The Motivation Equation

Screen Shot 2013-07-11 at 2.11.26 PMThe upcoming new ibook by Kathleen Cushman, “The Motivation Equation,” stands to expand on her pioneering work in leveraging students’ voices in shaping learning environments, pedagogical practices, and transforming how we talk about learning. And thank goodness.

Often missing from our education discourse is, ironically, the most important element of our education system: the learners.

In this newest endeavor (you can read an early release of the book for a limited time here), Kathleen seeks to provide information on “designing lessons that set minds free.” QED’s Chief Education Officer, Kim Carter, had this to say after reading the book:

Motivation is the holy grail of learning. Who doesn’t believe if learners are motivated, they have a much greater likelihood of successful learning?  From the Introduction’s explanation that “motivation is not something you have at the start” to its Appendices packed with additional resources, The Motivation Equation is brilliant on so many levels.  Let me name four:

  1. Kathleen’s synthesis of the essential mind, brain and education science related to motivation into 8 steps or conditions is mind-bogglingly clear.
  2. More importantly, the 8 steps are readily accessible and practical.
  3. The Motivation Equation is rich with student voices – offering a “unique ‘trialogue’ among students, teachers, and learning scientists” – which anchor the steps and the research in familiar realities.
  4. The Motivation Equation is the best (ever) use of the e-book medium that I have seen to date. Unerring integration of sound and video clips, call-out boxes for brief bios and research notes, links to additional resources, survey templates, and protocols for engaging learners in exploring their own motivation represent a treasure trove of value-added resources.

Still need convincing to check it out? Visit WKCD‘s new website, How Youth Learn, for research highlights and videos of student voices.

How Youth Learn: Ned’s GR8 8

This video needs no introduction. Just watch it and then file it under — “When Student Voices Align With Research From the Science of Learning.”

How to Increase Group IQ

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The following is a guest post by Annie Paul Murphy – book author, magazine journalist, consultant and speaker who helps people understand how we learn and how we can do it better. This post was originally published on her site, The Brilliant Blog.

What makes a group intelligent? That is: what enables a team of people to effectively solve problems and produce solutions? You might think a group’s IQ would be simply the average intelligence of the group’s members, or perhaps the intelligence of the team’s smartest participant. But researchers who study groups have found that this isn’t so.

Rather, a group’s intelligence emerges from the interactions that go on within the group. A team’s intelligence can be measured, and like an individual’s IQ score, it can accurately predict the team’s performance on a wide variety of tasks. And just as an individual’s intelligence is malleable and expandable (a big theme of The Brilliant Blog), a group’s intelligence can also be increased. Here, seven suggestions to guide the development of smart teams:

1. Choose team members carefully. The smartest groups are composed of people who are good at reading each others’ social cues, according to a study led by Carnegie Mellon University professor Anita Williams Woolley and published in the journal Science. (Woolley and her collaborators also found that groups that included a greater number of women were more intelligent—but the researchers think this is because women tend to be more socially sensitive than men.)

2. Share the floor. On the most intelligent teams, found Woolley et al., members take turns speaking. Participants who dominate the discussion, or who hang back and don’t say much, both bring down the intelligence of the group.

3. Talk about the “how.” Many members of teams don’t like to spend time talking about “process,” preferring to get right down to work—but Woolley notes that groups who take the time to discuss how they will work together are ultimately more efficient and effective.

4. Make sure members spend time face-to-face. L. Michelle Bennett and Howard Gadlin, two high-level administrators at the National Institutes of Health, performed in-depth interviews with members of five teams of NIH scientists. The conclusions they drew from these interviews, published in the Journal of Investigative Medicine, point to the importance of bridging the physical distance between the members of a team. The most successful collaborations assembled regularly for video conferences, or better yet, in-person meetings.

5. Foster informal social connections among members. Sandy Pentland, an MIT professor who studies group dynamics, has found that the smartest teams spend a lot of time communicating outside of formal meetings. He tells of a call center where team members’ coffee breaks were staggered across the workday. Changing the schedule so that all the members of a team had a coffee break at the same time led the workers to do their work more efficiently and to feel more satisfied with their jobs.

6. “Modularize” the work to be done. Bennett and Gadlin of the NIH advise groups to break up big tasks into distinct chunks that can be distributed among team members. Just because you’re working together doesn’t mean each member must have a spoon in every pot. Make sure that the correct incentives are in place, too: if your teammate’s boss rewards individual achievement but not productive collaboration, it won’t be long before your team falls apart.

7. Make contingency plans. While no one wants to think about it in the exciting early days of a project, group ventures do sometimes fail—so it’s important for prospective team members to write and sign what Gadlin calls a “prenuptial agreement,” spelling out how responsibilities are to be allocated, how credit is to be awarded—and who gets custody of the work if the collaboration should falter.

Abstracts of the studies mentioned here can be found on my blog.

Photo Credit: Lin Schorr via Compfight cc

Variability Matters

We design for variability we can see. But what about the variability we can’t?

By default, we tend to design learning environments for efficiency and the average student, but in doing so do we limit the potential inherent in the unseen variability of students’ brains? Are we, by default, failing to capitalize on one our nation’s most underutilized assets: diversity? Todd Rose thinks so.

Here is a short 10-minute lecture by Dr. Rose, whose biography at Harvard’s Mind, Brain and Education website reads:

Todd Rose is a research scientist with CAST and a faculty member at the Harvard Graduate School of Education, where he teaches Educational Neuroscience. His work is organized around six themes: human variability; course design and pedagogy in higher education; adaptive learning analytics; interdisciplinary thinking; the synergistic relationship between neuroscience, technology, and design in education; and the application of dynamic systems models to the study of behavior, learning, and development.

He makes a strong case for re-thinking how we go about designing learning environments that “genuinely support the full range of the learners in our classrooms.” He argues for cultivating an ecosystem of “learning opportunities” through “understanding variability and understanding how to design for it” as a method for leveraging the diversity of our student body, and making schools/cyberlearning more relevant, meaningful, and valuable in the process. We could not agree more.

It is a concept whose time has come.

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Want to know more about variability and designing for it in the classroom? Check out these resources:

Feel free to share other resources in the comments below.

This post is part of our Transformational Learning series and relates to Culture, Curriculum Goals, Academic Access, and Personalization.  

Photo Credit: ThreeHeadedMonkey via Compfight cc

Fixed vs. Growth Mindsets

Mindset, the seminal book by Carol Dweck, a Stanford University psychologist, unpacks the difference between a fixed mindset and a growth mindset.

In a fixed mindset, the belief is that intelligence is fixed and static. You are smart, or you aren’t. This was the widely accepted theory of cognitive development until a series of experiments in the 50’s and 60’s by UC Berkley professor, Mark Rosenzweig. His work with environmental influences on rats turned the idea of innate intelligence upside down.

In contrast, a growth mindset is the belief that intelligence is dynamic and that the brain changes based on experiences. This theory of growth mindset is supported by research into brain plasticity and has proven to be pivotal in helping students improve their academic achievement. (You can listen to an NPR story about this here.)

Below is an image that illustrates the (generalized) difference in behaviors between people of each mindset.

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Image: Nigel Holmes / Graph Content: Carol Dweck

Royal Society Recommendations for Neuroscience in Education

The Royal Society, a self-governing Fellowship of scientists from around the world dedicated to “excellence in science and to encourage the development and use of science for the benefit of humanity,” released a series of modules in 2011 as part of their Brain Waves Project. The four modules explore the intersection of neuroscience, society and public policy with summarized analyses of research, challenges and recommendations.

The second module, Neuroscience: Implications for education and lifelong learning, is of particular importance for educators and policy makers alike. As we find that the world of neurology continues to make strides in understanding how the brain develops, changes and learns, we also find that there is a hunger for such knowledge at the classroom level. As a result there are more and more programs that help bridge the gap between research and practice.

However, there are still many steps to be made. Toward that end, the authors of the education module list four “recommendations from the emerging field of educational neuroscience which might inform educational policy across all ages.”

1. Neuroscience should be used as a tool in educational policy.

Neuroscience evidence should inform the assessment of different education policy options and their impacts where available and relevant. Neuroscience evidence should also be considered in diverse policy areas such as health and employment.

Stronger links within the reach community and between researchers and the education system (schools, further education, higher education and institutes for lifelong learning) are needed in order to improve understanding of the implication of neuroscience for education. (Empasis theirs.)

2. Training and continued professional development should include a component of neuroscience relevant to educational issues, in particular, but not restricted to, Special Educational Needs.

Findings from neuroscience that characterise different learning processes can support and enhance teachers’ own experiences of how individuals learn. These findings can be used to inform alternative teaching approaches for learners of different abilities. However, at present neuroscience rarely features as part of initial teacher training courses or as part of continued professional development.

3. Neuroscience should inform adaptive learning technology.

Neuroscience can make valuable contributions to the development of adaptive technologies for learning. The Technology Strategy Board should promote knowledge exchange and collaboration between basic researchers, front-line practitioners and the private sector in order to inform and critically evaluate the impact and development of new technologies.

4. Knowledge exchange should be increased.

A knowledge exchange network is required to bridge disciplines, this should include a professionally monitored web forum to permit regular feedback between practitioners and scientists and to ensure that research is critically discussed, evaluated and effectively applied. High quality information about neuroscience on a web forum could also be made available to the general public . . . (who) will benefit from learning about the changes that are going on in their own brains and how this can affect their own learning.

The implications for education policy and implementation are clear and transferable around the world: Learning about leaning matters, and the greater collaboration and communication we can have between researchers, educators and policy makers, the better off our students will be.

BRAIN POWER: From Neurons to Networks

Here is a cleverly constructed and informative video by Tiffany Shlain, author of Brainpower: From Neurons to Networks.

12 Brain Rules

Below are the 12 Brain Rules developed by John Medina. Each link will take you to his site and to more information about each of the rules.

You can find the original list in his book “Brain Rules” and on his Brain Rules website.

Enjoy.

Exercise EXERCISE | Rule #1: Exercise boosts brain power.
Evolution SURVIVAL | Rule #2: The human brain evolved, too.
wiring WIRING | Rule #3: Every brain is wired differently.
attention ATTENTION | Rule #4: We don’t pay attention to boring things.
<img src="http://www.brainrules.net/images/icon_shortterm_m cheap viagra 100mg.gif” alt=”shortterm” /> SHORT-TERM MEMORY | Rule #5: Repeat to remember.
longterm LONG-TERM MEMORY | Rule #6: Remember to repeat.
sleep SLEEP | Rule #7: Sleep well, think well.
stress STRESS | Rule #8: Stressed brains don’t learn the same way.
multisensory SENSORY INTEGRATION | Rule #9: Stimulate more of the senses.
vision VISION | Rule #10: Vision trumps all other senses.
gender GENDER | Rule #11: Male and female brains are different.
exploration EXPLORATION | Rule #12: We are powerful and natural explorers.

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