Learning and the Brain Presentation: Daniel Willingham

Daniel Willingham, a cognitive scientist and author of Why Don't Students Like School, made an insightful presentation at the Learning and the Brain Conference in DC. As you read through these "tweets," keep in mind that I was posting the comments/ideas of the presenter. These do not necessarily represent my conclusions from the research.

These are my "tweets" posted live from Willingham's presentation at the conference.

• Will use initials DW to indicate Willingham’s comments/ideas.
• DW: Title of pres: Why Students Don’t Like School.
• DW: Interest in topic sprung from daughter’s excitement over possible snow days.
• DW: Daughter basically liked school but would have chosen to not have it most days.
• DW: How to make classroom activities more appealing? What drives our choices.
• DW: Factors of choice: 1. Outcome of choice 2. Probability of outcome 3. Costs of choice 4. Personality.
• DW: Outcomes can be concrete, can be emotional. Probability of outcome influences effort.
• DW: Cost: is task easy? hard? Relationship of effort required to probability of outcome.
• DW: Personality factors: self-discipline, carefulness, thoroughness, organization,
• deliberate, need for achievement.
• DW: Appeal of choice=outcome x probability/input x personality (figuratively!).
• DW: Policy-makers only think in terms of personality: “Kids just need more ‘grit.’”
• DW: Teachers think in terms of interest. Better to think about probability—how can we make students successful.
• DW: When psychological pain of risk is higher than psychological gain, people do not want to participate.
• DW: Opportunity to gain more is not the sole factor in choices—e.g., 50% of winning $30 vs. risk of losing $20.
• DW: The potential loss is the weightier factor in choices, not the potential gain. What are student losses.
• DW: Student losses: failure and shame. Fear of loss influences effort.
• DW: Make sure students experience successes. Minimize the “loss”—e.g., failure is not a terrible thing.
• DW: It’s a tough sell, but unique to schools. Kids fail at video games, but see it as learning. Think of academic work differently.
• DW: Dweck’s work indicates beliefs about intelligence contribute to this different view of failure. (More info on student beliefs & learning.)
• DW: At every possibility, emphasize the malleability of intelligence—something you get not something you are.
• DW: “Time discounting”: time between choice & outcome influences power of influence— e.g., ice cream in store vs. ice cream in bowl.
• DW: Example, value of money given now considered more valuable than same amount promised to be given to you later.
• DW: If you want child to value the outcome, the outcome needs to be almost immediate. Promised future rewards have no appeal.
• DW: Most academic outcomes are distant—diplomas, grades, pizza party on Friday.
• DW: Evaluations of outcomes are relative. Framing outcomes example: Tom Sawyer painting fence.
• DW: Software engineers reframing: “It’s not a bug, it’s a feature.”
• DW: Teachers should frame for positive outcomes not negative outcomes. Emphasize reward not punishment.
• DW: Punishment gets compliance only as long as “punisher” is present. Rewards are longer lasting.
• DW: Rewards change behavior, often to the point of internalization—e.g., I’m a kid who turns in things on-time.
• DW: Example of framing: UVA honor system—most profs emphasize the penalty of dismissal rather than how students can live up to idea.
• DW: Reasonable goals for each “session” (e.g., exercise) promote success. Daily targets are better than full goal.
• DW: Example: not “writing my dissertation” but “writing 200 words today.
• DW: Small goals help because they seem achievable. “Good grade” goal—success unknown. “Do this today”—manageable outcome.
• DW: Another approach: fuse a task with a more desirable task—charities do this: attend a concert rather than give $ outright.
• DW: Example in edu: gaming in the classroom (e.g., Jeopardy in classroom).
• DW: Scheduling also helps—daily schedule for completing a term paper works better than just deadlines for final papers.
• DW: Emotional support > guilt. e.g., exercising with a friend (support) vs. working alone.
• DW: Group work where students are responsible to one another—hard to pull-off, but effective if achieved.
• DW: Personality elements: student’s self-image as a student. Students who feel they don’t belong in school are overwhelmed by image.
• DW: How does a student reach this conclusion, this hindering self-image. This is not self-esteem.
• DW: Students need to feel 1) I’m needed here, and 2) I can contribute. How do we encourage this.
• DW: Emphasize classroom as community, everyone has responsibilities, everyone participate in range of activities.
• DW: …everyone tastes success and failure. Curriculum needs to be broad (e.g., science gets only about 5-6% of 3rd grade time.)
• DW: Challenges for teachers: creating community, vulnerability (teacher’s willingness to fail, tendency to control).

TMI! Information Overload and Learning

“Too much information—TMI!”

More than just a retort when conversations turn personal, TMI also describes a common student experience. When one period of steady information flow follows another, the rising data tide does not lift all boats. It overwhelms them.

We can maintain a quick and steady pace when we enter information into a database or spreadsheet, simply pushing “return” or “tab” to move to the next entry, but the brain is not a computer. It has limits. Data funneled endlessly through the senses prevents the processing required for learning.

What do students’ brains need to do to construct new learning? Let’s listen in as the neural “Data Manager” oversees the processing…

Okay, we got incoming data here. Everyone look alive!

Get that bit there and put it with the other that’s like it. Those two bits there, move them to the right. Move those others across the room to that grouping there.

Is that it? Do we have all the data? Okay, let me get up to the observation platform to see what we’ve got here. Hmm, okay. Put this label on that grouping there. And give that group to the right this label. That last group needs this label.

Okay, let’s see what’s really going on here. Seeing some patterns! Get the librarians searching for past records with these patterns.

Got something? Great. Let’s overlay it with this new data.

A-ha! The new data is like this past experience in some ways. Get the insights to the consciousness office and tell them to hit the “Give a lift” button! We’re constructing understanding right now!

Obviously no such director exists for cognitive activity, but the processing illustrated by the imagined “Data Manager’s” actions do reflect the brain’s approach to constructing new learning. Incoming data gets sorted and labeled as the brain engages in comprehension. The sorted and labeled data reveals emerging patterns that trigger recall of similar past experiences as the brain engages in elaboration. These cognitive processes empower learning.

But TMI floods the brain with data, preventing comprehension and elaboration, and thus, preventing learning. Jonah Lehrer suggests the danger of too much information is “it can actually interfere with understanding.” Why? Because the brain has a do-it-yourself attitude toward learning.

As teachers, we think through material when we plan its delivery. But students’ brains need to engage in that same process to learn for themselves. In short, we process the new material to teach it. Students must process the information similarly to learn it. As Daniel Willingham, author of Why Don't Students Like School?, explains, “Good teachers design lessons in which students unavoidably think about the meaning or central point” [emphasis added]. Thinking cannot overcome TMI, but TMI quickly overwhelms thinking. In short, TMI prevents learning while unavoidable thinking promotes it.

When you stop informing and engage students in thinking, you empower learning. In other words, you truly teach.