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Education is not Explaining…The Modeling Instruction Paradigm

February 13th, 2013 by

I own a t-shirt that reads, “I can explain it to you, but I can’t understand it for you.” I don’t normally wear t-shirts to class, so this seemingly cynical message is lost to my teacher colleagues. This is too bad because the message is far from cynical from an educator’s perspective. It really means that explaining a concept to someone does not mean they will understand it.

I can explain a concept in words by deconstructing it and providing numerous examples of how it applies to the real world. Can students do that after we explain it to them? Repeating back a list of facts or solving a narrowly focused group of problem sets does not mean students understand what they have done.

The t-shirt really means that to gain understanding, teachers need to go beyond explanations, and the onus is upon us to provide students with the opportunity to create their own explanations for what we teach. That means a higher level of processing that requires students to maintain interest, conduct investigations, relevant questioning, and modeling. Lessons and labs that do nothing more than verify what is already known and discovered by others does very little to stimulate a need to answer questions that lead to the creation of models.

Modeling Instruction for your STEM students is a gateway into generating activities that stimulate true engagement and require top-down thinking. Top-down thinking may be the opposite of what many teachers use as their teaching paradigm. It does not scaffold up knowledge in a linear fashion, where students are taught fundamentals one agonizing step at a time.

Modeling Instruction brings students from the textbook to the tarmac, where they observe phenomena and formulate questions that help them generate concrete data on what they have observed. This data is then analyzed and applied to other situations, relevant situations that relate to the students’ own experiences. In this way, Modeling Instruction allows students to generalize the data patterns, and they can predict future outcomes with similar variables. These predictions allow them to create models of their own to explain what they have observed, experimented on, and analyzed. Yes, this is both scientific and engineering practice. It requires numerous common core performance tasks to be mastered as participants use Mathematics to see measure outputs and correlate data and Language Arts to share what they have learned.

A video below from a TED talk explains what happens in teacher Frank Nochese’s ¬†classroom. He’s got some good suggestions for implementing Modeling Instruction in your STEM class. You can also visit the American Modeling Teacher’s Association¬†for an in-depth resource that will get your class going quickly. And at some point soon, maybe you can revisit the t-shirt rack and find one that reads, “I can explain it to you, because I can model it for you.”

 

 

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