Archive for the ‘education innovation’ Category

Experts from around the web share tactics and advice for educators who want to make the most of Google Forms.

Source: Tech Tips for Teachers: 4 Ways to Use Google Forms | EdTech Magazine

“I was so intent on finding a specific answer that I didn’t realize I was asking the wrong question. It was time to stop looking for the answer. It was time to ask new questions.

Here are the new questions I asked myself (and that you can ask yourself) that changed how I looked at this problem, at myself and at each future challenge:”

Source: Reframe Problems with These 5 Questions | SUCCESS

Open Innovation companies that help you innovate and solve problems. Click on a heading to add your comment or review.

Source: IdeaConnection: Outsourcing Innovation, Open Innovation

“The fight in Massachusetts has been dizzying, with a strange alliance between the teachers’ union and a conservative think tank that years before had been a chief proponent of the state’s earlier drive for standards and high-stakes tests. As in other states, conservatives complained of federal overreach into local schooling, while the union objected to tying the tests to teacher evaluations. The debate drew money from national political players like the billionaire David Koch and the Bill & Melinda Gates Foundation.” (excerpt)

Source: Massachusetts’s Rejection of Common Core Test Signals Shift in U.S. – The New York Times

Video games have expanded rapidly and created a large and growing industry since the 1980s.

Source: There’s more to gamification than just playing games

CompetencyWorks is an online resource dedicated to providing information and knowledge about competency education in the K-12 education system. Drawing on lessons learned by innovators and early adopters, CompetencyWorks shares original research, knowledge and a variety of perspectives through an informative blog with practitioner knowledge, policy advancements, papers on emerging issues and a wiki with resources curated from across the field. CompetencyWorks also offers a blog on competency education in higher education so that the sectors can learn from each other and begin to align systems across K-12, higher education and the workplace.

via Competency Works.

“Rather than placing tech leaders on a pedestal, we should put their successes in context, acknowledging the role of government not only as a supporter of basic science but as a partner for new ventures. Otherwise, it is all too easy to denigrate public-sector investment, eroding support for government agencies and training programs and ultimately putting future innovation at risk. As Mazzucato puts it, “It’s precisely because we admire Musk and think his contributions are important that we need to get real about where his success actually comes from.” (excerpt)

via Putting Elon Musk and Steve Jobs on a Pedestal Misrepresents How Innovation Happens | MIT Technology Review.

I recognize that this could politicized, and that’s not my intention for sharing this. Educators, after all, work best when they approach educating with an open mind (or open mindset) and flexibility. This is a reason education is both an art and a science. On the other hand, we should be careful about being “early adopters”. We should explore new ideas and tools, but we should approach these explorations with awareness and with special attention to measuring (somewhat objectively) what we hope to achieve against what was actually achieved (somewhat objectively).


The Neurocritic: Against Initiatives: “don’t be taken in by the boondoggle”.


Here’s Professor Leah Krubitzer, who heads theLaboratory of Evolutionary Biology at University of California, Davis:

“From a personal rather than scientific standpoint, the final important thing I’ve learned is don’t be taken in by the boondoggle, don’t get caught up in technology, and be very suspicious of “initiatives.” Science should be driven by questions that are generated by inquiry and in-depth analysis rather than top-down initiatives that dictate scientific directions. I have also learned to be suspicious of labels declaring this the “decade of” anything: The brain, The mind, Consciousness. There should be no time limit on discovery. Does anyone really believe we will solve these complex, nonlinear phenomena in ten years or even one hundred? Tightly bound temporal mandates can undermine the important, incremental, and seemingly small discoveries scientists make every day doing critical, basic, nonmandated research. These basic scientific discoveries have always been the foundation for clinical translation. By all means funding big questions and developing innovative techniques is worthwhile, but scientists and the science should dictate the process.”


Dweck: Actually, praise may not be the optimal way, but we are so praise oriented. We can ask the child questions about the process: “How did you do that? Tell me about it.” As they talk about the process and the strategies they tried, we can appreciate it. We can be interested in it. We can encourage it. It doesn’t have to be outright praise.

via Too Many Kids Quit Science Because They Don’t Think They’re Smart – The Atlantic.


Dweck’s conclusions about how praise works should help shape discussions about parenting, teaching, feedback, and also around the building of credibility THROUGH appreciation. The boundaries are dissolving between education and other knowledge work fields but also between educators and learners. Students will recognize real interest and appreciation of their thinking-work as truly valuing work. Attention is one of the main currencies of the knowledge era. The more attention being paid to what you are doing, the more encouragement you feel that what you are doing is valuable and valued. These are the face-to-face “likes” that do more than vaguely acknowledge you have accomplished something. When time is spent listening, evaluating the student’s process and progress, and asking questions that leads to more progress, students will deepen their interest, become more encouraged, and may increase in other areas as well.

This is true for any worker, though. In education, the teacher is a knowledge worker, and the public awareness of teacher supervision can give insights into Davenport and Maccoby’s recognition that knowledge workers often know more about their areas of expertise than their supervisors.

No teacher wants to simply be observed and assessed based on a pass/fail system. Teachers want to feel that the person observing them “gets” what the teacher is doing, what the teacher has accomplished. In the Danielson tool, this appreciation has the opportunity of expression when discussing planning and also in the follow up or post-observation debriefing. Cognitive coaching models are appreciation and credibility-building tools.

extensive excerpt:

“A number of comprehensive models of school learning have been advanced to describe and explain the school learning process (see McGrew, Johnson, Cosio, & Evans, 2004).  Walberg’s (1981) theory of educational productivity is one of the few empirically tested theories of school learning.  Walberg’s model is based on an extensive review and integration of over 3,000 studies (DiPerna, Volpe & Stephen, 2002; Wang, Haertel, and Walberg, 1997).  Walberg et al. reported that the following key variables are important for understanding school learning—student ability and prior achievement, motivation, age or developmental level, quantity of instruction, quality of instruction, classroom climate, home environment, peer group, and exposure to mass media outside of school (Walberg, Fraser & Welch, 1986).  The first three variables (ability, motivation, and age) reflect student individual difference characteristics.  The fourth and fifth variables reflect characteristics of instruction (quantity and quality), and the final four variables (classroom climate, home environment, peer group, and exposure to media) represent aspects of the psychological environment(DiPerna et al., 2002).  Clearly student characteristics are important for school learning, but they only comprise a portion of the complete learning equation.

“The Walberg research group (see Wang, Haertel, & Walberg, 1993) also concluded that psychological, instructional, and home environment characteristics (proximal variables) had a more significant impact on achievement than variables such as state-, district-, or school-level policy and demographics (distal variables).  More important for practicing school psychologists was the conclusion that student characteristics (i.e., social, behavioral, motivational, affective, cognitive, metacognitive) were the set of proximal variables that had the most significant impact on learner outcomes (DiPerna et al., 2002).”

via IQ’s Corner: The Motivation and Academic Competence MACM Commitment Pathway to Learning Model: Crossing the Rubicon to Learning Action.