The Learning & Employment Records (LER) Ecosystem Map — with thanks to Melanie Booth on LinkedIn for this resource
Driving Opportunity and Equity Through Learning & Employment Records

The Learning & Employment Records (LER) Ecosystem Map

Imagine A World Where…

  • Everyone is empowered to access learning and earning opportunities based on what they know and can do, whether those skills and abilities are obtained through degrees, work experiences, or independent learning.
  • People can capture and communicate the skills and competencies they’ve acquired across their entire learning journey — from education, experience and service — with more ease, confidence, and clarity than a traditional resume.
  • Learners and earners control their information and can curate their skills to take advantage of every opportunity they are truly qualified to pursue, opening up pathways that help address systemic inequities.
  • Employers can tap into a wider talent pool and better match applicants to opportunities with verifiable credentials that represent skills, competencies, and achievements.

This is the world that we believe can be created by Learning and Employment Records (LERs), i.e. digital records of learning and work experiences that are linked to and controlled by learners and earners. An interoperable, well-governed LER ecosystem has the potential to transform the future of work so that it is more equitable, efficient, and effective for everyone involved— individuals, training and education providers, employers, and policymakers.


Also per Melanie Booth, see:

 

Thinking with Colleagues: AI in Education — from campustechnology.com by Mary Grush
A Q&A with Ellen Wagner

Wagner herself recently relied on the power of collegial conversations to probe the question: What’s on the minds of educators as they make ready for the growing influence of AI in higher education? CT asked her for some takeaways from the process.

We are in the very early days of seeing how AI is going to affect education. Some of us are going to need to stay focused on the basic research to test hypotheses. Others are going to dive into laboratory “sandboxes” to see if we can build some new applications and tools for ourselves. Still others will continue to scan newsletters like ProductHunt every day to see what kinds of things people are working on. It’s going to be hard to keep up, to filter out the noise on our own. That’s one reason why thinking with colleagues is so very important.

Mary and Ellen linked to “What Is Top of Mind for Higher Education Leaders about AI?” — from northcoasteduvisory.com. Below are some excerpts from those notes:

We are interested how K-12 education will change in terms of foundational learning. With in-class, active learning designs, will younger students do a lot more intensive building of foundational writing and critical thinking skills before they get to college?

  1. The Human in the Loop: AI is built using math: think of applied statistics on steroids. Humans will be needed more than ever to manage, review and evaluate the validity and reliability of results. Curation will be essential.
  2. We will need to generate ideas about how to address AI factors such as privacy, equity, bias, copyright, intellectual property, accessibility, and scalability.
  3. Have other institutions experimented with AI detection and/or have held off on emerging tools related to this? We have just recently adjusted guidance and paused some tools related to this given the massive inaccuracies in detection (and related downstream issues in faculty-elevated conduct cases)

Even though we learn repeatedly that innovation has a lot to do with effective project management and a solid message that helps people understand what they can do to implement change, people really need innovation to be more exciting and visionary than that.  This is the place where we all need to help each other stay the course of change. 


Along these lines, also see:


What people ask me most. Also, some answers. — from oneusefulthing.org by Ethan Mollick
A FAQ of sorts

I have been talking to a lot of people about Generative AI, from teachers to business executives to artists to people actually building LLMs. In these conversations, a few key questions and themes keep coming up over and over again. Many of those questions are more informed by viral news articles about AI than about the real thing, so I thought I would try to answer a few of the most common, to the best of my ability.

I can’t blame people for asking because, for whatever reason, the companies actually building and releasing Large Language Models often seem allergic to providing any sort of documentation or tutorial besides technical notes. I was given much better documentation for the generic garden hose I bought on Amazon than for the immensely powerful AI tools being released by the world’s largest companies. So, it is no surprise that rumor has been the way that people learn about AI capabilities.

Currently, there are only really three AIs to consider: (1) OpenAI’s GPT-4 (which you can get access to with a Plus subscription or via Microsoft Bing in creative mode, for free), (2) Google’s Bard (free), or (3) Anthropic’s Claude 2 (free, but paid mode gets you faster access). As of today, GPT-4 is the clear leader, Claude 2 is second best (but can handle longer documents), and Google trails, but that will likely change very soon when Google updates its model, which is rumored to be happening in the near future.

 

The Public Is Giving Up on Higher Ed — from chronicle.com by Michael D. Smith
Our current system isn’t working for society. Digital alternatives can change that.

Excerpts:

I fear that we in the academy are willfully ignoring this problem. Bring up student-loan debt and you’ll hear that it’s the government’s fault. Bring up online learning and you’ll hear that it is — and always will be — inferior to in-person education. Bring up exclusionary admissions practices and you’ll hear something close to, “Well, the poor can attend community colleges.”

On one hand, our defensiveness is natural. Change is hard, and technological change that risks making traditional parts of our sector obsolete is even harder. “A professor must have an incentive to adopt new technology,” a tenured colleague recently told me regarding online learning. “Innovation adoption will occur one funeral at a time.”

But while our defense of the status quo is understandable, maybe we should ask whether it’s ethical, given what we know about the injustice inherent in our current system. I believe a happier future for all involved — faculty, administrators, and students — is within reach, but requires we stop reflexively protecting our deeply flawed system. How can we do that? We could start by embracing three fundamental principles.

1. Digitization will change higher education.

2. We should want to embrace this change.

3. We have a way to embrace this change.

I fear that we in the academy are willfully ignoring this problem. Bring up student-loan debt and you’ll hear that it’s the government’s fault. Bring up online learning and you’ll hear that it is — and always will be — inferior to in-person education. Bring up exclusionary admissions practices and you’ll hear something close to, “Well, the poor can attend community colleges.”

 

 

US Higher Education Needs a Revolution. What’s Holding It Back? — from bloomberg.com by Tyler Cowen
Not only do professors need to change how they teach, but universities need to change how they evaluate them.

When the revolution in higher education finally arrives, how will we know? I have a simple metric: When universities change how they measure faculty work time. Using this yardstick, the US system remains very far from a fundamental transformation.

But today’s education system is dynamic, and needs to become even more so. There is already the internet, YouTube, and a flurry of potential innovations coming from AI. If professors really are a society’s best minds, shouldn’t they be working to improve the entire educational process, not just punching the equivalent of a time clock at a university?

Such a change would require giving them credit for innovations, which in turn would require a broader conception of their responsibilities. 


Citing Significant Budget Deficits, Several Colleges Face Cuts — from insidehighered.com by Doug Lederman
The affected institutions include Christian Brothers, Delta State, Lane Community College, Miami University, St. Norbert and Shepherd.

Numerous colleges and universities, public and private, announced in recent days that they face significant budget deficits that will require cuts to programs and employees.

Many of the institutions appear to have been motivated by fall enrollment numbers that did not meet their expectations, in most cases representing a failure to recover from record low enrollments during the pandemic. Others cited the lingering effects on enrollment and budgets from COVID-19, exacerbated by the end of federal relief funds.


How universities can adopt a lifelong learning mindset: Lifelong learning that will last — from timeshighereducation.com by various authors
How the traditional university degree can be reimagined as a lifelong educational journey, enabling students to upskill and reskill throughout their lives

The rapid evolution of the workplace and changing skills demands are driving calls for better lifelong learning provision. For universities, this means re-examining traditional teaching practices and course design to ensure that students can benefit from continuing education throughout their careers. It requires more flexible, accessible, bite-sized learning that can be completed in tandem with other professional and personal commitments. But how can this be offered in a coherent, joined-up way without sacrificing quality? From Moocs to microcredentials, these resources offer advice and insight into how lifelong learning opportunities can be developed and improved for future generations.


The College Backlash Is Going Too Far — from theatlantic.com by David Deming; via Matthew Tower who also expresses his concerns re: this article from The Chronicle
Getting a four-year degree is still a good investment. 

American higher education certainly has its problems. But the bad vibes around college threaten to obscure an important economic reality: Most young people are still far better off with a four-year college degree than without one.

Historically, analysis of higher education’s value tends to focus on the so-called college wage premium. That premium has always been massive—college graduates earn much more than people without a degree, on average—but it doesn’t take into account the cost of getting a degree. So the St. Louis Fed researchers devised a new metric, the college wealth premium, to try to get a more complete picture.

But the long-term value of a bachelor’s degree is much greater than it initially appears. If a college professor or pundit tries to convince you otherwise, ask them what they would choose for their own children.

From DSC:
David’s last quote here is powerful and likely true. But that doesn’t mean that we should disregard trying to get the cost of obtaining a degree down by 50% or more. There are still way too many people struggling with student loans — and they have been for DECADES. And others will be joining these same financial struggles — again, for DECADES to come.


Johns Hopkins aims to address teacher shortage with new master’s residency option — from hub.jhu.edu ; via Matthew Tower

The School of Education’s TeachingWell program will provide professional, financial support for applicants looking to start long-term careers in teaching

Students in TeachingWell will earn the Master of Education for Teaching Professionals in four semesters at Johns Hopkins and gain Maryland state teacher certification along with real-world teaching experience—all made stronger by ongoing mentoring, life design, and teacher wellness programs through the university.

“We will focus on teacher well-being and life-design skills that address burnout and mental health concerns that are forcing too many teachers out of the profession,” says Mary Ellen Beaty-O’Ferrall, associate professor at the School of Education and faculty director of TeachingWell. “We want teachers with staying power—effective and financially stable educators with strong personal well-being.”


How to Build Stackable Credentials — from insidehighered.com by Lindsay Daugherty , Peter Nguyen , Jonah Kushner and Peter Riley Bahr
Five actions states and colleges are taking.

Stackable credentials are a top priority for many states and colleges these days. The term can be used to mean different things, from college efforts to embed short-term credentials into their degree programs to larger-scale efforts to rethink the way credentialing is done through alternative approaches, like skills badges. The goals of these initiatives are twofold: (1) to ensure individuals can get credit for a range of different learning experiences and better integrate these different types of learning, and (2) to better align our education and training systems with workforce needs, which often require reskilling through training and credentials below the bachelor’s degree level.S

 

As AI Chatbots Rise, More Educators Look to Oral Exams — With High-Tech Twist — from edsurge.com by Jeffrey R. Young

To use Sherpa, an instructor first uploads the reading they’ve assigned, or they can have the student upload a paper they’ve written. Then the tool asks a series of questions about the text (either questions input by the instructor or generated by the AI) to test the student’s grasp of key concepts. The software gives the instructor the choice of whether they want the tool to record audio and video of the conversation, or just audio.

The tool then uses AI to transcribe the audio from each student’s recording and flags areas where the student answer seemed off point. Teachers can review the recording or transcript of the conversation and look at what Sherpa flagged as trouble to evaluate the student’s response.

 

The Enemy Within: Former College Presidents Offer Warnings — from forbes-com.cdn.ampproject.org by David Rosowsky; via Robert Gibson on LinkedIn

Excerpt (emphasis DSC):

Brian Mitchell, former president of Bucknell University and Washington & Jefferson College, draws on his experience to offer insight in his newest Forbes contribution. He also offers a stern warning: “Boards, administrators, and faculty must wake up to the new realities they now face… the faculty can no longer live in a world that no longer exists… institutional change will happen at a speed to which they are unaccustomed and potentially unwilling to accept.” President Mitchell then goes on to offer some immediate steps that can be taken. Perhaps the most important is to “abandon the approach to governance where trustees are updated in their periodic board meetings.”

Incremental change is possible, but transformational change may not be.

Therein lies the conundrum about which Rosenberg writes in his new book. Higher ed’s own systems are inhibiting needed transformational change.

Also just published was the book, “Whatever It Is, I’m Against It: Resistance to Change in Higher Education” by Brian Rosenberg, former president of Macalester College. Articles on Rosenberg’s observations, analysis, and cautions have appeared this month in both The Chronicle of Higher Education and Inside Higher Ed, the two leading higher education publications in the US.


Addendum on 10/6/23:

Higher Education as Its Own Worst Enemy — from insidehighered.com/ by Susan H. Greenberg
In a wide-ranging discussion about his new book, Brian Rosenberg explains how shared governance, tenure and other practices stifle change on college campuses.

He argues that the institutions designed to foster critical inquiry and the open exchange of ideas are themselves staunchly resistant to both. 

The other would be some serious thinking about pedagogy and how students learn. Because the research is there if people were willing to take it seriously and think about ways of providing an education that is not quite as reliant upon lots of faculty with Ph.D.s. Is that easy to do? No, but it is something that I think there should at least begin to be some serious discussions about.

Shared governance is one of those things that if you ask any college president off the record, they’ll probably express their frustration, then they’ll go back to their campus and wax poetic about the wonders of shared governance, because that’s what they have to do to survive.

 

Student Use Cases for AI: Start by Sharing These Guidelines with Your Class — from hbsp.harvard.edu by Ethan Mollick and Lilach Mollick

To help you explore some of the ways students can use this disruptive new technology to improve their learning—while making your job easier and more effective—we’ve written a series of articles that examine the following student use cases:

  1. AI as feedback generator
  2. AI as personal tutor
  3. AI as team coach
  4. AI as learner

Recap: Teaching in the Age of AI (What’s Working, What’s Not) — from celt.olemiss.edu by Derek Bruff, visiting associate director

Earlier this week, CETL and AIG hosted a discussion among UM faculty and other instructors about teaching and AI this fall semester. We wanted to know what was working when it came to policies and assignments that responded to generative AI technologies like ChatGPT, Google Bard, Midjourney, DALL-E, and more. We were also interested in hearing what wasn’t working, as well as questions and concerns that the university community had about teaching and AI.


Teaching: Want your students to be skeptical of ChatGPT? Try this. — from chronicle.com by Beth McMurtrie

Then, in class he put them into groups where they worked together to generate a 500-word essay on “Why I Write” entirely through ChatGPT. Each group had complete freedom in how they chose to use the tool. The key: They were asked to evaluate their essay on how well it offered a personal perspective and demonstrated a critical reading of the piece. Weiss also graded each ChatGPT-written essay and included an explanation of why he came up with that particular grade.

After that, the students were asked to record their observations on the experiment on the discussion board. Then they came together again as a class to discuss the experiment.

Weiss shared some of his students’ comments with me (with their approval). Here are a few:


2023 EDUCAUSE Horizon Action Plan: Generative AI — from library.educause.edu by Jenay Robert and Nicole Muscanell

Asked to describe the state of generative AI that they would like to see in higher education 10 years from now, panelists collaboratively constructed their preferred future.
.

2023-educause-horizon-action-plan-generative-ai


Will Teachers Listen to Feedback From AI? Researchers Are Betting on It — from edsurge.com by Olina Banerji

Julie York, a computer science and media teacher at South Portland High School in Maine, was scouring the internet for discussion tools for her class when she found TeachFX. An AI tool that takes recorded audio from a classroom and turns it into data about who talked and for how long, it seemed like a cool way for York to discuss issues of data privacy, consent and bias with her students. But York soon realized that TeachFX was meant for much more.

York found that TeachFX listened to her very carefully, and generated a detailed feedback report on her specific teaching style. York was hooked, in part because she says her school administration simply doesn’t have the time to observe teachers while tending to several other pressing concerns.

“I rarely ever get feedback on my teaching style. This was giving me 100 percent quantifiable data on how many questions I asked and how often I asked them in a 90-minute class,” York says. “It’s not a rubric. It’s a reflection.”

TeachFX is easy to use, York says. It’s as simple as switching on a recording device.

But TeachFX, she adds, is focused not on her students’ achievements, but instead on her performance as a teacher.


ChatGPT Is Landing Kids in the Principal’s Office, Survey Finds — from the74million.org by Mark Keierleber
While educators worry that students are using generative AI to cheat, a new report finds students are turning to the tool more for personal problems.

Indeed, 58% of students, and 72% of those in special education, said they’ve used generative AI during the 2022-23 academic year, just not primarily for the reasons that teachers fear most. Among youth who completed the nationally representative survey, just 23% said they used it for academic purposes and 19% said they’ve used the tools to help them write and submit a paper. Instead, 29% reported having used it to deal with anxiety or mental health issues, 22% for issues with friends and 16% for family conflicts.

Part of the disconnect dividing teachers and students, researchers found, may come down to gray areas. Just 40% of parents said they or their child were given guidance on ways they can use generative AI without running afoul of school rules. Only 24% of teachers say they’ve been trained on how to respond if they suspect a student used generative AI to cheat.


Embracing weirdness: What it means to use AI as a (writing) tool — from oneusefulthing.org by Ethan Mollick
AI is strange. We need to learn to use it.

But LLMs are not Google replacements, or thesauruses or grammar checkers. Instead, they are capable of so much more weird and useful help.


Diving Deep into AI: Navigating the L&D Landscape — from learningguild.com by Markus Bernhardt

The prospect of AI-powered, tailored, on-demand learning and performance support is exhilarating: It starts with traditional digital learning made into fully adaptive learning experiences, which would adjust to strengths and weaknesses for each individual learner. The possibilities extend all the way through to simulations and augmented reality, an environment to put into practice knowledge and skills, whether as individuals or working in a team simulation. The possibilities are immense.

Thanks to generative AI, such visions are transitioning from fiction to reality.


Video: Unleashing the Power of AI in L&D — from drphilippahardman.substack.com by Dr. Philippa Hardman
An exclusive video walkthrough of my keynote at Sweden’s national L&D conference this week

Highlights

  • The wicked problem of L&D: last year, $371 billion was spent on workplace training globally, but only 12% of employees apply what they learn in the workplace
  • An innovative approach to L&D: when Mastery Learning is used to design & deliver workplace training, the rate of “transfer” (i.e. behaviour change & application) is 67%
  • AI 101: quick summary of classification, generative and interactive AI and its uses in L&D
  • The impact of AI: my initial research shows that AI has the potential to scale Mastery Learning and, in the process:
    • reduce the “time to training design” by 94% > faster
    • reduce the cost of training design by 92% > cheaper
    • increase the quality of learning design & delivery by 96% > better
  • Research also shows that the vast majority of workplaces are using AI only to “oil the machine” rather than innovate and improve our processes & practices
  • Practical tips: how to get started on your AI journey in your company, and a glimpse of what L&D roles might look like in a post-AI world

 

Preparing Students for the AI-Enhanced Workforce — from insidehighered.com by Ray Schroeder
Our graduating and certificate-completing students need documented generative AI skills, and they need them now.

The common adage repeated again and again is that AI will not take your job; a person with AI skills will replace you. The learners we are teaching this fall who will be entering, re-entering or seeking advancement in the workforce at the end of the year or in the spring must become demonstrably skilled in using generative AI. The vast majority of white-collar jobs will demand the efficiencies and flexibilities defined by generative AI now and in the future. As higher education institutions, we will be called upon to document and validate generative AI skills.


AI image generators: 10 tools, 10 classroom uses — from ditchthattextbook.com by Matt Miller

AI image generators: 10 tools, 10 classroom uses


A Majority of New Teachers Aren’t Prepared to Teach With Technology. What’s the Fix? — from edweek.org by Alyson Klein

Think all incoming teachers have a natural facility with technology just because most are digital natives? Think again.

Teacher preparation programs have a long way to go in preparing prospective educators to teach with technology, according to a report released September 12 by the International Society for Technology in Education, a nonprofit.

In fact, more than half of incoming teachers—56 percent—lack confidence in using learning technology prior to entering the classroom, according to survey data included with the report.


5 Actual Use Cases of AI in Education: Newsletter #68 — from transcend.substack.com by Alberto Arenaza
What areas has AI truly impacted educators, learners & workers?

  1. AI Copilot for educators, managers and leaders
  2. Flipped Classrooms Chatbots
  3. AI to assess complex answers
  4. AI as a language learning tool
  5. AI to brainstorm ideas

AI-Powered Higher Ed — from drphilippahardman.substack.com by  Dr. Philippa Hardman
What a House of Commons round table discussion tells us about how AI will impact the purpose of higher education

In this week’s blog post I’ll summarise the discussion and share what we agreed would be the most likely new model of assessment in HE in the post-AI world.

But this in turn raises a bigger question: why do people go to university, and what is the role of higher education in the twenty first century? Is it to create the workforce of the future? Or an institution for developing deep and original domain expertise? Can and should it be both?


How To Develop Computational Thinkers — from iste.org by Jorge Valenzuela

In my previous position with Richmond Public Schools, we chose to dive in with computational thinking, programming and coding, in that order. I recommend building computational thinking (CT) competency first by helping students recognize and apply the four elements of CT to familiar problems/situations. Computational thinking should come first because it’s the highest order of problem-solving, is a cross-curricular skill and is understandable to both machines and humans. Here are the four components of CT and how to help students understand them.

 

Next, The Future of Work is… Intersections — from linkedin.com by Gary A. Bolles; via Roberto Ferraro

So much of the way that we think about education and work is organized into silos. Sure, that’s one way to ensure a depth of knowledge in a field and to encourage learners to develop mastery. But it also leads to domains with strict boundaries. Colleges are typically organized into school sub-domains, managed like fiefdoms, with strict rules for professors who can teach in different schools.

Yet it’s at the intersections of seemingly-disparate domains where breakthrough innovation can occur.

Maybe intersections bring a greater chance of future work opportunity, because that young person can increase their focus in one arena or another as they discover new options for work — and because this is what meaningful work in the future is going to look like.

From DSC:
This posting strikes me as an endorsement for interdisciplinary degrees. I agree with much of this. It’s just hard to find the right combination of disciplines. But I supposed that depends upon the individual student and what he/she is passionate or curious about.


Speaking of the future of work, also see:

Centaurs and Cyborgs on the Jagged Frontier — from oneusefulthing.org by Ethan Mollick
I think we have an answer on whether AIs will reshape work…

A lot of people have been asking if AI is really a big deal for the future of work. We have a new paper that strongly suggests the answer is YES.
.

Consultants using AI finished 12.2% more tasks on average, completed tasks 25.1% more quickly, and produced 40% higher quality results than those without. Those are some very big impacts. Now, let’s add in the nuance.

 

From DSC:
In Rick Seltzer’s Daily Briefing for 9-18-23, he ends the briefing with this important point:

The bigger picture: Culture is exceedingly hard to change, especially after trust evaporates in a crisis. And crises can be particularly wrenching when institutions haven’t established cultures of transparency and accountability during good times. Instead, trust continues to erode in a vicious cycle.

And I thought to myself, the scope of Rick’s conclusion could likely be expanded/applied to institutions of higher education as a whole.

 

A First Look at Teaching Preferences since the Pandemic”— from library.educause.edu/ by Muscanell

2023 Faculty & Technology Report: A First Look at Teaching Preferences since the Pandemic

This is the first faculty research conducted by EDUCAUSE since 2019. Since then, the higher education landscape has been through a lot, including COVID-19, fluctuations in enrollment and public funding, and the rapid adoption of multiple instructional modalities and new technologies. In this report, we describe the findings of the research in four key areas:

  • Modality preferences and the impacts of teaching in non-preferred modes
  • Experiences teaching online and hybrid courses
  • Technology and digital availability of course components
  • Types of support needed and utilized for teaching

From DSC:
Polling the faculty members and getting their feedback is not as relevant and important to the future of higher education as better addressing the needs and wants of parents and students who are paying the bills. Asking faculty members what they want to post online is not as relevant as what students want and need to see online.


From DSC:
More fringe responses — versus overhauling pricing, updating curriculum, providing more opportunities to try out jobs before investing in a degree, and/or better rewarding those adjunct faculty members who are doing the majority of the teaching on many campuses.


Online college enrollment is on the rise: What brings students to virtual campuses? — from digitaljournal.com by Jill Jaracz and Emma Rubin; via GSV

Before the pandemic, online learning programs were typically for people going back to school to augment or change their career or pursuing a graduate degree to enhance their career while they work. That attitude is shifting as students juggle learning with jobs, family responsibilities, and commutes. In California, 4 in 5 community college classes were in person before the pandemic. By 2021, just 1 in 4 were in person, while 65% were online, according to the California Community Colleges Chancellor’s Office.

Younger students are also opting for online classes. EducationDynamics found in 2023 that the largest share of students pursuing undergraduate or graduate degrees online is 35 or younger. That said, 35% of students pursuing online undergraduate degrees are between


 

From DSC: If this is true, how will we meet this type of demand?!?

RESKILLING NEEDED FOR 40% OF WORKFORCE BECAUSE OF AI, REPORT FROM IBM SAYS — from staffingindustry.com; via GSV

Generative AI will require skills upgrades for workers, according to a report from IBM based on a survey of executives from around the world. One finding: Business leaders say 40% of their workforces will need to reskill as AI and automation are implemented over the next three years. That could translate to 1.4 billion people in the global workforce who require upskilling, according to the company.

 

10 Ways Artificial Intelligence Is Transforming Instructional Design — from er.educause.edu by Robert Gibson
Artificial intelligence (AI) is providing instructors and course designers with an incredible array of new tools and techniques to improve the course design and development process. However, the intersection of AI and content creation is not new.

What does this mean for the field of instructional and course design? I have been telling my graduate instructional design students that AI technology is not likely to replace them any time soon because learning and instruction are still highly personalized and humanistic experiences. However, as these students embark on their careers, they will need to understand how to appropriately identify, select, and utilize AI when developing course content.

Here are a few interesting examples of how AI is shaping and influencing instructional design. Some of the tools and resources can be used to satisfy a variety of course design activities, while others are very specific.


GenAI Chatbot Prompt Library for Educators — from aiforeducation.io
We have a variety of prompts to help you lesson plan and do adminstrative tasks with GenAI chatbots like ChatGPT, Claude, Bard, and Perplexity.

Also relevant/see:

AI for Education — from linkedin.com
Helping teachers and schools unlock their full potential through AI



Google Chrome will summarize entire articles for you with built-in generative AI — from theverge.com by Jay Peters
Google’s AI-powered article summaries are rolling out for iOS and Android first, before coming to Chrome on the desktop.

Google’s AI-powered Search Generative Experience (SGE) is getting a major new feature: it will be able to summarize articles you’re reading on the web, according to a Google blog post. SGE can already summarize search results for you so that you don’t have to scroll forever to find what you’re looking for, and this new feature is designed to take that further by helping you out after you’ve actually clicked a link.


A Definitive Guide to Using Midjourney — from every.to by Lucas Crespo
Everything you need to know about generating AI Images

In this article, I’ll walk you through the most powerful and useful techniques I’ve come across. We’ll cover:

  • Getting started in Midjourney
  • Understanding Midjourney’s quirks with interpreting prompts
  • Customizing Midjourney’s image outputs after the fact
  • Experimenting with a range of styles and content
  • Uploading and combining images to make new ones via image injections
  • Brainstorming art options with parameters like “chaos” and “weird”
  • Finalizing your Midjourney output’s aspect ratio

And much more.


Report: Potential NYT lawsuit could force OpenAI to wipe ChatGPT and start over — from arstechnica.com by Ashley Belanger; via Misha da Vinci
OpenAI could be fined up to $150,000 for each piece of infringing content.

Weeks after The New York Times updated its terms of service (TOS) to prohibit AI companies from scraping its articles and images to train AI models, it appears that the Times may be preparing to sue OpenAI. The result, experts speculate, could be devastating to OpenAI, including the destruction of ChatGPT’s dataset and fines up to $150,000 per infringing piece of content.

NPR spoke to two people “with direct knowledge” who confirmed that the Times’ lawyers were mulling whether a lawsuit might be necessary “to protect the intellectual property rights” of the Times’ reporting.


Midjourney Is Easily Tricked Into Making AI Misinformation, Study Finds — from bloomberg.com (paywall)


AI-generated art cannot be copyrighted, rules a US Federal Judge — from msn.com by Wes Davis; via Tom Barrett


Do you want to Prepare your Students for the AI World? Support your Speech and Debate Team Now — from stefanbauschard.substack.com by Stefan Bauschard
Adding funding to the debate budget is a simple and immediate step administrators can take as part of developing a school’s “AI Strategy.”

 
 

The Changing Landscape of Online Education (CHLOE), 2023
Student Demand Moves Higher Ed Toward a Multi-Modal Future

The majority of survey participants report increased student demand for online and hybrid learning juxtaposed with decreased demand for face-to-face courses and programs. Most participants also say that their institutions are aligning or working to align their strategic priorities to meet this demand. Notable findings from the 50+-page report include:

  • Face-to-Face enrollment is stagnant or declining.
  • Online and hybrid enrollment is growing.
  • Institutions are quickly aligning their strategic priorities to meet online/hybrid student demand.
  • “Quiet” quality assurance.

 
© 2024 | Daniel Christian