meaningful learning process doesn’t end there. At first, each time you want to remember new information, you can act as if it were a separate entity from the more general cognitive framework in which it is embedded. However, with the passage of time both contents merge into one, so that only one can no longer be evoked, understanding it as an entity separate from the other.

In a way, the new knowledge that was learned at the beginning is forgotten as such, and in its place appears a set of information that is qualitatively different. This process of forgetting is called by Ausubel “obliterating assimilation”.

What is not meaningful learning?

To better understand David Ausubel’s concept of meaningful learning, it can help to know what the opposite version consists of: machine learning, also called rote learning by this same researcher.

It is a concept closely linked to passive learning, which many times occurs even unintentionally due to simple exposure to repeated concepts that leave their mark on our brain.

Rote learning

In rote learning, new content is accumulated in memory without being linked to old knowledge through meaning.

This kind of learning differs from meaningful learning not only because it does not help expand real knowledge, but also because new information is more volatile and easy to forget.

For example, learning the names of the Autonomous Communities of Spain by memorizing the words in a list is an example of rote learning.

However, machine learning is not useless at all, but it makes some sense at certain stages of development to learn certain data. However, it is insufficient to generate complex and elaborate knowledge.

The types of meaningful learning

Meaningful learning is opposed to the previous type, fundamentally, because for it to occur it is necessary to actively seek a personal link between the content that we learn and those that we have already learned. Now, in this process there is room to find different nuances. David Ausubel distinguishes between three kinds of meaningful learning:

Learning representations

It is the most basic form of learning. In it, the person gives meaning to symbols by associating them with that specific and objective part of reality to which they refer, resorting to easily available concepts.

Learning concepts

This type of meaningful learning is similar to the previous one and relies on it to exist, so that both complement and “fit” with each other. However, there is a difference between the two.

In concept learning, instead of associating a symbol with a concrete and objective object, it is related to an abstract idea, something that in most cases has a very personal meaning, accessible only from our own personal experiences. something that we and no one else have experienced.

For example, to get to internalize the idea of ​​what a hyena is, it is necessary to develop an idea of ​​”hyena” that allows these animals to be differentiated from dogs, lions, etc. If we have previously seen a hyena in a documentary but could not differentiate it from a large dog, that concept will not exist, while a person familiar with dogs will probably notice those significant anatomical and behavioral differences and be able to create that concept as a category apart from that of dogs.

Learning propositions

In this learning, knowledge arises from the logical combination of concepts. For this reason, it constitutes the most elaborate form of meaningful learning, and from it it is capable of making very complex scientific, mathematical and philosophical appraisals. As it is a type of learning that demands more efforts, it is done in a voluntary and conscious way. Of course, it uses the two previous types of meaningful learning.

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