How to Get Students to Buy-Into Your Content…

I’d like to introduce a critical topic: how to get students to care about the content you have to offer.

Why should YOU care about this? I think I can save you a TON of time this year.

Here’s how:

Research on Buy-in

I said I could save you a ton of time this school year, and there are many ways to make that happen. I am going to focus on just one area to save time: reduce re-teaching. If you find re-teaching is costing you more than 5 minutes a day, this article is for you.

I don’t think you can erase all re-teaching because the wide variety of student backgrounds makes that task overwhelming, even with solid differentiation in your teaching. But, today we’ll focus on four powerful ways to reduce re-teaching.

Here’s what the research says about our brain remembering what was just taught. As amazing as our brain is, it would make no sense for it to give equal weight to every single moment of our life, in terms of memory. When your brain is exposed to new input (sights, sounds, touch, smells, etc.), there’s a choice to make. “Do I (the brain) create new lasting representations of this new learning, or assume it was random and will not likely occur again?” How DOES the brain know whether something should be saved or not?

It doesn’t know.

If it did know, you’d always recall all the important things from life, and forget all the trivia. But your brain IS designed to make high-probability guesses based on many factors (there are 12 total that I know of).

I am going to list 25% of my memory-saving tools the brain uses to create and save new pathways in the brain. These each raise the probability of your brain identifying the learning as “worth saving.” Sorry, the other 75% are in the upcoming workshops this summer. And, by the way, if you implement just these 4 listed here, you’ll have the most awesome class on campus!

1) Behavioral relevance – Link the learning to the things that your students (developmentally) care about the most. Some links might be to affiliation among peers, strengthening student identity, relationships with teachers, autonomy, status among classroom peers, fun or food.

2) Spaced repetition – Tweak the learning four times to keep it fresh. After the initial learning, do retrieval learning a day later. Then add a retrieval practice halfway to the test and another last retrieval the day before the test. To do that, students use a blank sheet of paper and write everything that they think is important about a topic in 5 minutes or less. There is no looking at notes or reviewing. The hard work of the retrieval is what strengthens the memory.

3) Intensity or type of emotional valence (e.g. our mood) – When our state is in any one of the 12 “hungry states” I share in my summer events, receptivity to learning goes up. Here are a few of those hungry and amazing states for your class: puzzled, expectant, anticipation and confused. First, use demonstrations, powerful questions or cliff-hangers to get students to be “hungry” for the rest of the “story.”

4) Redundant sensory stimulation – Combinevisual (see the learning) and auditory (hear it), plus olfactory (unusual smell) and tactile (“being hands-on”). For example, doing a new relevant task that is hard work and requires repetition WILL get “saved” in our brain. That’s a guarantee. Ask the students to stand and mirror you as you walk through verbally and physically demonstrating the key ideas. Use positioning, facial expressions, theater, gesturing and physical memory cues to help reinforce key ideas.

While many of us can say we intuitively knew this list, it took decades of experiments, starting with animal studies, to confirm each of the items listed above. When you see software used in a school setting that works, the real pioneers were rogue bench scientists who did the hard work to figure all this out. The names are not likely familiar to you, but the list would include Norman Weinberger (who passed away recently), Michael Kilgard and Michael Merzenich (who have both presented at our programs), Susan Sara, James McGaugh, and truthfully, a couple dozen other researchers.

One more thing for you to consider. At this stage in your life, you often see an idea and recognize it (familiarity) or feel that you know it well (fluency). Never confuse those two labels with implementation. If you want to do LESS re-teaching, please take the planning time for implementation of at least one or more of the four items mentioned above.

In closing, you CAN have the best school year of your life. Implement ideas from this article and get ready for a miracle!

Your partner in learning, Eric Jensen
CEO, Jensen Learning
Brain-Based Education

CITATIONS:
Aston-Jones G. & Cohen JD. (2005). Adaptive gain and the role of the locus coeruleus-norepinephrine system in optimal performance. J Comp Neurol 493:99.
Chen N, Sugihara H, Sharma J, Perea G, Petravicz J, Le C. & Sur M. (2012). Nucleus basalis-enabled stimulus-specific plasticity in the visual cortex is mediated by astrocytes. Proc Natl Acad Sci U S A.109, 2832-41.
Kilgard, MP & Merzenich, MM (1999). Cortical map reorganization enabled by nucleus basalis activity. Science, 998a; 279: 1714-8.
Kilgard, MP & Merzenich, MM: (1998). Plasticity of temporal information processing in the primary auditory cortex. Nature Neuroscience. 1,727-731.
McGaugh JL (2000) Memory–a century of consolidation. Science 287, 248-251.
Miasnikov AA, Chen JC, Gross N, Poytress BS. & Weinberger NM. (2008). Motivationally neutral stimulation of the nucleus basalis induces specific behavioral memory. Neurobiol Learn Mem. 90,125-37.
Sara SJ, & Bouret S (2012). Orienting and reorienting: the locus coeruleus mediates cognition through arousal. Neuron, 76,130-141.
Schultz W (2010). Subjective neuronal coding of reward: temporal value discounting and risk. Eur J Neurosci 31:2124.
Recanzone G. H., Schreiner C. E. & Merzenich M. M. (1993). Plasticity in the frequency representation of primary auditory cortex following discrimination training in adult owl monkeys. J. Neurosci. 13, 87-103.
Zhang J. Y., Zhang G. L., Xiao L. Q., Klein S. A., Levi D. M. & Yu C. (2010b). Rule-based learning explains visual perceptual learning and its specificity and transfer. J. Neurosci. 30, 12323-12328.