Serendipity35

It is an evolution that I have been following and I have written about how AI and machine learning are pushing us closer to that new age. I jokingly said that I was accepting resumes for a digital assistant. And most recently, the amazing and also frightening Google Duplex demo made me wonder if we don't need a reverse Turing test for AI.

It has been suggested that in this era where technology and society are evolving faster than businesses and schools can naturally adapt, the mantra of “adapt or die” comes into play. You can react to change, be disrupted by it, or adapt. Brian Solis and others have referred to this as "Digital Darwinism."

As with the more established Darwinism, the digital version is pretty indiscriminate when it comes to which products or companies survive, thrive or fade.

I suppose we are still officially in the Information Age, but I think we may be evolving into an Age of Assistance. There is some evidence of this when you hear people say things like "Google, dim the bedroom lights" or "Alexa, play music by James Taylor."  

As in nature, we need experimentation and adpatations and even new species to survive. And some will have to go extinct. Goodbye Blockbuster, Circuit City, Borders Books, Tower Records, Pontiac, Saturn, and Palm. Hello Netflix, which then had to evolve (and is still doing so) to be a streaming rather than discs-in-the-mail service.

This pruning is clearly happening in business. Have any colleges fallen aside via Digital Darwinism? (A colleague answered that question by only half-sarcastically saying "Trump University.")

Artificial intelligence and machine learning are big drivers in Digital Darwinism. Is it true that Digital Darwinism has pushed open the door to an age of assitance a bit wider?  

That push comes from artifical intelligence combined with speech recognition.

Though smartphones and standalone devices with Siri, Alexa et al have put this assistance in front of consumers, digital speech recognition didn't start with those devices. The IBM Shoebox was shown to the general public during the 1962 Seattle World's Fair. It was launched in 1961 - almost 20 years before the introduction of the first IBM Personal Computer. It was able to recognize 16 spoken words and the digits 0 to 9. 

Most speech recognition systems require some "training" from users and with AI they learn to respond more accurately and efficiently. We have moved away from the earlier "speaker dependent" systems in some ways. They have to learn a particular user's speech patterns, accent, pronunciation etc. Newer systems tend to be independent and aggregate patterns from the many users that are connected to them more than focus on one user. It's not your Alexa. It's everyone's Alexa.

The rise of smart speakers in the past year via their sales (sales that have more than tripled) like Google Home and Amazon Echo have made some humans more reliant on voice commands.

Google has been talking and offering voice search for a few years and we ceratinly sometimes use voice to seach on our phones. But, if you're like me, you still find that technology lacking in most instances. But the voice search revolution is still predicted to happen and I don't doubt that it will occur, though perhaps more evolutionarily than revolutionariy.

The sophistication of voice-recognition systems is improving rapidly. Microsoft’s Cortana voice recognition software (which doesn't get as much attention it seems) now has an error rate of 5.1 percent, which gets it up there with human counterparts. With Microsoft large installed base of Windows-based personal computers, smartphones and smart speakers, they will certain be players in this area.

Google Assistant is a virtual assistant primarily available on mobile and smart home devices, and (unlike Google Now) it can engage in two-way conversations.

What I find on this topic online is primarily about marketing, but I believe it also applies to education.

Consumers are researching just about everything they buy and want relevant results. they want assistance. In an Age of Assistance, we are finding that assistance in what is being refferred to as mobile-first “micro-moments.”

This is way beyond classical marketing. Currently, I don't see many examples in eduction of schools getting into new opportunities for “assisted” engagement. Is your help desk using voivce recognition and AI? Is it in other student support services? can a student in a course that is online or in a classroom use voice to aska question of a digital assistent at 1 AM when they are stuck on a problem?

Those few schools that are adapting and experimenting with these technologies might be safer down the evolutionary road when Digital Darwinism starts to make programs or colleges digital Dodo birds.

 

Digital Darwinism: Survival of the Fittest in the Age of Business Disruption

Digital Darwinism: Branding and Business Models in Jeopardy

                 

 

FURTHER READING

thinkwithgoogle.com/intl/en-154/insights-inspiration/thought-leadership/marketing-age-assistance/

thinkwithgoogle.com/intl/en-gb/consumer-insights/search-in-the-age-of-assistance/

forbes.com/sites/briansolis/2017/10/11/wtf-whats-the-future-of-marketing-in-the-age-of-assistance/

business2community.com/tech-gadgets/the-age-of-assistance

I have been reading about some of the sessions at the International Conference on E-Learning in the Workplace (ICELW) that occurred this month at Columbia University. 

One keynoter was Dr. Barbara Oakley, Professor of Engineering at Oakland University in Rochester. She is known for her course "Learning How to Learn," which is sometimes described as being "the world’s most popular MOOC." It has had more than 2 million participants. There may be MOOCs with more participants, but her course has been translated into multiple languages and had some serious media attention. It is a broader kind of course and not really aimed at a college audience alone. It fits into a workplace focused conference and lifelong learning. It is described as a course that “gives you easy access to the invaluable learning techniques used by experts in art, music, literature, math, science, sports, and many other disciplines” to learn.

I haven't taken this course, but I plan to this summer. From what I have read, many of the concepts are ones I know from my own teaching and education courses. For example, “how the brain uses two very different learning modes and how it encapsulates (“chunks”) information.” That is something I learning a long time ago in teaching secondary school, and also used extensively in doing instructional design on other professors' courses as they moved online.

I was more interested in knowing what her "secrets" would be for building and teaching that MOOC. I haven't seen any video from the conference, but here are some bits I have found about her session.  

She uses the "Learning How to Learn" principles of learning that are being taught in the course in the design of the course. She is not adverse to PowerPoint slides but uses simple visuals to chunk key ideas.

Oakley emphasized the impact of integrating lessons from neuroscience. One of those is neuro reuse theory. The theory was a way to explain the underlying neural processes which allow humans to acquire recently invented cognitive capacities. It attempts to explain how the brain responds to new cognitive processes - think of many of our digital encounters - which are cultural inventions too modern to be the products of evolution. Simple application is her use of metaphors (a key element of neural reuse theory) because they allow students to a quick way to encounter new ideas. 

She emphasizes paying attention to production values in creating a course. She did her course production herself at home and says the cost was $5000. I assume that was for software, video hardware etc. Many schools now have production facilities for online course development. 

Bottom-up (as opposed to top-down) attentional mechanisms are a theory from neuroscience that she uses to keep attention on the screen.  Bottom-up mechanisms are thought to operate on raw sensory input, rapidly and
involuntarily shifting attention to salient visual features of potential importance. Think of the sudden movement that could be a predator. Top-down mechanisms implement our longer-term cognitive strategies, biasing attention toward something like a learned shape or color that signals a predator.

This is a more complex topic than can be covered in a blog post but it is easy to accept that the brain is limited in its capacity to process all sensory stimuli in our sensory-overload physical world. The brain relies on the cognitive process of attention to focus neural resources according to the contingencies of the moment. You can attention into two functions. Bottom-up attention is attention guided by externally driven factors to stimuli. That could be the bright colored popup ad on a screen. Instructional designers can make use of techniques that marketers and game designers have long used. Top-down attention refers to internal guidance of attention based on factors such as prior knowledge and current goals. The overall organizational structure of a course - weekly elements, labels, icons - can take advantage of top-down attention.

She recommended the use of "unexpected humor" to help maintain interest, which can also be a bottom-up technique.

Wherever practicable, theory is instantiated with examples drawn from personal stories.

Overall, this is all about trying harder to engage learners. Oakley pointed out that in a MOOC learners aren’t "caged up like students on campus." MOOC learners are free-range learners - free to come and go, free to stop paying attention or attending class - and if course production values are weak, students are more likely to tune out.

In designing and teaching an online course in the traditional college/tuition/credit/degree situation, we do have students caged more, but that doesn't mean their brains operate differently.

One of Oakley's earlier books is A Mind for Numbers with the subtitle How to Excel at Math and Science (Even If You Flunked Algebra) and her new book this summer is Learning How to Learn whose subtitle is How to Succeed in School Without Spending All Your Time Studying; A Guide for Kids and Teens. Those subtitles remind me that these book and the topics they address are lifelong learning concerns, though certainly of interest to K-20 teachers.

I am planning to take her course this summer before I embark on a new course design project. See coursera.org/learn/learning-how-to-learn I'll follow up on this post when I finish. If I finish. If I don't finish, I guess I'll make some analysis of why - was it me or the course?

A recent opinion piece headlined "Moocs are a solution in search of a problem" by Chris Fellingham, who is strategy and research manager at FutureLearn, got a response from true MOOC pioneer Stephen Downes. 

Downes writes:

According to Chris Fellingham, MOOCs " arose from the boredom of Stanford University computer science professors fed up with teaching the same lectures each year. Out of idle curiosity, they wanted to see what would happen if they dumped their courses, lectures and all, online for anyone to take." According to this story, MOOCs then searched for a problem to solve - providing new skills to university graduates, say, or offering new kinds of certificates. None of that is my experience, nor is it even true outside the narrow bounds of Coursera and Udacity. MOOCs were created in order top provide access to learning using open educational resources, modeling the connectivist philosophy George Siemens and I had been working on for a number of years. The problem of access is real. It exists because the people writing in places like Times Higher Education do not consider access to be a problem at all.

Fellingham's main premise is that since "A common question to start-up founders is: 'What problem does this solve?'” Then, MOOCs are a solution in want of a problem.

As Downes counters, the MOOC did not emerge initially "from the boredom of Stanford University computer science professors fed up with teaching the same lectures each year." Those Stanford courses came later, but did get a lot more attention in the media than the earlier MOOCs.

One problem that MOOCs can still help solve is access to learning. The "democratizing of knowledge" may sound lofty, but it is real. The Internet itself allowed for this in an informal learning way, but a MOOC is a much more formal approach - and an important one.

That first "O" in a Massive Open Online Course has taken a beating in the years since those first MOOCs. I would say that the majority of courses labeled as MOOCs today (such as those in Coursera and other large providers) are still massive online courses, but they are not open.

As Coursera, edX, Udacity and Fellingham's own FutureLearn make more connections and deals with universities in order to have a business model, their course become less open in the true OER sense.

Luckily, many of these courses are still free when taken without credit concerns. But free in cost is just one aspect of OPEN Educational resources.

I don't have issues with providers wanting to make a profit with their courses. But I am concerned with 1) those courses being called MOOCs when they are MOCs, and 2) that I am seeing fewer truly open courses being offered by large universities and the biggest providers.

Alternative certifications and degrees, such as MicroMasters and nanodegrees, have a place in higher ed and they owe much to the MOOC rEvolution.  

New online education companies keep appearing. No connections to a university, but possibly connections with employers also have a place in providing specific training in what employers want - which educators have sadly discovered is often not what they teach.

Many of the problems in education and in online education from a decade ago still exist. The solutions are still evolving.

Professional learning, often referred to as training, has been in companies for a long time.  But as a history of  training would show, that training is different from education and their evolutions have differed and crossed paths at times.

Education is instruction in more general knowledge, such as the history of the society, or mathematics. Training teaches how to do a specific task, such as building or running a machine.  As societies developed, there accumulated more knowledge than people could pick up on their own or learn informally from others.

That training history would reach back to antiquity when "On-The-Job Training" was the way people learned a job or career. In the Middle Ages, the apprenticeship was the new trend - learning from an expert while on the job. The Industrial Revolution brought about actual classrooms and factory schools with more formal training inside the company. 

I thought about this history when I was reading about the work of the Director of Learning at Slack, Kristen Swanson. Her job is to develop training for the tech company's employees and to help explain their messaging tool to customers around the globe. Swanson came to the company after an earlier career in EdTech. She started in education as an elementary school teacher, then served as a district director of technology, moved to directing a research department at BrightBytes, and then founded the Edcamp Foundation. That last role helped teachers run free, grassroots professional-development workshops. 

Directing learning at a company like Slack, must be very different, right? 

Amazon operates its own education division, Amazon Education. It currently offers products and services aimed at K-12 classrooms, such as TenMarks, an online math and writing program, and Inspire, a directory of online educational materials where teachers can find and share teaching materials. And Candace Thille, a professor of education at Stanford University, is now Amazon's Director of Learning Science and Engineering. 

A newish trend is for large technology companies to hire former educators to lead training and education efforts. Is professional learning outside academia becoming more like learning inside academia?

Returning to that training history, we saw that "vestibule training" emerged at the start of the 20th century blending the classroom with on-the-job training or "near-the-job" training. The training room was located close to the workplace and equipped with the same machines, equipment and technology that are used in production. The trainer was usually a skilled worker or supervisor, much like the much older apprentice model.

During and after the two world wars, there was a need to train large numbers of defense workers because of increased demand for products and a loss of workers to the military. Several shifts occurred during this period. Training was done by supervisors who were being trained how to teach. Training classes were smaller, generally 9-11 workers.

As training departments became established in many companies, so did ways of providing more efficient, less expensive methods of training. Individualized automated instruction came into play, and was the basis for CBT (computer-based training) which is still used in various forms in companies today.

Has training been learning from education, or has education been trying to include training in the curriculum?