Meaningful Learning
Week 5 Meaningful Learning
What is learning Sept. 21
What is learning? Learning is acquiring a new skill, knowledge, or information. We read about meaningful learning which essentially means activating prior knowledge, although it encompasses more. A learner who can apply prior knowledge or skill to a new concept or task is able to learn the new more quickly, and with stronger attachment, or interest. For example, one of the major reading strategies is to compare text to self (the learner): one of my favorites. This strategy requires the learner to compare his or her personal experiences or knowledge to whatever he/she is reading. This creates a personal connection to the text helping the learner first, know what the text is about, and second, have an emotional connection to it. Even if the connection is negative, the learner will remember the text. Which leads me to say: is learning simply connecting to and remembering information? Could be.
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When I defined learning a few weeks ago I described it as growing, improving, expanding and refining. In order for learning to be these things it must be more than rote. For this reason I am a big believer in the Meaningful Learning Model. It’s helpful to link new concepts and information to things one already knows and understands. There are lots of examples and many applications of ML, but here is one simple example of this model where, at the beginning of the school year, a teacher drew on a student’s experience with music to help her and her classmates understand their important role in the learning process.
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I'm not sure my view on learning has really changed that much. Meaningful learning seemed to me to be an extension of cognitive information processing (CIP). As CIP states, we learn by building on previous knowledge and constructing pychological "building blocks" of knowledge. However, some of our premises or previous knowledge can be flawed which leads to continued error. Some examples given in the Novak reading (Novak 2002) refer to studies done with MIT graduates in which very intelligent student expressed inaccurate views on subjects such as the origin of weather change, the explanation of the carbon in trees, and other concepts that should normally have been easy for them to understand.
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