open courseware and systems

AI, Instructional Design, and OER [Wiley]

On 01/25/2023, in Artificial Intelligence/Agents/LLMs/and Related, assessment, instructional design, learning ecosystem, open courseware and systems, pedagogy, teaching & learning, by Daniel Christian

AI, Instructional Design, and OER — from opencontent.org by David Wiley

Excerpt:

LLMs Will Make Creating the Content Infrastructure Significantly Easier, Faster, and Cheaper
LLMs will dramatically increase the speed of creating the informational resources that comprise the content infrastructure. Of course the drafts of these informational resources will need to be reviewed and improvements will need to be made – just as is the case with all first drafts – to insure accuracy and timeliness. But it appears that LLMs can get us 80% or so of the way to reasonable first drafts orders of magnitude faster, eliminating the majority of the expense involved in this part of the process. Here’s an example of what I’m talking about. Imagine you’re a SME who has been tasked with writing the content for an introductory economics textbook. (The following examples are from ChatGPT.)

Speaking of ID and higher education, also relevant/see:

5 Myths About Instructional Design in Higher Education — from drlukehobson.com by Luke Hobson
Fulfillment in Higher Education / Other Roles Besides Instructional Designer / Confused Subject Matter Experts — from drlukehobson.com by Luke Hobson

Some example components of a learning ecosystem [Christian]

On 01/20/2023, in 21st century, A/V -- audio/visual, active learning, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, Augmented Reality (AR), blended learning, blogs / blogging / vlogging, bots, Canvas - and other Instructure-related items, cloud-based computing / apps / other cloud-related, CMS/LMS, collaboration, colleges, communities of practice, community colleges, competency-based learning/education, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, Daniel S. Christian, digital audio, digital learning, digital textbooks, digital video, e-books, e-publishing related items (EPUB and more), education technology, educational games / serious games, elearning, face-to-face, faculty/staff, heutagogy, higher education, human-computer interaction (HCI), hybrid learning, Hyflex learning, informal learning, instructional design, intelligent systems, intelligent tutoring, K-12 related, law schools, learner profiles, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, learning theories, library / librarians, lifelong learning, microlearning, mobile learning, MOOCs -- Massive Open Online Courses, online learning, online media, online tutoring, open courseware and systems, parents/guardians, pedagogy, personalized/customized learning, platforms, play, podcasting, professional development, social learning / networks, social media, society, streams of content, student-related, teachers, teaching & learning, technology (general), tools, training / L&D, universities, videoconferencing, Virtual Reality (VR) / worlds / learning, vocational / trades, webinars, by Daniel Christian

A learning ecosystem is composed of people, tools, technologies, content, processes, culture, strategies, and any other resource that helps one learn. Learning ecosystems can be at an individual level as well as at an organizational level.

Some example components:

Subject Matter Experts (SMEs) such as faculty, staff, teachers, trainers, parents, coaches, directors, and others
Fellow employees
L&D/Training professionals
Managers
Instructional Designers
Librarians
Consultants
Types of learning
- Active learning
- Adult learning
- PreK-12 education
- Training/corporate learning
- Vocational learning
- Experiential learning
- Competency-based learning
- Self-directed learning (i.e., heutagogy)
- Mobile learning
- Online learning
- Face-to-face-based learning
- Hybrid/blended learning
- Hyflex-based learning
- Game-based learning
- XR-based learning (AR, MR, and VR)
- Informal learning
- Formal learning
- Lifelong learning
- Microlearning
- Personalized/customized learning
- Play-based learning
Cloud-based learning apps
Coaching & mentoring
Peer feedback
Job aids/performance tools and other on-demand content
Websites
Conferences
Professional development
Professional organizations
Social networking
Social media – Twitter, LinkedIn, Facebook/Meta, other
Communities of practice
Artificial Intelligence (AI) — including ChatGPT, learning agents, learner profiles,
LMS/CMS/Learning Experience Platforms
Tutorials
Videos — including on YouTube, Vimeo, other
Job-aids
E-learning-based resources
Books, digital textbooks, journals, and manuals
Enterprise social networks/tools
RSS feeds and blogging
Podcasts/vodcasts
Videoconferencing/audio-conferencing/virtual meetings
Capturing and sharing content
Tagging/rating/curating content
Decision support tools
Getting feedback
Webinars
In-person workshops
Discussion boards/forums
Chat/IM
VOIP
Online-based resources (periodicals, journals, magazines, newspapers, and others)
Learning spaces
Learning hubs
Learning preferences
Learning theories
Microschools
MOOCs
Open courseware
Portals
Wikis
Wikipedia
Slideshare
TED talks
…and many more components.

These people, tools, technologies, etc. are constantly morphing — as well as coming and going in and out of our lives.

ChatGPT, Chatbots and Artificial Intelligence in Education — from ditchthattextbook.com by Matt Miller
AI just stormed into the classroom with the emergence of ChatGPT. How do we teach now that it exists? How can we use it? Here are some ideas.

Excerpt:
Now, we’re wondering …

What is ChatGPT? And, more broadly, what are chatbots and AI?
How is this going to impact education?
How can I teach tomorrow knowing that this exists?
Can I use this as a tool for teaching and learning?
Should we block it through the school internet filter — or try to ban it?

Also relevant/see:

We gave ChatGPT a college-level microbiology quiz. It blew the quiz away. — from bigthink.com by Dr. Alex Berezow
ChatGPT’s capabilities are astonishing.

Key takeaways:

The tech world is abuzz over ChatGPT, a chat bot that is said to be the most advanced ever made.
It can create poems, songs, and even computer code. It convincingly constructed a passage of text on how to remove a peanut butter sandwich from a VCR, in the voice of the King James Bible.
As a PhD microbiologist, I devised a 10-question quiz that would be appropriate as a final exam for college-level microbiology students. ChatGPT blew it away.

ChatGPT Is Dumber Than You Think — from theatlantic.com by Ian Bogost
Treat it like a toy, not a tool.

Excerpt:

On the one hand, yes, ChatGPT is capable of producing prose that looks convincing. But on the other hand, what it means to be convincing depends on context. The kind of prose you might find engaging and even startling in the context of a generative encounter with an AI suddenly seems just terrible in the context of a professional essay published in a magazine such as The Atlantic. And, as Warner’s comments clarify, the writing you might find persuasive as a teacher (or marketing manager or lawyer or journalist or whatever else) might have been so by virtue of position rather than meaning: The essay was extant and competent; the report was in your inbox on time; the newspaper article communicated apparent facts that you were able to accept or reject.

I Would Have Cheated in College Using ChatGPT — from eliterate.us by Michael Feldstein

Excerpt:

These lines of demarcation—the lines between when a tool can do all of a job, some of it, or none of it—are both constantly moving and critical to watch. Because they define knowledge work and point to the future of work. We need to be teaching people how to do the kinds of knowledge work that computers can’t do well and are not likely to be able to do well in the near future. Much has been written about the economic implications to the AI revolution, some of which are problematic for the employment market. But we can put too much emphasis on that part. Learning about artificial intelligence can be a means for exploring, appreciating, and refining natural intelligence. These tools are fun. I learn from using them. Those two statements are connected.

Google to Rival OpenAI’s ChatGPT? New AI Bot for Chats in 2023, CEO Claims to Use it for Search — from techtimes.com by Isaiah Richard
Google to expand its Search engine with AI for 2023, but not in a creepy way.

Excerpt:

Google is planning to create a new AI feature for its Search engine, one that would rival the recently released and controversial ChatGPT from OpenAI. The company revealed this after a recent Google executive meeting that involved the likes of its CEO Sundar Pichai and AI head, Jeff Dean, that talked about the technology that the internet company already has, soon for development.

Employees from the Mountain View giant were concerned that it was behind the current AI trends to the likes of OpenAI despite already having a similar technology laying around.

And more focused on the business/vocational/corporate training worlds:

Sana raises $34M for its AI-based knowledge management and learning platform for workplaces — from techcrunch.com by Ingrid Lunden

There are a lot of knowledge management, enterprise learning and enterprise search products on the market today, but what Sana believes it has struck on uniquely is a platform that combines all three to work together: a knowledge management-meets-enterprise-search-meets-e-learning platform.

Exclusive: ChatGPT owner OpenAI projects $1 billion in revenue by 2024 — from reuters.com by Jeffrey Dastin, Krystal Hu, and Paresh Dave

Excerpt:

Three sources briefed on OpenAI’s recent pitch to investors said the organization expects $200 million in revenue next year and $1 billion by 2024.

The forecast, first reported by Reuters, represents how some in Silicon Valley are betting the underlying technology will go far beyond splashy and sometimes flawed public demos.

“We’re going to see advances in 2023 that people two years ago would have expected in 2033. It’s going to be extremely important not just for Microsoft’s future, but for everyone’s future,” he said in an interview this week.

Addendum on 12/21/22:

ChatGPT and higher education: last week and this week — from bryanalexander.org by Bryan Alexander

AI bot ChatGPT stuns academics with essay-writing skills and usability [Hern]

On 12/14/2022, in adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, computer science, content development, aggregation, repositories, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, instructional design, IT in HE, law schools, learning ecosystem, Learning Experience Design, Microsoft, online media, open courseware and systems, platforms, productivity / tips and tricks, programming, the downsides of how people use tech, tools, UK, United States, universities, vendors, writing, by Daniel Christian

AI bot ChatGPT stuns academics with essay-writing skills and usability — from theguardian.com by Alex Hern
Latest chatbot from Elon Musk-founded OpenAI can identify incorrect premises and refuse to answer inappropriate requests

Excerpt:

Professors, programmers and journalists could all be out of a job in just a few years, after the latest chatbot from the Elon Musk-founded OpenAI foundation stunned onlookers with its writing ability, proficiency at complex tasks, and ease of use.

The system, called ChatGPT, is the latest evolution of the GPT family of text-generating AIs. Two years ago, the team’s previous AI, GPT3, was able to generate an opinion piece for the Guardian, and ChatGPT has significant further capabilities.

In the days since it was released, academics have generated responses to exam queries that they say would result in full marks if submitted by an undergraduate, and programmers have used the tool to solve coding challenges in obscure programming languages in a matter of seconds – before writing limericks explaining the functionality.

Also related/see:

AI and the future of undergraduate writing — from chronicle.com by Beth McMurtrie

Excerpts:

Is the college essay dead? Are hordes of students going to use artificial intelligence to cheat on their writing assignments? Has machine learning reached the point where auto-generated text looks like what a typical first-year student might produce?

And what does it mean for professors if the answer to those questions is “yes”?
…
Scholars of teaching, writing, and digital literacy say there’s no doubt that tools like ChatGPT will, in some shape or form, become part of everyday writing, the way calculators and computers have become integral to math and science. It is critical, they say, to begin conversations with students and colleagues about how to shape and harness these AI tools as an aide, rather than a substitute, for learning.

“Academia really has to look at itself in the mirror and decide what it’s going to be,” said Josh Eyler, director of the Center for Excellence in Teaching and Learning at the University of Mississippi, who has criticized the “moral panic” he has seen in response to ChatGPT. “Is it going to be more concerned with compliance and policing behaviors and trying to get out in front of cheating, without any evidence to support whether or not that’s actually going to happen? Or does it want to think about trust in students as its first reaction and building that trust into its response and its pedagogy?”

ChatGPT is incredibly limited, but good enough at some things to create a misleading impression of greatness.

it’s a mistake to be relying on it for anything important right now. it’s a preview of progress; we have lots of work to do on robustness and truthfulness.

— Sam Altman (@sama) December 11, 2022

fun creative inspiration; great! reliance for factual queries; not such a good idea.

we will work hard to improve!

— Sam Altman (@sama) December 11, 2022

1/Large language models like Galactica and ChatGPT can spout nonsense in a confident, authoritative tone. This overconfidence – which reflects the data they’re trained on – makes them more likely to mislead.

— Andrew Ng (@AndrewYNg) December 13, 2022

ChatGPT Could Be AI’s iPhone Moment — from bloomberg.com by Vlad Savov; with thanks to Dany DeGrave for his Tweet on this

Excerpt:

The thing is, a good toy has a huge advantage: People love to play with it, and the more they do, the quicker its designers can make it into something more. People are documenting their experiences with ChatGPT on Twitter, looking like giddy kids experimenting with something they’re not even sure they should be allowed to have. There’s humor, discovery and a game of figuring out the limitations of the system.

And on the legal side of things:

In the legal education context, I’ve been playing around with generating fact patterns and short documents to use in exercises.

— Rebecca Fordon (@theFordon) December 9, 2022

OpenAI Says DALL-E Is Generating Over 2 Million Images a Day—and That’s Just Table Stakes [Dorrier]

On 10/04/2022, in 21st century, 24x7x365 access, A/V -- audio/visual, Artificial Intelligence/Agents/LLMs/and Related, design, digital video, disruption, emerging technologies, Facebook / Meta Platforms, graphics, media/film, open courseware and systems, vendors, by Daniel Christian

OpenAI Says DALL-E Is Generating Over 2 Million Images a Day—and That’s Just Table Stakes — from singularityhub.com by Jason Dorrier

Excerpt:

The venerable stock image site, Getty, boasts a catalog of 80 million images. Shutterstock, a rival of Getty, offers 415 million images. It took a few decades to build up these prodigious libraries.

Now, it seems we’ll have to redefine prodigious. In a blog post last week, OpenAI said its machine learning algorithm, DALL-E 2, is generating over two million images a day. At that pace, its output would equal Getty and Shutterstock combined in eight months. The algorithm is producing almost as many images daily as the entire collection of free image site Unsplash.

And that was before OpenAI opened DALL-E 2 to everyone.

Here’s a look at what DALL·E 2 can do. ???

Want to see more? Follow along on Instagram: https://t.co/eKejIFxWdn

— OpenAI (@OpenAI) April 6, 2022

From DSC:
Further on down that Tweet is this example image — wow!
.

.

On the video side of things, also relevant/see:

Meta’s new text-to-video AI generator is like DALL-E for video — from theverge.com by James Vincent
Just type a description and the AI generates matching footage

A sample video generated by Meta’s new AI text-to-video model, Make-A-Video. The text prompt used to create the video was “a teddy bear painting a portrait.” Image: Meta

From DSC:
Hmmm…I wonder…how might these emerging technologies impact copyrights, intellectual property, and/or other types of legal matters and areas?

Learning 3.0: A data-fueled, equitable future for corporate learning [Ramos & Zao-Sanders]

On 08/31/2022, in Artificial Intelligence/Agents/LLMs/and Related, Bias | Diversity Equity & Inclusion (DE&I), CMS/LMS, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, internet, learning ecosystem, open courseware and systems, pedagogy, tools, training / L&D, Web3, workplace, by Daniel Christian

Learning 3.0: A data-fueled, equitable future for corporate learning — from chieflearningofficer.com by Marc Ramos and Marc Zao-Sanders
Learning pedagogy, technology and practice inevitably draw on (but tend to lag behind) the developments of the web, the world’s main stage for advancement and innovation.

Excerpts:

Tomorrow could be extraordinary. Many of the crowning jewels of Web 3.0 and web3 have been designed to be open source, user-friendly and ship with APIs, such as OpenAI’s GPT3, which generates natural language to an expert human level, seemingly at will. This means that the time between the launch of cutting-edge technology and it reaching corporate learning will decrease substantially. Learning might finally advance from the back seat to a board seat. There is already a growing list of GPT3 content creation tools that will impact creators, publishers, academic and corporate education materials as well as the design process.

We’re less than five years from this. The technology is here already. What’s missing is the data.

Fluid students flowing in and out of education are higher ed’s future. Here’s how colleges must adapt. — from highereddive.com by Anne Khademian
The Universities at Shady Grove’s executive director adapts the fluid fan idea reshaping the business of sports, shedding light on higher ed’s future.

We need less tweaking and more rethinking of how to deliver greater access, affordability and equity in higher education, and we must do it at scale. We need a new paradigm for the majority of students in higher education today that commits to meaningful employment and sustainable-wage careers upon completion of a degree or credential.

The challenge is the same for the business of higher education in serving future, more fluid students — and today’s nontraditional students. Many need to flow in and out of jobs and education, rather than pursue a degree in two or four years. Increasingly, they will seek to direct their educational experience toward personalized career opportunities, while stacking and banking credentials and experience into degrees.

From DSC:
Coming in and going out of “higher education” throughout one’s career and beyond…constant changes…morphing…hmm…sounds like a lifelong learning ecosystem to me.

#learningecosystems #learningfromthelivingclassroom
#highereducation #change #lifelonglearning

75% of master’s programs with high debt and low earnings are at private nonprofits — from highereddive.com by Lilah Burke
Urban Institute report undermines narrative that programs with poor student outcomes are all at for-profit colleges and in the humanities.

Although private nonprofit institutions accounted for 44% of all master’s programs in the data, they made up 75% of programs with high debt and low earnings.

Tuition increases, lower capital spending likely in store for higher ed as inflation persists, Fitch says — from highereddive.com by Rick Seltzer

The next inflation-driven worry: Rising college tuition — from washingtonpost.com by Nick Anderson and Danielle Douglas-Gabriel
Families are concerned about affordability of higher education

Spiraling rents are wreaking havoc on college students seeking housing for the fall — from by Jon Marcus
Big hikes are forcing students deeper into debt, risk pushing more out of school altogether

From DSC:
From someone who is paying for rent for a college student — along with tuition, books, fees, etc. — this has direct application to our household. If there isn’t a perfect storm developing in higher ed, then I don’t know what that phrase means.

#costofhighereducation #inflation

HBCUs see a historic jump in enrollments — from npr.org with Michel Martin; with thanks to Marcela Rodrigues-Sherley and Julia Piper from The Chronicle for the resource

Also from that same newsletter:

What would Harvard University’s ranking be if the only criteria considered was economic mobility? According to The Washington Post, it would be 847th out of 1,320. First place would go to California State University at Los Angeles.

A New Vision for the Future of Higher Education: Prioritizing Engagement and Alignment — from moderncampus.com with Amrit Ahluwalia and Brian Kibby

Excerpt:

Change is a constant in higher ed, just as it is in the labor market. Staying up to date and flexible is more important than ever for colleges and universities, and through the pandemic, many relied on their continuing and workforce education divisions to support their agility. In fact, 56% of higher ed leaders said the role of their CE units expanded through the pandemic.

The pandemic led to some of the biggest innovations in continuing ed in recent memory.

Students Lobby Lawmakers to Improve College Experience for Neurodiverse Learners — from edsurge.com by Daniel Lempres

Excerpt:

Lobbying for more support for students with learning disabilities in higher education, the students called for increased funding for the National Center for Special Education Research and the Individuals with Disabilities Education Act (IDEA Act) — legislation which requires that children with disabilities be given a free and appropriate public education, and makes it possible for states and local educational agencies to provide federal funds to make sure that happens. They also encouraged lawmakers to pass the RISE Act, a bill designed to better support neurodiverse students in higher education.

What a Homework Help Site’s Move to Host Open Educational Resources Could Mean — from edsurge.com by Daniel Mollenkamp

How can leaders bridge the gap between higher ed and employers? — from highereddive.com by Lilah Burke

Dive Brief:

Partnerships between higher education institutions and employers can be difficult to create, often because of misalignment between the cultures, structures and values of the two groups, according to a July report from California Competes, a nonprofit policy organization focused on higher education.
Higher ed leaders could improve employer relations by making industry engagement an expected responsibility of both faculty and staff, said the report, which drew from 28 interviews with people at colleges and employers.
Robust employer engagement can strengthen enrollment and job outcomes for students, the authors argued, while also benefiting state and local economies.

Price-fixing lawsuit against 568 Group of top-ranked universities can continue, judge rules — from highereddive.com by Rick Seltzer

Termination of the Accrediting Council for Independent Colleges and Schools as an ED Recognized Accrediting Agency — from blog.ed.gov

A Best-Selling Textbook Is Now Free — from insidehighered.com by Liam Knox
A popular chemistry book’s jump from a publishing titan to an OER pioneer could be pivotal for the open access movement. For the author, it’s also a fitting tribute to his late son.

Excerpt:

John McMurry’s textbook Organic Chemistry has helped millions of students across the globe pass the infamous gauntlet of its namesake class — also known among stressed-out pre-med students as “orgo” — since the book was first printed in 1984.

For his bestseller’s 10th edition, McMurry has decided to part ways with his longtime publisher, the industry giant Cengage, which has published the book since the beginning. He recently sold the rights to OpenStax, a nonprofit based at Rice University that is dedicated to developing open education resources (OER), learning and research materials created and licensed to be free for the user.

From DSC:
From someone paying for a young adult to get through college, I hope this kind of thing happens more often! 🙂 But seriously, there are too many instances when students have been treated as cash cows, when we should have been bending over backward to help them get their educations.

For example, if I pay an invoice from our son’s university by credit card, I get a 3% charge — of the total invoice/$$ amount!!! — added to the bill. Are you kidding me? I have to pay several hundred dollars just for an electronic transaction?!

Can you imagine if the same thing happened to the rest of us at restaurants, hotels, grocery stores, etc. out there? Consumers would throw a fit! And I’d be right there with them.

Also related, see:

Millennials have money problems — from linkedin.com by Taylor Borden

Excerpt (emphasis DSC):

The average millennial is $117,000 in debt, but don’t blame avocado toast. According to new research, more than 70% of millennials have some form of non-mortgage debt, typically linked to student loans and credit cards.

Too Broke to Finish a Ph.D. Program? Tell Us About It — from the chronicle.com by Fernanda Zamudio-Suarez

Excerpt:

Doctoral programs can be long, trying, and expensive — even cost-prohibitive, depending on your circumstances.

Radar Trends to Watch: August 2022 [Loukides]

On 08/10/2022, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, computer science, emerging technologies, Google, health, innovation, languages and translation, Microsoft, open courseware and systems, platforms, programming, trends, United States, vendors, Web3, by Daniel Christian

Radar Trends to Watch: August 2022 — from oreilly.com by Mike Loukides
Developments in Security, Quantum Computing, Energy, and More

Excerpt:

The large model train keeps rolling on. This month, we’ve seen the release of Bloom, an open, large language model developed by the BigScience collaboration, the first public access to DALL-E (along with a guide to prompt engineering), a Copilot-like model for generating regular expressions from English-language prompts, and Simon Willison’s experiments using GPT-3 to explain JavaScript code.

On other fronts, NIST has released the first proposed standard for post-quantum cryptography (i.e., cryptography that can’t be broken by quantum computers). CRISPR has been used in human trials to re-engineer a patient’s DNA to reduce cholesterol. And a surprising number of cities are paying high tech remote workers to move there.

Inside a radical new project to democratize AI [Heikkilä]

On 07/16/2022, in 21st century, Amazon, Artificial Intelligence/Agents/LLMs/and Related, bots, emerging technologies, ethics, Europe, Google, Microsoft, morals/values, open courseware and systems, by Daniel Christian

Inside a radical new project to democratize AI — from technologyreview.com by Melissa Heikkilä
A group of over 1,000 AI researchers has created a multilingual large language model bigger than GPT-3—and they’re giving it out for free.

Excerpt:

PARIS — This is as close as you can get to a rock concert in AI research. Inside the supercomputing center of the French National Center for Scientific Research, on the outskirts of Paris, rows and rows of what look like black fridges hum at a deafening 100 decibels.

They form part of a supercomputer that has spent 117 days gestating a new large language model (LLM) called BLOOM that its creators hope represents a radical departure from the way AI is usually developed.

Unlike other, more famous large language models such as OpenAI’s GPT-3 and Google’s LaMDA, BLOOM (which stands for BigScience Large Open-science Open-access Multilingual Language Model) is designed to be as transparent as possible, with researchers sharing details about the data it was trained on, the challenges in its development, and the way they evaluated its performance. OpenAI and Google have not shared their code or made their models available to the public, and external researchers have very little understanding of how these models are trained.

Another item re: AI:

Not my job: AI researchers building surveillance tech and deepfakes resist ethical concerns — from protocol.com by Kate Kaye
The computer vision research community is behind on AI ethics, but it’s not just a research problem. Practitioners say the ethics disconnect persists as young computer vision scientists make their way into the ranks of corporate AI.

For the first time, the Computer Vision and Pattern Recognition Conference — a global event that attracted companies including Amazon, Google, Microsoft and Tesla to recruit new AI talent this year — “strongly encouraged”researchers whose papers were accepted to the conference to include a discussion about potential negative societal impacts of their research in their submission forms.

Top Sites for Educator Professional Development — from techlearning.com by Diana Restifo
These professional development sites for education will help teachers refresh and update their practice

Excerpt:

The learning never stops for teachers. Even if continuing education were not required by law, educators would still strive toward deepening their subject knowledge, keeping up with the latest research, sharpening their classroom skills, and learning to use education technology tools.

The following professional development sites for education will help teachers refresh and update their practice, connect with fellow educators and, in some cases, earn continuing education credits. All provide substantial free or modestly priced content.

And for you higher ed folks, see the Tweet below; my thanks to Becky Supiano for this resource out at The Chronicle of Higher Education

I’m putting together a short session for students about to teach (single session, not whole course) for the first time. I’ll focus on planning, and engaging students.

What would your vote be for the single most helpful thing to know before prepping your first class?

— Dr. Molly Metz (@metzpsych) June 16, 2022

Why Improving Student Learning is So Hard — from opencontent.org by David Wiley

Excerpt:

2. Student behavior will normally change only in response to changes in faculty behavior – specifically, the assignments faculty give and the support faculty provide.

For many students, the things-they-do-to-learn are all located within the relatively small universe of things their faculty assign them to do – read chapters, complete homework assignments, etc. For a variety of reasons, and many of them perfectly good reasons, “students don’t do optional” – they only do what they’re going to be graded on.

Therefore, students will likely engage in more effective learning behaviors ONLY IF their faculty assign them more effective learning activities. Faculty can further increase the likelihood of students engaging in more effective learning activities if they support them appropriately throughout the process.

From DSC:
I can put an “Amen” to the above excerpt. For years I managed a Teaching & Learning Digital Studio. Most of the students didn’t come into the Studio for help, because most of the faculty members assigned the normal kinds of things (papers, quizzes, and such). Had there been more digitally-created means of showing what students knew, there would have been more usage of the T&L Digital Studio.

Also, if we want to foster more creativity and innovation — as well as give our learners more choice and more control over their learning — we should occasionally get away from the traditional papers.

Another comment here is that it’s hard to change what faculty members do, when Instructional Designers can’t even get in the car to help faculty members navigate. We need more team-based efforts in designing our learning experiences.

7 Essential Ingredients of a Metaverse [Andreessen Horowitz’s Harkavy, Lazzarin, & Simpson]

On 05/11/2022, in 21st century, 24x7x365 access, 3D, A/V -- audio/visual, emerging technologies, Metaverse, open courseware and systems, platforms, Web3, by Daniel Christian

7 Essential Ingredients of a Metaverse — from future.a16z.com by Liz Harkavy, Eddy Lazzarin, Arianna Simpson

Excerpt:

There has been a lot of buzz about “the metaverse” since its coinage in the ‘90s, but especially during the pandemic (given the surge in online activity), and even more so after Facebook changed its name to Meta.

Is this just a bit of opaque marketing-speak? What is a metaverse exactly? How does one define the term, and where does one draw a line between a metaverse and, say, just another virtual world? These are common questions that people ask about the metaverse, so we thought we’d outline how we see it and how the metaverse intersects with web3.

Also relevant/see:

Can you truly own anything in the metaverse? A law professor explains how blockchains and NFTs don’t protect virtual property — from theconversation.com by João Marinotti

All of the topics covered in The Future Trends Forum [Alexander]

On 04/11/2022, in accessibility / UDL, accreditation, adjunct faculty, Alternatives, blended learning, business side of he, change, changing business models, CMS/LMS, colleges, community colleges, cost of getting a degree, credentialing, curriculum, data related items, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, higher education, hybrid learning, Hyflex learning, ideas, innovation, IT in HE, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, learning spaces, learning theories, new business models, new media literacies, online learning, open courseware and systems, research, science, STEAM-related, teaching & learning, tools, United States, universities, videoconferencing, Virtual Reality (VR) / worlds / learning, Web3, XR - extended reality, by Daniel Christian

The Future Trends Forum Topics page — from forum.futureofeducation.us by Bryan Alexander

Excerpt:

The Future Trends Forum has explored higher education in depth and breadth. Over six years of regular live conversations we have addressed many aspects of academia.

On this page you’ll find a list of our topics. Consider it a kind of table of contents, or, better yet, an index to the Forum’s themes.

Also see:

300 videos: the Future Trends Forum passes another milestone — from bryanalexander.org by Bryan Alexander

Since we launched in early February, 2016, the Forum has successfully published three hundred videos to YouTube. Week after week, month by month, over more than six years we’ve held great conversations, then shared them with the world, free of charge.

Reflections on “Do We Really Want Academic Permanent Records to Live Forever on Blockchain?” [Bohnke]

On 03/19/2022, in 21st century, 24x7x365 access, adult learning, Alternatives, analytics, Artificial Intelligence/Agents/LLMs/and Related, Blockchain, business, career development, cloud-based computing / apps / other cloud-related, CMS/LMS, colleges, communities of practice, community colleges, competency-based learning/education, corporate / business world, corporate universities / corporate training, credentialing, Daniel S. Christian, digital learning, education, elearning, formal learning, future, future of higher education, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, informal learning, innovation, instructional design, K-12 related, law schools, learner profiles, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, lifelong learning, love of learning, microlearning, more voice more choice more control, online learning, open courseware and systems, participation, professional development, project-based learning, publishing, real-world assignments, social learning / networks, society, student-related, technologies for your home, the downsides of how people use tech, training / L&D, United States, universities, user experience (UX), vendors, vision/possibilities, youth, by Daniel Christian

From DSC:
Christin Bohnke raises a great and timely question out at edsurge.com in her article entitled:
Do We Really Want Academic Permanent Records to Live Forever on Blockchain?

Christin does a wonderful job of addressing the possibilities — but also the challenges — of using blockchain for educational/learning-related applications. She makes a great point that the time to look at this carefully is now:

Yet as much as unchangeable education records offer new chances, they also create new challenges. Setting personal and academic information in stone may actually counter the mission of education to help people evolve over time. The time to assess the benefits and drawbacks of blockchain technology is right now, before adoption in schools and universities is widespread.

As Christin mentions, blockchain technology can be used to store more than formal certification data. It could also store such informal certification data such as “research experience, individual projects and skills, mentoring or online learning.”

The keeping of extensive records via blockchain certainly raises numerous questions. Below are a few that come to my mind:

Will this type of record-keeping help or hurt in terms of career development and moving to a different job?
Will — or should — CMS/LMS vendors enable this type of feature/service in their products?
Should credentials from the following sources be considered relevant?
- Microlearning-based streams of content
- Data from open courseware/courses
- Learning that we do via our Personal Learning Networks (PLNs) and social networks
- Learning that we get from alternatives such as bootcamps, coding schools, etc.
Will the keeping of records impact the enjoyment of learning — or vice versa? Or will it depend upon the person?
Will there be more choice, more control — or less so?
To what (granular) level of competency-based education should we go? Or from project-based learning?
Could instructional designers access learners’ profiles to provide more personalized learning experiences?
…and I’m certain there are more questions than these.

All that said…

To me, the answers to these questions — and likely other questions as well — lie in:

Giving a person a chance to learn, practice, and then demonstrate the required skills (regardless of the data the potential employer has access to)
.
Giving each user the right to own their own data — and to release it as they see fit. Each person should have the capability of managing their own information/data without having to have the skills of a software engineer or a database administrator. When something is written to a blockchain, there would be a field for who owns — and can administer — the data.

In the case of finding a good fit/job, a person could use a standardized interface to generate a URL that is sent out to a potential employer. That URL would be good for X days. The URL gives the potential employer the right to access whatever data has been made available to them. It could be full access, in which case the employer is able to run their own queries/searches on the data. Or the learner could restrict the potential employer’s reach to a more limited subset of data.

Visually, speaking:

I still have a lot more thinking to do about this, but that’s where I’m at as of today. Have a good one all!

Learning Ecosystems

A brief reflection on “Why Improving Student Learning is So Hard” [Wiley]

7 Essential Ingredients of a Metaverse [Andreessen Horowitz’s Harkavy, Lazzarin, & Simpson]

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