Bad bargain: Why we still ask kids to factor polynomials and how we fix it — from gettingsmart.com by Tom Vander Ark

Excerpt:

OK, we cut a bad deal 20 years ago and it’s time to fix it.

Kids are still factoring polynomials and that’s just dumb. Requiring every student to pass a course on regurgitated symbol manipulation (Algebra 2) is torturous for many students and why some dropout. It’s an inequitable barrier to college and careers.

“The tragedy of high school math,” said venture investor and education advocate Ted Dintersmith (who has a Ph.D. in math modeling), “is that less than 20% of adults ever use algebra. No adult in America still does integrals and derivatives by hand – the calculus that blocks so many from career paths. It remains in the curriculum because it’s easy to test, not important to learn.”

Math educator Dan Meyer told the We’re Doing It All Wrong Podcast that algebra 2 is “arcane gibberish…not useful knowledge”…

Now, rather than the plug and crank of symbol manipulation, we should be teaching computational thinking. As mathematician Conrad Wolfram said, we should be teaching math as if computers existed.

Rather than a separate symbol language, Wolfram argues, math should be taught as computational thinking and integrated across the curriculum. That starts with problem finding–spotting big tough problems worth working on. Next comes understanding the problems and valuables associated–that’s algebraic reasoning. But rather than focusing on computation (including factoring those nasty polynomials), students should be building data sets and using computers to do what they’re good at–calculations.

To fix the problem, states that require Algebra 2 should swap it out for a course in coding and computational thinking. Colleges and college entrance exams should drop Algebra 2 requirements. They should start by asking young people about their contributions to solving big problems.

 

From DSC:
This posting reminded me that, just the other day, I took the picture below…it’s outside a local mall. The annotated picture below gives you some of my thoughts on this ridiculous setup. 

 

Are some of our educational systems setup like this stop sign outside an abandoned, old store that's no longer being used?!

 

 

 

Five key trends for professional and continuing education leaders in the next five years — from evolllution.com by Ray Schroeder

Excerpts:

Higher education is on the cusp of major changes. Enrollments are on the decline—both online and on campus—and the trend is expected to accelerate.[1] Graduates are laboring under substantial college loan debts totaling more than $1.5 trillion.[2] Employers are demanding that applicants possess soft and hard skills that many college graduates do not hold.[3] At the same time new and emerging technologies are changing the way credentials are shared and work is done.

It is in this context that continuing, professional and online programs have been imported from the periphery to the center of traditional universities. Students and employers alike have made clear that their top priority is relevance to the rapidly changing workplace. Artificial intelligence, blockchain, augmented/virtual reality and other technologies are driving the changes. Professional and Continuing Education (PCE) has long been the leader in providing relevant courses, certificates and degrees that connect students with the needs of employers.

 

…the Online Master’s Science in Computer Science degree at Georgia Tech is now the largest computer science program in the world. And the degree costs less than $9,000.

 

Also see:

Interview with Hunt Lambert – What is the 60-year curriculum?
Colleges and universities used to be primarily responsible for a four-year learning experience. We now need to envision a 60-year curriculum, whereby educational institutions partner with learners at all stages of their professional career, providing skills and knowledge as needed.

 


 

 

 


 

 

From DSC:
For anyone out there who thinks that teaching and learning is easy and who agrees with the uninformed saying that goes “Those who can’t do…teach”…might I recommend a few potential to-do’s for you to try out…?

  1. Try teaching 30-35 students yourself for at least 4-6 weeks about a topic that you just found out that you’ll be teaching and one that you don’t know much about. (And see if you enjoy the process that some teachers sometimes have to go through…putting down the tracks right in front of the trains that are rapidly moving down the tracks right behind them.) Also, you must have at least one student in your class who requires an Individualized Education Program (IEP) as well as 4-5 students who constantly cause trouble and who don’t want to be in school at all.
    .
  2. Identify each student’s strengths, weaknesses, and learning preferences — and their Zone of Proximal Development — then customize the learning that each of your 30-35 learners receives (with the goal of keeping each student moving forward at their most appropriate pace, while staying encouraged and yet appropriately challenged).
    .
  3. Attend Individualized Education Program (IEP) meetings and work with other IEP team members to significantly contribute to the appropriate student’s (or students’) teaching and learning environment(s). For a real challenge, at least one of those students will be someone who is struggling, but is very much hanging in there — someone who is “right in the middle of the pack,” so to speak. (My guess is that if you did this, you would never think of teaching, nor teachers, nor other specialists in quite the same way again. My guess is that you would develop a whole new appreciation for how complex teaching and learning really is.)

Regarding that last item about at least one of your students requiring an IEP, here are some questions that might come up:

  • What specialized services are needed this year?
  • What do the teachers need to know about this student’s cognitive processing/executive functioning?
  • How has the student been doing with the specialized services and teaching and learning strategies that have been attempted since the last IEP meeting? 
  • If their scores are going down, how are you going to address that issue (especially given limited resources)?
  • How is the student’s motivation level doing? Is attending school still a positive experience? Or are things starting to become negative and/or downright painful for the student? Are they starting to get bummed out about having to come to school?
  • How are they relating with and collaborating with other students? If poorly, how are you going to address that issue? How are you going to handle group-related projects (especially after reading all of those articles that assert which skills the workplace values these days)?
  • What do you do with grades and assessments? Do you treat the student differently and give them higher grades to keep them encouraged? But if you do that, will your school system back you up on that or will someone come down hard on you for doing that? Or, perhaps you will find yourself struggling internally — trying to figure out what grades are really for and wondering if they are helpful in the first place. In fact, you might find yourself wondering if grades aren’t really just a mechanism for ranking and comparing individuals, schools, and even entire school systems (which, as we know, impacts property values)? 
  • What do grades really produce — game players or (lifelong) learners? It won’t surprise you to know that I would argue that the former is what gets “produced.”  Grades don’t really produce as many learners as they do game-players (i.e., students who know the minimum amount of work that they need to do and still get that all important A).

So, as you can hopefully see here, learning is messy. It’s rarely black and white…there’s a lot of gray out there and a lot of things to consider. It’s not a one-size fits all. And teaching others well is certainly NOT easy to do! 

RELEVANT IDEAS:

While I’m thinking about related ideas here…wouldn’t it be great if EVERY. SINGLE. STUDENT. could have their own IEP and their own TEAM of specialists — people who care about their learning?

What if each student could have their own cloud-based learner profile — a portion of which would be a series of VoiceThreads per student, per period of time (or per mastering a particular topic or area)?  Such VoiceThreads could include multimedia-based comments, insights, and recommendations for how the student is doing and how they best learn. Through the years, those teams of people — people who care about that student’s learning — could help that student identify their:

  • strengths
  • weaknesses
  • passions/interests
  • their optimal learning strategies and preferences
  • potential careers

The students could periodically review such feedback.

 

 

For every single student, we could build a history of feedback, helpful suggestions, 
and recommendations via audio, video, text, graphics, etc.

 

 

LinkedIn 2019 Talent Trends: Soft Skills, Transparency and Trust — from linkedin.com by Josh Bersin

Excerpts:

This week LinkedIn released its 2019 Global Talent Trends research, a study that summarizes job and hiring data across millions of people, and the results are quite interesting. (5,165 talent and managers responded, a big sample.)

In an era when automation, AI, and technology has become more pervasive, important (and frightening) than ever, the big issue companies face is about people: how we find and develop soft skills, how we create fairness and transparency, and how we make the workplace more flexible, humane, and honest.

The most interesting part of this research is a simple fact: in today’s world of software engineering and ever-more technology, it’s soft skills that employers want. 91% of companies cited this as an issue and 80% of companies are struggling to find better soft skills in the market.

What is a “soft skill?” The term goes back twenty years when we had “hard skills” (engineering and science) so we threw everything else into the category of “soft.” In reality soft skills are all the human skills we have in teamwork, leadership, collaboration, communication, creativity, and person to person service. It’s easy to “teach” hard skills, but soft skills must be “learned.”

 

 

Also see:

Employers Want ‘Uniquely Human Skills’ — from campustechnology.com by Dian Schaffhauser

Excerpt:

According to 502 hiring managers and 150 HR decision-makers, the top skills they’re hunting for among new hires are:

  • The ability to listen (74 percent);
  • Attention to detail and attentiveness (70 percent);
  • Effective communication (69 percent);
  • Critical thinking (67 percent);
  • Strong interpersonal abilities (65 percent); and
  • Being able to keep learning (65 percent).
 

Online curricula helps teachers tackle AI in the classroom — from educationdive.com by Lauren Barack

Dive Brief:

  • Schools may already use some form of artificial intelligence (AI), but hardly any have curricula designed to teach K-12 students how it works and how to use it, wrote EdSurge. However, organizations such as the International Society for Technology in Education (ISTE) are developing their own sets of lessons that teachers can take to their classrooms.
  • Members of “AI for K-12” — an initiative co-sponsored by the Association for the Advancement of Artificial Intelligence and the Computer Science Teachers Association — wrote in a paper that an AI curriculum should address five basic ideas:
    • Computers use sensors to understand what goes on around them.
    • Computers can learn from data.
    • With this data, computers can create models for reasoning.
    • While computers are smart, it’s hard for them to understand people’s emotions, intentions and natural languages, making interactions less comfortable.
    • AI can be a beneficial tool, but it can also harm society.
  • These kinds of lessons are already at play among groups including the Boys and Girls Club of Western Pennsylvania, which has been using a program from online AI curriculum site ReadyAI. The education company lent its AI-in-a-Box kit, which normally sells for $3,000, to the group so it could teach these concepts.

 

AI curriculum is coming for K-12 at last. What will it include? — from edsurge.com by Danielle Dreilinger

Excerpt:

Artificial intelligence powers Amazon’s recommendations engine, Google Translate and Siri, for example. But few U.S. elementary and secondary schools teach the subject, maybe because there are so few curricula available for students. Members of the “AI for K-12” work group wrote in a recent Association for the Advancement of Artificial Intelligence white paper that “unlike the general subject of computing, when it comes to AI, there is little guidance for teaching at the K-12 level.”

But that’s starting to change. Among other advances, ISTE and AI4All are developing separate curricula with support from General Motors and Google, respectively, according to the white paper. Lead author Dave Touretzky of Carnegie Mellon has developed his own curriculum, Calypso. It’s part of the “AI-in-a-Box” kit, which is being used by more than a dozen community groups and school systems, including Carter’s class.

 

 

 

 

Training the workforce of the future: Education in America will need to adapt to prepare students for the next generation of jobs – including ‘data trash engineer’ and ‘head of machine personality design’– from dailymail.co.uk by Valerie Bauman

Excerpts:

  • Careers that used to safely dodge the high-tech bullet will soon require at least a basic grasp of things like web design, computer programming and robotics – presenting a new challenge for colleges and universities
  • A projected 85 percent of the jobs that today’s college students will have in 2030 haven’t been invented yet
  • The coming high-tech changes are expected to touch a wider variety of career paths than ever before
  • Many experts say American universities aren’t ready for the change because the high-tech skills most workers will need are currently focused just on people specializing in science, technology, engineering and math

.

 

 

Cut the curriculum — from willrichardson.com by Will Richardson

Excerpt:

Here’s an idea: A Minimal Viable Curriculum (MVC). That’s what Christian Talbot over at Basecamp is proposing, and I have to say, I love the idea.

He writes: “What if we were to design MVCs: Minimum Viable Curricula centered on just enough content to empower learners to examine questions or pursue challenges with rigor? Then, as learners go deeper into a question or challenge, they update their MVC…which is pretty much how learning happens in the real world.”

The key there to me is that THEY update their MVC. That resonates so deeply; it feels like that’s what I’m doing with my learning each day as I read about and work with school leaders who are thinking deeply about change.

 

When we pursue questions that matter to us, rigor is baked in.

 

From DSC:
I love the idea of giving students — as they can handle it — more choice, more control. So anytime around 8th-12th grade, I say we turn much more control over to the students, and let them make more choices on what they want to learn about. We should at least try some experiments along these lines.

 

 

As everyone in the workforce is now required to be a lifelong learner, our quality of life goes much higher if we actually enjoy learning. As I think about it, I have often heard an adult (especially middle age and older) say something like, “I hated school, but now, I love to learn.”

Plus, I can easily imagine greater engagement with the materials that students choose for themselves, as well as increased attention spans and higher motivation levels.

Also, here’s a major shout out to Will Richardson, Bruce Dixon, Missy Emler and Lyn Hilt for the work they are doing at ModernLearners.com.

 

Check out the work over at Modern Learners dot com

 

 

To higher ed: When the race track is going 180mph, you can’t walk or jog onto the track. [Christian]

From DSC:
When the race track is going 180mph, you can’t walk or jog onto the track.  What do I mean by that? 

Consider this quote from an article that Jeanne Meister wrote out at Forbes entitled, “The Future of Work: Three New HR Roles in the Age of Artificial Intelligence:”*

This emphasis on learning new skills in the age of AI is reinforced by the most recent report on the future of work from McKinsey which suggests that as many as 375 million workers around the world may need to switch occupational categories and learn new skills because approximately 60% of jobs will have least one-third of their work activities able to be automated.

Go scan the job openings and you will likely see many that have to do with technology, and increasingly, with emerging technologies such as artificial intelligence, deep learning, machine learning, virtual reality, augmented reality, mixed reality, big data, cloud-based services, robotics, automation, bots, algorithm development, blockchain, and more. 

 

From Robert Half’s 2019 Technology Salary Guide 

 

 

How many of us have those kinds of skills? Did we get that training in the community colleges, colleges, and universities that we went to? Highly unlikely — even if you graduated from one of those institutions only 5-10 years ago. And many of those institutions are often moving at the pace of a nice leisurely walk, with some moving at a jog, even fewer are sprinting. But all of them are now being asked to enter a race track that’s moving at 180mph. Higher ed — and society at large — are not used to moving at this pace. 

This is why I think that higher education and its regional accrediting organizations are going to either need to up their game hugely — and go through a paradigm shift in the required thinking/programming/curricula/level of responsiveness — or watch while alternatives to institutions of traditional higher education increasingly attract their learners away from them.

This is also, why I think we’ll see an online-based, next generation learning platform take place. It will be much more nimble — able to offer up-to-the minute, in-demand skills and competencies. 

 

 

The below graphic is from:
Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages

 

 

 


 

* Three New HR Roles To Create Compelling Employee Experiences
These new HR roles include:

  1. IBM: Vice President, Data, AI & Offering Strategy, HR
  2. Kraft Heinz Senior Vice President Global HR, Performance and IT
  3. SunTrust Senior Vice President Employee Wellbeing & Benefits

What do these three roles have in common? All have been created in the last three years and acknowledge the growing importance of a company’s commitment to create a compelling employee experience by using data, research, and predictive analytics to better serve the needs of employees. In each case, the employee assuming the new role also brought a new set of skills and capabilities into HR. And importantly, the new roles created in HR address a common vision: create a compelling employee experience that mirrors a company’s customer experience.

 


 

An excerpt from McKinsey Global Institute | Notes from the Frontier | Modeling the Impact of AI on the World Economy 

Workers.
A widening gap may also unfold at the level of individual workers. Demand for jobs could shift away from repetitive tasks toward those that are socially and cognitively driven and others that involve activities that are hard to automate and require more digital skills.12 Job profiles characterized by repetitive tasks and activities that require low digital skills may experience the largest decline as a share of total employment, from some 40 percent to near 30 percent by 2030. The largest gain in share may be in nonrepetitive activities and those that require high digital skills, rising from some 40 percent to more than 50 percent. These shifts in employment would have an impact on wages. We simulate that around 13 percent of the total wage bill could shift to categories requiring nonrepetitive and high digital skills, where incomes could rise, while workers in the repetitive and low digital skills categories may potentially experience stagnation or even a cut in their wages. The share of the total wage bill of the latter group could decline from 33 to 20 percent.13 Direct consequences of this widening gap in employment and wages would be an intensifying war for people, particularly those skilled in developing and utilizing AI tools, and structural excess supply for a still relatively high portion of people lacking the digital and cognitive skills necessary to work with machines.

 


 

 

Smart Machines & Human Expertise: Challenges for Higher Education — from er.educause.edu by Diana Oblinger

Excerpts:

What does this mean for higher education? One answer is that AI, robotics, and analytics become disciplines in themselves. They are emerging as majors, minors, areas of emphasis, certificate programs, and courses in many colleges and universities. But smart machines will catalyze even bigger changes in higher education. Consider the implications in three areas: data; the new division of labor; and ethics.

 

Colleges and universities are challenged to move beyond the use of technology to deliver education. Higher education leaders must consider how AI, big data, analytics, robotics, and wide-scale collaboration might change the substance of education.

 

Higher education leaders should ask questions such as the following:

  • What place does data have in our courses?
  • Do students have the appropriate mix of mathematics, statistics, and coding to understand how data is manipulated and how algorithms work?
  • Should students be required to become “data literate” (i.e., able to effectively use and critically evaluate data and its sources)?

Higher education leaders should ask questions such as the following:

  • How might problem-solving and discovery change with AI?
  • How do we optimize the division of labor and best allocate tasks between humans and machines?
  • What role do collaborative platforms and collective intelligence have in how we develop and deploy expertise?


Higher education leaders should ask questions such as the following:

  • Even though something is possible, does that mean it is morally responsible?
  • How do we achieve a balance between technological possibilities and policies that enable—or stifle—their use?
  • An algorithm may represent a “trade secret,” but it might also reinforce dangerous assumptions or result in unconscious bias. What kind of transparency should we strive for in the use of algorithms?

 

 

 

Experiences in self-determined learning — a free download/PDF file from uni-oldenburg.de by Lisa Blaschke, Chris Kenyon, & Stewart Hase (Eds.)

Excerpts (emphasis DSC):

An Introduction to Self-Determined Learning (Heutagogy)

Summary
There is a good deal that is provocative in the theory and principles surrounding self-determined learning or heutagogy. So, it seems appropriate to start off with a, hopefully, eyebrow-raising observation. One of the key ideas underpinning self-determined learning is that learning, and educational and training are quite different things. Humans are born to learn and are very good at it. Learning is a natural capability and it occurs across the human lifespan, from birth to last breath. In contrast, educational and training systems are concerned with the production of useful citizens, who can contribute to the collective economic good. Education and training is largely a conservative enterprise that is highly controlled, is product focused, where change is slow, and the status quo is revered. Learning, however, is a dynamic process intrinsic to the learner, uncontrolled except by the learner’s mental processes. Self-determined learning is concerned with understanding how people learn best and how the methods derived from this understanding can be applied to educational systems. This chapter provides a relatively brief introduction of the origins, the key principles, and the practice of self-determined learning. It also provides a number of resources to enable the interested reader to take learning about the approach further.

Contributors to this book come from around the world: they are everyday practitioners of self-determined learning who have embraced the approach. In doing so, they have chosen the path less taken and set off on a journey of exploration and discovery – a new frontier – as they implement heutagogy in their homes, schools, and workplaces. Each chapter was written with the intent of sharing the experiences of practical applications of heutagogy, while also encouraging those just starting out on the journey in using self-determined learning. The authors in this book are your guides as you move forward and share with you the lessons they have learned along the way. These shared experiences are meant to be read – or dabbled in – in any way that you want to read them. There is no fixed recipe or procedure for tackling the book contents.

At the heart of self-determined learning is that the learner is at the centre of the learning process. Learning is intrinsic to the learner, and the educator is but an agent, as are many of the resources so freely available these days. It is now so easy to access knowledge and skills (competencies), and in informal settings we do this all the time, and we do it well. Learning is complex and non-linear, despite what the curricula might try to dictate. In addition, every brain is different as a result of its experience (as brain research tells us). Each brain will also change as learning takes place with new hypotheses, new needs, and new questions forming, as new neuronal connections are created.

Heutagogy also doesn’t have anything directly to do with self-determination theory (SDT). SDT is a theory of motivation related to acting in healthy and effective ways (Ryan & Deci, 2000). However, heutagogy is related to the philosophical notion of self-determinism and shares a common belief in the role of human agency in behavior.

The idea of human agency is critical to self-determined learning, where learning is learner-directed. Human agency is the notion that humans have the capacity to make choices and decisions, and then act on them in the real world. However, how experiences and learning bring people to make the choices and decisions that they do make, and what actions they may then take is a very complex matter. What we are concerned with in self-determined learning is that people have agency with respect to how, what, and when they learn. It is something that is intrinsic to each individual person. Learning occurs in the learner’s brain, as the result of his or her past and present experiences.

 

The notion of placing the learner at the centre of the learning experience is a key principle of self-determined learning. This principle is the opposite of teacher-centric or, perhaps more accurately curriculum-centric, approaches to learning. This is not to say that the curriculum is not important, just that it needs to be geared to the learner – flexible, adaptable, and be a living document that is open to change.

Teacher-centric learning is an artifact of the industrial revolution when an education system was designed to meet the needs of the factories (Ackoff & Greenberg, 2008) and to “make the industrial wheel go around” (Hase & Kenyon, 2013b). It is time for a change to learner-centred learning and the time is right with easy access to knowledge and skills through the Internet, high-speed communication and ‘devices’. Education can now focus on more complex cognitive activities geared to the needs of the 21st century learner, rather than have its main focus on competence (Blaschke & Hase, 2014; Hase & Kenyon, 2013a).

 

 

 

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