maureen greenbaum's List: 21st Century Teaching

• ense of wonder and curiosity
• participatory learning platform
• people create stuff to be read and tried and critiqued,” where cognitive “apprenticeships” lead to networks of practice. “Deep tinkering” is encouraged

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• Colleges are focused on teaching kids content, not on teaching them skills, and too many students are focused on passing the multitude of tests in the multitude of classes they take, rather than really learning.
• One of the best college grads I ever hired (a graduate of Dartmouth) majored in history. In his job at ITIF (a technology policy think tank) he didn't need to know history. What he needed to know was how to think, how to write, how to speak intelligently, how to find information and make sense out of it, how to argue coherently, and how to do basic math. Fortunately, he had acquired these skills.
• teaching 21st century skills, not 20th century subjects

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• learning resources and opportunities are infinite
• Change your curriculum from a list of what you will say to a list of essential problems (or questions) that students will address, with your guidance, throughout the semester.
  

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  <!--area Type="main" face="Arial,Helvetica,sans-serif" size="2" color="0033cc" style="0"-->   Principles of Teaching as a Subversive Activity (Postman & Weingartner)

• If educational reform is to be successful it must start with how students learn and how teachers teach, not with legislated outcomes.
• The second issue is that most teachers rely on textbooks. W
• we constructed our own text on a wiki.

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• data includes any combination of: location, previous learning activities, health concerns (physical and emotional/mental), attendance, grades, socio-economic data (parental income), parental status, and so on. Most universities will store and aggregate this data under the umbrella of institutional statistics.
• most schools and universities do very little with this wealth of data, other than possibly producing an annual institutional profile report. Even a simple analysis of existing institutional data could raise the profile of potential at-risk students or reveal attendance or assignment submission patterns that indicate the need for additional support.
• An area of data gathering that universities and schools are largely overlooking relates to the distributed social interactions learners engage in on a daily basis through Facebook, blogs, Twitter, and similar tools
• social networks can provide valuable insight into how connected learners are to each other and to the university.
• Discussions about data ownership and privacy lag well behind what is happening in learning analytics. Who owns learner-produced data? Who owns the analysis of that data? Who gets to see the results of analysis? How much should learners know about the data being collected and analyzed?
• I believe that learners should have access to the same dashboard for analytics that educators and institutions see. Analytics can be a powerful tool in learner motivation — how do I compare to others in this class? How am I doing against the progress goals that I set?
• Education is, today at least, a black box. Society invests significantly in primary, secondary, and higher education. Unfortunately, we don't really know how our inputs influence or produce outputs. We don't know, precisely, which academic practices need to be curbed and which need to be encouraged. We are essentially swatting flies with a sledgehammer and doing a fair amount of peripheral damage.
• Once we better understand the learning process — the inputs, the outputs, the factors that contribute to learner success — then we can start to make informed decisions that are supported by evidence.
• today, our learning content is created in advance of the learners taking a course in the form of curriculum like textbooks. This process is terribly inefficient. Each learner has differing levels of knowledge when they start a course. An intelligent curriculum should adjust and adapt to the needs of each learner. We don't need one course for 30 learners; each learner should have her own course based on her life experiences, learning pace, and familiarity with the topic. The content in the courses that we take should be as adaptive, flexible, and continually updated. The black box of education needs to be opened and adapted to the requirements of each individual learner.
• assessment should be in-process, not at the conclusion of a course in the form of an exam or a test.
• Much of the current focus on analytics relates to reducing attrition or student dropouts. This is the low-hanging fruit of analytics. An analysis of the signals learners generate (or fail to — such as when they don't login to a course) can provide early indications of which students are at risk for dropping out. By recognizing these students and offering early interventions, schools can reduce dropouts dramatically.
• Companies like Grockit and Knewton are creating personalized adaptive learning platforms.
• The profile of the learner, not pre-planned content, needs to drives curriculum and learning opportunities.

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• just 56 percent of those who enroll in a four-year college earn a bachelor’s degree.
• more than half of first-year students are simply underprepared for college-level work
• U.S. has fallen from leader to 12th place in the ratio of young people with the equivalent of a bachelor’s degree, well behind Russia, Canada, Korea and Japan.
• four-year college degree can earn far more than those with just a high school diploma, $60,954, on average, in 2008, compared with $33,618
• education achievement gap cost between $1.3 trillion and $2.3 trillion in lost gross domestic product

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• The underlying principle is simple: Students learn math by doing math, not by listening to someone talk about doing math. Interactive computer software, personalized on-demand assistance, and mandatory student participation are the key elements of success.
• What is critical is the pedagogy: eliminating lecture and using interactive computer software combined with personalized, on-demand assistance.
• ALEKS, Hawkes Learning Systems, or MyMathLab, students are able to spend more time on task
• immediate support and don't want to admit before fellow students that they do not understand. So they often do not get answers to the questions they have. In addition, homework problems are typically hand-graded and returned days after the students have made mistakes. By the time they see the graded homework, they are not sufficiently motivated to review their errors.
• Instant feedback lets students review their errors at the time they make them and immediately get assistance from online tutorials and guided solutions, as well as from fellow students. In several of the math emporia, computer stations are arranged in pods of four to six to encourage collaboration

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• Roughly half of entering college students from low-income families drop out empty handed.
• But money and family obligations aren’t the only barriers to college completion.

• n recent American students were asked to rate their own abilities, they were more likely than previous generations to rate themselves above average on attributes like academic ability, drive to achieve, leadership ability, self-confidence, and writing ability.

   
• Groups of students who reported studying for fewer hours tended to rate themselves higher in achievement drive.
• 75 percent of 2011 high school graduates who took the ACT were not prepared for a university education in one or more core areas, including English, reading, math, and science.
• The New York Times, more than one million students are forced to take remedial college classes each year.

• What happens when overly confident college students come face to face with the reality of their skill deficits?

   
• 40 percent of students who left did so because of poor academic performance

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• vidence is unequivocal: Those with college degrees, on average, earn far more than those without them.
• 90% of these young college graduates were employed in 2010, compared with only 64% of their peers who did not attend college but went straight on to look for work. Even more astounding, the college graduates are making, on average, almost double the annual earnings of those with only a high school diploma. And this advantage is likely to stick with them over a lifetime of work. For example, at age 50 a college graduate earns about $46,500 more per year than the average person with only a high school diploma.

• Andragogy consists of learning strategies focused on adults. It is often interpreted as the process of engaging adult learners with the structure of learning experience. The term ‘andragogy’ has been used in different times and countries with various connotations

• Knowles asserted that andragogy (Greek: "man-leading") should be distinguished from the more commonly used pedagogy (Greek: "child-leading").

   

  Knowles' theory can be stated with six assumptions related to motivation of adult learning:^[1][2]

   
   
  1. Adults need to know the reason for learning something (Need to Know)
   
  2. Experience (including error) provides the basis for learning activities (Foundation).
   
  3. Adults need to be responsible for their decisions on education; involvement in the planning and evaluation of their instruction (Self-concept).
   
  4. Adults are most interested in learning subjects having immediate relevance to their work and/or personal lives (Readiness).
   
  5. Adult learning is problem-centered rather than content-oriented (Orientation).
   
  6. Adults respond better to internal versus external motivators (Motivation).
   
   

  The term has been used by some to allow discussion of contrast between self-directed and 'taught' education

• their belief in the importance of technology to make change happen in a system that hasn’t changed in decades.
• Newark Mayor Cory Booker shared that he can no longer watch the way school systems have worked, there has to be change. Technology, he believes, can bring that change.
• theme of the night appeared to be data. Educational institutions have a huge flow of data, some not even digitized, and have no way to pour through it to make smart decisions for their schools or more importantly for their students.
• use data to incentive students
• share lesson plans all over the world.

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• The evidence is irrefutable that computerised automation, networks and artificial intelligence (AI)—including machine-learning, language-translation, and speech- and pattern-recognition software—are beginning to render many jobs simply obsolete.
• machines gradually replaced the muscle-power of human labourers and horses. Today, automation is having an impact not just on routine work, but on cognitive and even creative tasks as well. A tipping point seems to have been reached, at which AI-based automation threatens to supplant the brain-power of large swathes of middle-income employees.
• Not only is AI software much cheaper than mechanical automation to install and operate, there is a far greater incentive to adopt it—given the significantly higher cost of knowledge workers compared with their blue-collar brothers and sisters in the workshop, on the production line, at the check-out and in the field.
• “more sophisticated software technologies are going to bring civilisation ever closer to a near-workerless world.”
• data-analytics, business-intelligence and decision-making software do a better and cheaper job, even professionals are not immune to the job-destruction trend now underway. Pattern-recognition technologies are making numerous highly paid skills redundant.
  
• Lawyers are in a similar boat now that smart algorithms can search case law, evaluate the issues at hand and summarise the results. Machines have already shown they can perform legal discovery for a fraction of the cost of human professionals—and do so with far greater thoroughness than lawyers and paralegals usually manage.
• those threatened the most by technology should learn to work with machines, rather than against them. Do that, they suggest, and the shake-out among knowledge workers becomes less of a threat and more of an opportunity.
• The things that make people human—the ability to imagine, feel, learn, create, adapt, improvise, have intuition, act spontaneously—are the comparative advantages they have over machines. They are also the skills that machines, no matter how smart, have had the greatest difficulty replicating.
• Marina Gorbis of the Institute for the Future, an independent think-tank in Palo Alto, California, believes that, while machines will replace people in any number of tasks, “they will amplify us, enabling us to do things we never dreamed of doing before.” If that new “human-machine partnership” gives people the dignity of work, as well as some means for financial reward, all the better. But for sure, the world is going to be a different place.

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