Streaming Learning

video playerThis past summer for the first time ever, streaming services captured more viewers than cable or broadcast TV, according to new data from Nielsen. Streaming has outperformed broadcast before, but never broadcast and cable in the same month. It's a close race though.
In the U.S., streaming captured 34.8% of viewership in July, while cable accounted for 34.4% and broadcast came in third at 21.6%.

When I read an article such as "Reasons Why Video Streaming Is The Future Of Education In 2022," the reasons are really the reasons why we should be offering online learning. Streaming is just a newer delivery method.

The history of distance learning goes from correspondence (snail mail) to broadcast and ITV, to videotapes, CDs and DVDs, the Internet (the earlier and slower version), and now streaming. When video first appeared in classrooms as broadcast, ITV and even on tapes it was sometimes considered controversial. Did it have educational value? Was it a lazy way to teach? Didn't students get enough video at home? But that is no longer true in almost every instance. Video is effective for learning. Online video has been shown to enhance comprehension and retention of information, support multi-modal learning, can help develop digital literacies when it is taught rather than just consumed. It can also be a more cost-effective learning solution, and can be repurposed in multiple ways.

Frequently, video is a supplement to make additional material available to students online. Some movements, like the flipped classroom, used online videos to swap lectures and classroom time. And this is true beyond traditional classrooms and schools as video became a training model for employees and customers.

When you use a streaming service (Netflix, Apple+ et al) you are almost always watching recorded videos. But the newer use of streaming is live streaming. Teachers are live streaming lectures and lessons to fully online students and also to students when you can’t meet in person. The real-time nature of live video allows a virtual classroom to be interactive in ways similar to in-person lessons.

Educational live streaming goes beyond lectures. There are also discussion panels, debates, guest speakers, presentations, virtual field trips, laboratory exercises, tutorials on demand and workshops.

Live streaming almost alw and "interact" sometimes ays ends up being recorded video later. Many presentations I register for that are live are later offered as a recording. That's great but it does make me feel less of an obligation sometimes to watch it live. Yes, I can sometimes ask questions in the live sessions, but I've gotten so used to recording TV programs and watching them later that it has carried over to "educational" applications.

Tech-Enhanced Learning and Mobile Natives

I consult with Eastern International College on topics around online learning. They use the LMS Canvas from Instructure for online courses and only started using it more widely about 3 years ago. It's a for-profit college that offers degrees and certifications in health and medical fields. That is a population of faculty and students who have always been reluctant to go online. These are very hands-on, in-a-lab classes primarily. But the move proved to be somewhat lifesaving when the Covid pandemic hit schools in the 2020 semester.

Instructure sent me some resources to think about for the fall semester and one was strategies for "Tech-Enhanced Learning." I will date myself by saying I recall when we were attaching the term "web-enhanced" to courses and strategies. I also remember very clearly when the term "digital natives" was used to describe the students we were meeting in our classrooms.

Thomas Husson had blogged some time ago about mobile natives from a marketing perspective. He notes that the first iPhone was released in 2007 and, on average, a kid gets their first cell phone around 11 years old. That means the first entire generation that mobile has impacted will enter the workforce about 2025 - but they are already in schools grades kindergarten through higher education. 

kids on phones in class
     Photo: Rodnae Productions

Technology-enhanced (or sometimes "infused")  learning is essential to best learning practices and also to keeping learning relevant. It surely will play a role - as it has already and not always in a positive way - in the survival of higher education institutions. Instructional technology is important to student engagement. The correct approach is not to digitize what is already being used. That's closer to what we called "web-enhanced" when we were starting to put materials online. 

How do you use technology to transform pedagogy to be more engaging, innovative, and inclusive?  here are their suggested strategies.

Though the pandemic forced coursework online out of necessity, digital learning should now be the default. All courses should be designed so that they could be taught online, even if the intent is to teach them in a classroom. When course content is and communication is available online students can access it anywhere and at any time.

As noted above, courses should also be optimized courses for mobile access since mobile phones are the primary tool used by many students and student income levels are no longer the deciding factor for that use. How many of your students have a desktop computer or even a laptop?

Engagement includes interactive experiences between faculty and students, and also connecting students with one another. This is also something that goes across face-to-face, hybrid and fully remote courses.

It is important that this shift goes beyond your classes. A "digital campus" means things beyond coursework. Virtual tutoring, office hours, counseling, tech support, and library access is especially critical for off-campus students to have that on-campus connection. And even residential students will often prefer digital over face-to-face. Mental health resources for psychological well-being are a leading factor for student success and schools can leverage technology to expand access to mental health resources including virtual counseling, staff mental health training, and student mental health apps.

HyFlex learning environments got a lot more attention during the pandemic. This approach is student-centered and offers equitable access to content. Students should be able to move between modalities based on their learning needs and the location - pandemic or not.

For a long time, educators have been told what to expect from Millennials. We have moved on to Generation Z which is usually defined as those 4 to 24 years old - which covers pre-school to graduate school. They are a group that has always had access to the Internet - as did many Millennials - but Gen Z also has mobile devices as their primary way of communicating and getting information in and out of classes.

I added this post to my category "Education 2.0" which for me meant where education was moving. I have seen articles about "Education 3.0" but I stick with version 2 because I haven't seen the really big seismic shift in education yet.

Some futurists say that by the end of this decade workers who still go to a workplace outside their home will walk in, plug their device into the network ( Is say "plug" but it will probably be wireless), connect to a bigger screen(s) and start working. Shifting to mobile is not in its early stage. There are 7 billion mobile subscriptions now. That's not everyone and not every student, but a report from Forrester Research said that mobile phone penetration is at 91 percent of Generation Y homes. (80 percent for all households across North America.) 79 present 13-20-year-olds say in surveys that they can't live without their smartphones compared to 70 percent of 21-39-year-olds.

 

SOURCES
instructure.com/higher-education/back-to-school/faculty

blogs.forrester.com/thomas_husson/14-12-02-mobile_and_mobile_natives...

linkedin.com/pulse/mobile-natives-eric-isham/

ypulse.com/article/2022/03/29/3-stats-on-how-gen-z-is-being-raised-on-smartphones/

marketingdive.com/ex/mobilemarketer/cms/news/research/1576.html

 

Machine Learning MOOC Updated

Python book
Photo by Christina Morillo

Andrew Ng's Machine Learning course on Coursera has been revamped and updated and it is getting good student ratings.

There are fewer online courses that I consider to be true MOOCs now. Massive is small. Open is more closed. But the "OC" portion remains for many. The three courses that make up the Machine Learning Specialization offered by DeepLearning.AI and Stanford on the Coursera platform still fit the MOOC definition more closely.

You can earn a certificate at the end, and enjoy the full experiences including quizzes and assignments if you enroll and pay a monthly subscription but the courses are free (Open) to audit and view the course materials. The Massive in this course is massive with over 20,000 students enrolled.

Andrew Ng is the co-founder of Coursera and was the founding lead of Google’s Brain Project, and served as Chief Scientist at Baidu. He then did two artificial intelligence startups - Deeplearning.ai (a training company founded in 2017) and Landing.ai (for transforming enterprises with AI). He remains an adjunct professor at Stanford University. His course on Machine Learning was one of the very first courses from Coursera when it first launched in 2012. I audited the course that year though I knew the content was way above my abilitiees but I was curious as to the structure of the course from a design perspective.

At that time, Machine Learning was a new concept and was close to applied statistics. Ng goes way back because his Stanford lectures were on YouTube in 2008 and got 200,000 views. Then, he converted them to an online format in Fall 2011 and they were offered for free. He had 104,000 students and 13,000 of them gained certificates.

On the tech side, this updated version:
uses Python rather than Octave
expanded list of topics including modern deep learning algorithms, decision trees, and tools such as TensorFlow
new ungraded code notebooks with sample code and interactive graphs to help you visualize what an algorithm is doing
programming exercises
practical advice section on applying machine learning based on best practices from the last decade