liberal arts

How might you alter your teaching if in 5 years you knew: [Stefan Bauschard]

On 10/24/2023, in adjunct faculty, change, colleges, community colleges, expectations, experimentation, faculty, future, future of higher education, game-changing environment, generational differences, higher education, homeschooling/homeschoolers, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, online learning, pedagogy, student teaching/teacher education, student-related, teachers, teaching & learning, trends, United States, universities, by Daniel Christian

From DSC:
Interesting fodder for thought, for sure. Thanks Stefan.

Thinking with Colleagues: AI in Education [Grush & Wagner]

On 10/14/2023, in accessibility / UDL, adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, assessment, Bias | Diversity Equity & Inclusion (DE&I), change, colleges, communities of practice, community colleges, copyright/ownership/NFTs, education technology, emerging technologies, engagement / engaging students, experimentation, face-to-face, faculty, future of higher education, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, IT in HE, K-12 related, learning, learning ecosystem, Learning Experience Design, liberal arts, Microsoft, open courseware and systems, platforms, privacy, student-related, teaching & learning, United States, universities, vendors, by Daniel Christian

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?

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.
We will need to generate ideas about how to address AI factors such as privacy, equity, bias, copyright, intellectual property, accessibility, and scalability.
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.

Everyday Media Literacy: An Analog Guide for Your Digital Life — from routledge.com by Sue Ellen Christian

In this second edition, award-winning educator Sue Ellen Christian offers students an accessible and informed guide to how they can consume and create media intentionally and critically.

The textbook applies media literacy principles and critical thinking to the key issues facing young adults today, from analyzing and creating media messages to verifying information and understanding online privacy. Through discussion prompts, writing exercises, key terms, and links, readers are provided with a framework from which to critically consume and create media in their everyday lives. This new edition includes updates covering privacy aspects of AI, VR and the metaverse, and a new chapter on digital audiences, gaming, and the creative and often unpaid labor of social media and influencers. Chapters examine news literacy, online activism, digital inequality, social media and identity, and global media corporations, giving readers a nuanced understanding of the key concepts at the core of media literacy. Concise, creative, and curated, this book highlights the cultural, political, and economic dynamics of media in contemporary society, and how consumers can mindfully navigate their daily media use.

This textbook is perfect for students and educators of media literacy, journalism, and education looking to build their understanding in an engaging way.

Canva and Adobe are going hard with it re: the use of AI

On 10/09/2023, in 21st century, 24x7x365 access, adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, colleges, communications, community colleges, content development, aggregation, repositories, corporate universities / corporate training, design, digital photography, digital video, education technology, emerging technologies, engagement / engaging students, experimentation, faculty, graphics, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, IT in HE, K-12 related, liberal arts, maker movement, multimedia, online media, photography, platforms, productivity / tips and tricks, skills, student teaching/teacher education, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, training / L&D, United States, universities, vendors, visualizing information, web design and production, by Daniel Christian

Canva’s new AI tools automate boring, labor-intensive design tasks — from theverge.com by Jess Weatherbed
Magic Studio features like Magic Switch automatically convert your designs into blogs, social media posts, emails, and more to save time on manually editing documents.

Canva launches Magic Studio, partners with Runway ML for video — from bensbites.beehiiv.com by Ben Tossell

Here are the highlights of launched features under the new Magic Studio:

Magic Design – Turn ideas into designs instantly with AI-generated templates.
Magic Switch – Transform content into different formats and languages with one click.
Magic Grab – Make images editable like Canva templates for easy editing.
Magic Expand – Use AI to expand images beyond the original frame.
Magic Morph – Transform text and shapes with creative effects and prompts.
Magic Edit – Make complex image edits using simple text prompts.
Magic Media – Generate professional photos, videos and artworks from text prompts.
Magic Animate – Add animated transitions and motion to designs instantly.
Magic Write – Generate draft text and summaries powered by AI.

Adobe Firefly

Addendums on 10/11/23:

We released a new model ?

!!! Firefly Image 2 !!!!

As a scientist I am in disbelief that such model is possible with a small dataset as we had.

We compensated artists for training it.

We worked very hard on it. Please, enjoy! #AdobeMax https://t.co/j2TUiiyjN7 pic.twitter.com/gqABThSBWZ

— Kris Kashtanova (@icreatelife) October 10, 2023

Adobe Releases New AI Models Aimed at Improved Graphic Design — from bloomberg.com
New version of Firefly is bigger than initial tool, Adobe says Illustrator, Express programs each get own generative tools

A few hours ago, Adobe released Firefly 2, their new AI image generator.

But how good is it?

I compared it to Midjourney & DALL-E 3 across 10 very different image categories so you don’t have to.

Here are the results:

— Chase Lean (@chaseleantj) October 11, 2023

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

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?

AI Copilot for educators, managers and leaders
Flipped ~~Classrooms~~ Chatbots
AI to assess complex answers
AI as a language learning tool
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.
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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.

What Will Determine AI’s Impact on College Teaching? 5 Signs to Watch. — from chronicle.com by Beth McMurtrie (behind a paywall)

One of the biggest challenges to navigate now is the fact that more digital tools will come with generative AI already embedded in them, says Annette Vee, director of composition and an associate professor at the University of Pittsburgh. “It’s everywhere in professional writing.”

“We need to be fundamentally rethinking ways we teach writing, so we are thinking about integrating tools mindfully,” says Vee, who helped develop a new resource, TextGenEd, that provides guidance in this area. “The real challenge is how do we teach courses that are preparing students and that are smart about generative AI? We have very few teachers currently equipped to do that work.”

“It’s best if there are real stakes attached to the work, for example, an authentic audience the student is writing to,” he writes. “A subject on which students have both sufficient interest and knowledge in order to feel as though they can write convincingly to this audience also matters a lot.”

Also relevant/see — via Robert Gibson on LinkedIn:

Learnt.ai — Built for Learning Specialists — from learnt.ai
Harness the power of artificial intelligence to enhance your learning and development efforts with our easy-to-use platform – no technical expertise required!

Introducing Learnt.ai – a revolutionary collection of AI-powered content generation tools and AI chatbots that are specifically designed to support the common writing tasks of educationalists and learning and development professionals. Imagine being able to generate learning objectives on any topic of your choice, create engaging icebreakers and activities, write assessment questions with ease, and so much more.

Also relevant/see:

An AI and higher education panel — from aiandacademia.substack.com by Bryan Alexander
Live notes

Today I took in a webinar on AI and higher education. The American Association of Colleges and Universities hosted “The AI Revolution: Transforming Higher Education for the Workforce of Tomorrow” and I’d like to share my running notes.

Also relevant/see:

Students’ Perspectives on Using AI — from er.educause.edu by Sarah J. Buszka, Jeremy Cortez, and Isabella Meltzer

Students are using artificial intelligence tools to assist them in their academic careers. Three students share their viewpoints on the tools they use and how using these tools helps them in their coursework and prepares them for the professional world.

Also relevant/see:

Why Professors Are Polarized on AI — from insidehighered.com by Susan D’Agostino
Academics who perceive threats to education from AI band together as a survival mechanism. The resulting alliances echo divisions formed during online learning’s emergence.

Are your students prepared for active learning? You can help them! — from The Educationalist at educationalist.substack.com by Alexandra Mihai

What does active learning require from students?
There is no secret that PBL and all other active learning approaches are much more demanding from students compared to traditional methods, mainly in terms of skills and attitudes towards learning. Here are some of the aspects where students, especially when first faced to active learning, seem to struggle:

Formulating own learning goals and following through with independent study. While in traditional teaching the learning goals are given to students, in PBL (or at least in some of its purest variants), they need to come up with their own, for each problem they are solving. This requires understanding the problem well but also a certain frame of mind where one can assess what is necessary to solve it and make a plan of how to go about it (independently and as a group). All these seemingly easy steps are often new to students and something they intrinsically expect from us as educators.

From DSC:
The above excerpt re: formulating one’s own learning goals reminded me of project management and learning how to be a project manager.

It reminded me of a project that I was assigned back at Kraft (actually Kraft General Foods at the time). It was an online-based directory of everyone in the company at the time. When it was given to me, several questions arose in my mind:

Where do I start?
How do I even organize this project?
What is the list of to-do’s?
Who will I need to work with?

Luckily I had a mentor/guide who helped me get going and an excellent contact with the vendor who educated me and helped me get the ball rolling.

I’ll end with another quote and a brief comment:

Not being afraid of mistakes and learning from them.
The education system, at all stages, still penalises mistakes, often with long term consequences. So it’s no wonder students are afraid of making mistakes…

From DSC:
How true.

AI Can Teach Students a Powerful Lesson About the Truth — from edweek.org by Rachna Nath
How I’m harnessing ChatGPT in the classroom

What we teachers desperately need, though, is an ocean of examples and training. We need to see and share examples of generative AI—any type of artificial intelligence that can be used to create new text, images, video, audio, code, or data—being used across the curriculum. We need catalogs of new lesson plans and new curriculum.

And we need training on theoretical and practical levels: training to understand what artificial intelligence actually is and where it stands in the development timeline and training about how to integrate it into our classes.

So, my advice to teachers is to use any and all the generative AI you can get your hands on. Then experience—for yourself—verification of the information. Track it back to the source because in doing so, you’ll land on the adjustments you need to make in your classes next year.

From DSC:
Interesting.

Learners can now seamlessly transition between AI-powered assistance (AI Tutor) and Live Expert support to get access to instant support, whether through AI-guided learning or real-time interactions with a human expert.

From Brainly Enrolls New AI-Powered Tools for More
Personalized and Accessible Learning (businesswire.com)

ASSIGNMENT MAKEOVERS IN THE AI AGE WITH DEREK BRUFF — from teachinginhighered.com by Bonni Stachowiak
Derek Bruff shares about assignment makeovers in the AI age on episode 481 of the Teaching in Higher Ed podcast

Comment on this per Derek Bruff:

Why not ask ChatGPT to write what King or X would say about a current debate and then have the students critique the ChatGPT output? That would meet the same learning goals while also teaching AI literacy.

(Be sure to read Asim’s contribution for a useful take.)

Generative AI in Schools: A Closer Look and Future Predictions — from thejournal.com by Ted Mo Chen (emphasis DSC)

Here’s a closer look at the concurrent AI landscape in schools — and a prediction of what the future holds.

So far, high-profile ventures in the instruction realm, such as Kyron Learning, have fused teacher-produced, recorded content with LLM-powered conversational UX. The micro-learning tool Nolej references internet material when generating tasks and tests, but always holds the language model closely to the ground truth provided by teachers. Both are intriguing takes on re-imagining how to deliver core instruction and avoid hallucinations (generated content that is nonsensical).

Also see this posting on LinkedIn about that article, where Ted Mo Chen mentions the following companies:

Companies to watch:

New report: Trends in Learning 2023 — from open.ac.uk by Professor Agnes Kukulska-Hulme

So, what six trends have we chosen for this year’s report? They are: advances in AI, the metaverse and learning, challenge-based learning, entrepreneurial learning, seeing yourself in the curriculum and multimodal learning. In the report, we discuss each of the trends in turn, why we think they are important and the impact they are already having or will have on workplace learning. We have also interviewed six people, experts in their field, to find out their opinions and experiences of the trends, sharing their insights in the report.

Unity executive shares her thoughts on the future of education and technology with the rise in popularity of A.I. and real-time 3D content — from fortune.com by Preston Fore

As a result, real-time 3D jobs are among the most in demand within the tech industry. According to Unity’s vice president of Education and Social Impact, Jessica Lindl, demand is 50% higher than traditional IT jobs—adding that salaries for real-time 3D jobs are 60% greater.

“We want to provide really simple on ramps and pathways that will lead you into entry level jobs so that at any point in your career, you can decide to transfer into the industry,” Lindl says.

How universities worldwide are responding to generative AI — from linkedin.com by University World News

University World News continues its exploration of generative AI in our new special report on ‘AI and Higher Education’. In commentaries and features, academics and our journalists around the world investigate issues and developments around AI that are impacting on universities. Generative AI tools are challenging and changing higher education systems and institutions — how they are run as well as ways of teaching and learning and conducting research.

We’ve collated the lead articles below for you to read and the full report is available here.

What’s the future of generative AI? An early view in 15 charts — from mckinsey.com
Generative AI has hit the ground running—so fast that it can feel hard to keep up. Here’s a quick take pulled from our top articles and reports on the subject.

Teaching in the Age of AI — from cft.vanderbilt.edu by Michael Coley, Stacey M. Johnson, Paige Snay, Joe Bandy, John Bradley, and Ole Molvig

This guide will explore:

What is generative AI, and where can it be found?
How can I harness generative AI tools in my teaching to improve student learning?
How can I craft assignments that deter unauthorized use of generative AI?
How does academic integrity relate to generative AI tools?
What resources are there for instructors who want to engage with generative AI tools?

15 Inspirational Voices in the Space Between AI and Education — from jeppestricker.substack.com by Jeppe Klitgaard Stricker
Get Inspired for AI and The Future of Education.

My advice for you today is this: fill your LinkedIn-feed and/or inbox with ideas, inspirational writing and commentary on AI.

This will get you up to speed quickly and is a great way to stay informed on the newest movements you need to be aware of.

My personal recommendation for you is to check out these bright people who are all very active on LinkedIn and/or have a newsletter worth paying attention to.

I have kept the list fairly short – only 15 people – in order to make it as easy as possible for you to begin exploring.

It is crucial to recognize that the intrinsic value of higher education isn’t purely in its ability to adapt to market fluctuations or technological innovations. Its core strength lies in promoting critical thinking, nurturing creativity, and instilling a sense of purpose and belonging. As AI progresses, these traits will likely become even more crucial. The question then becomes if higher education institutions as we know them today are the ony ones, or indeed the best ones, equipped to convey those core strengths to students.

Higher education clearly finds itself caught in a whirlwind of transformation, both in its essence and execution. The juxtaposition of legacy structures and the evolving technological landscape paints a complex picture.

For institutional leaders, the dual challenge lies in proactively seeking and initiating change (not merely adapting to it) without losing sight of their foundational principles. Simultaneously, they must equip students with skills and perspectives that AI cannot replicate.

— from Is Higher Education Nearing the Tipping Point?
by Jeppe Klitgaard Stricker

EdTech Companies Are Racing to Build a Github Copilot for Teachers. This Will Not Be Easy. — from danmeyer.substack.com by Dan Meyer; via Matthew Tower
Generative AI has produced an extremely useful tool for software developers. Can it do the same for teachers?

Also, Matthew Tower, pulled this quote from The big problem with grades. / via Washington Post

“They begged, bargained with, and berated their instructor in pursuit of better grades — not “because they like points,” but rather, “because the education system has told them that these points are the currency with which they can buy a successful future.””

Don’t Be Fooled: How You Can Master Media Literacy in the Digital Age — from youtube.com by Professor Sue Ellen Christian

During this special keynote presentation, Western Michigan University (WMU) professor Sue Ellen Christian speaks about the importance of media literacy for all ages and how we can help educate our friends and families about media literacy principles. Hosted by the Grand Rapids Public Library and GRTV, a program of the Grand Rapids Community Media Center. Special thanks to the Grand Rapids Public Library Foundation for their support of this program.

Excerpts:

Also relevant/see:

Kalamazoo Valley Museum’s newest exhibit teaches community about media literacy — from mlive.com by Gabi Broekema

From DSC:
Time will tell.

Per Jeff Maggioncalda, Coursera CEO: “This system-wide industry micro-credential program sets an innovative blueprint for the future of higher education.”

***

University Of Texas, Coursera Launch Historic Micro-credential Partnership — from forbes.com by Michael T. Nietzel

The University of Texas and Coursera, the online learning platform and a pioneer of Massive Open Online Courses (MOOCS), are launching a large-scale, industry-recognized micro-credential program. The collaboration was announced today in a blogpost by Coursera.

Through the new partnership, every student, faculty, and staff (and even alumni) across all nine universities in the University of Texas (UT) System will gain access to Courser’s Career Academy for no additional cost to them.

The Homework Apocalypse — from oneusefulthing.org by Ethan Mollick
Fall is going to be very different this year. Educators need to be ready.

Excerpt:

Students will cheat with AI. But they also will begin to integrate AI into everything they do, raising new questions for educators. Students will want to understand why they are doing assignments that seem obsolete thanks to AI. They will want to use AI as a learning companion, a co-author, or a teammate. They will want to accomplish more than they did before, and also want answers about what AI means for their future learning paths. Schools will need to decide how to respond to this flood of questions.

The challenge of AI in education can feel abstract, so to understand a bit more about what is going to happen, I wanted to examine some common assignment types.

Recording Arts as Reengagement, Social Justice and Pathway — from gettingsmart.com

Key Points

After a successful career as a recording artist, David “TC” Ellis created Studio 4 in St. Paul to spot budding music stars.
It became a hangout spot for creative young people, most of whom had “dropped out of school due to boredom and a sense that school wasn’t relevant to their lives and dreams.”
Ellis and colleagues then opened the High School for Recording Arts in 1998.

“The economic potential of generative AI” [McKinsey & Co.] + using AI in the classroom + other AI-related items

On 06/27/2023, in adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, assessment, business, changing business models, colleges, community colleges, corporate / business world, digital learning, digital video, economics, education technology, emerging technologies, experimentation, faculty, future, future of higher education, game-changing environment, generational differences, graphics, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, lifelong learning, new business models, open courseware and systems, personalized/customized learning, platforms, policy, society, teachers, teaching & learning, technologies for your home, tools, UK, United States, universities, workplace, writing, by Daniel Christian

The economic potential of generative AI — from mckinsey.com; via Superhuman

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DC: It should prove to be interesting & fun to watch how #AI and #XR related technologies will be integrated into games & the #gamification of #learning .https://t.co/HO2CftqNrs via @VRScout

— Daniel Christian (he/him/his) (@dchristian5) June 23, 2023

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On giving AI eyes and ears — from oneusefulthing.org by Ethan Mollick
AI can listen and see, with bigger implications than we might realize.

Excerpt:

But even this is just the beginning, and new modes of using AI are appearing, which further increases their capabilities. I want to show you some examples of this emerging world, which I think will soon introduce a new wave of AI use cases, and accompanying disruption.

We need to recognize that these capabilities will continue to grow, and AI will be able to play a more active role in the real world by observing and listening. The implications are likely to be profound, and we should start thinking through both the huge benefits and major concerns today.

Ethan Mollick

5 Steps to Transforming Images into Videos Using AI Tools — from heatherbcooper.substack.com by Heather Cooper
A simple guide to layering AI tools for quick video creation

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‘Nobody wins in an academic-integrity arms race’ — from chonicle.com by Ian Wilhelm
How artificial intelligence is changing the way college thing about cheating

Even though generative AI is a new thing, it doesn’t change why students cheat. They’ve always cheated for the same reason: They don’t find the work meaningful, and they don’t think they can achieve it to their satisfaction. So we need to design assessments that students find meaning in.

Tricia Bertram Gallant

Caught off guard by AI — from chonicle.com by Beth McMurtrie and Beckie Supiano
Professor scrambled to react to ChatGPT this spring — and started planning for the fall

Excerpt:

Is it cheating to use AI to brainstorm, or should that distinction be reserved for writing that you pretend is yours? Should AI be banned from the classroom, or is that irresponsible, given how quickly it is seeping into everyday life? Should a student caught cheating with AI be punished because they passed work off as their own, or given a second chance, especially if different professors have different rules and students aren’t always sure what use is appropriate?

GPT-4 Can Use Tools Now—That’s a Big Deal — from every.to by Dan Shipper; resource via Sam DeBrule
What “function calling” is, how it works, and what it means

Excerpt:

…OpenAI built tool use right into the GPT API with an update called function calling. It’s a little like a child’s ability to ask their parents to help them with a task that they know they can’t do on their own. Except in this case, instead of parents, GPT can call out to external code, databases, or other APIs when it needs to.

Each function in function calling represents a tool that a GPT model can use when necessary, and GPT gets to decide which ones it wants to use and when. This instantly upgrades GPT capabilities—not because it can now do every task perfectly—but because it now knows how to ask for what it wants and get it.
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How ChatGPT can help disrupt assessment overload — from timeshighereducation.com by David Carless
Advances in AI are not necessarily the enemy – in fact, they should prompt long overdue consideration of assessment types and frequency, says David Carless

Excerpt:

Reducing the assessment burden could support trust in students as individuals wanting to produce worthwhile, original work. Indeed, students can be co-opted as partners in designing their own assessment tasks, so they can produce something meaningful to them.

A strategic reduction in quantity of assessment would also facilitate a refocusing of assessment priorities on deep understanding more than just performance and carries potential to enhance feedback processes.

If we were to tackle assessment overload in these ways, it opens up various possibilities. Most significantly there is potential to revitalise feedback so that it becomes a core part of a learning cycle rather than an adjunct at its end. End-of-semester, product-oriented feedback, which comes after grades have already been awarded, fails to encourage the iterative loops and spirals typical of productive learning.
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The full 12 uses are here: https://edgeoflearning.com/your-new-teaching-superpower-ai-tools/

The AI Tools in Education Database — from kiwi-path-612.notion.site by EdTech Insiders

Excerpt (emphasis DSC):

Since AI in education has been moving at the speed of light, we built this AI Tools in Education database to keep track of the most recent AI tools in education and the changes that are happening every day. This database is intended to be a community resource for educators, researchers, students, and other edtech specialists looking to stay up to date. This is a living document, so be sure to come back for regular updates.

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Time for Class 2023 Study finds students are earlier adopters of generative AI tools than faculty, and majority (69%) of learners prefer hybrid, blended or online course formats — from globenewswire.com by Tyton Partners

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AI Could Prevent Hiring Bias — Unless It Makes It Worse — from nerdwallet.com by Anna Helhoski
Advocates say AI can eliminate human biases in hiring. Skeptics point out that AI tools are trained by … humans.

Excerpt:

These claims conjure up the rosiest of images: human resource departments and their robot buddies solving discrimination in workplace hiring. It seems plausible, in theory, that AI could root out unconscious bias, but a growing body of research shows the opposite may be more likely.
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Companies’ use of AI didn’t come out of nowhere: For example, automated applicant tracking systems have been used in hiring for decades. That means if you’ve applied for a job, your resume and cover letter were likely scanned by an automated system. You probably heard from a chatbot at some point in the process. Your interview might have been automatically scheduled and later even assessed by AI.

From DSC:
Here was my reflection on this:

DC: Along these lines, I wonder if Applicant Tracking Systems cause us to become like typecast actors and actresses — only thought of for certain roles. Pigeonholed.

— Daniel Christian (he/him/his) (@dchristian5) June 23, 2023

Also related to AI in hiring, see:

4 in 10 Companies Will Be Using AI Interviews by 2024 — from resumebuilder.com

In June, ResumeBuilder.com surveyed more than 1,000 employees who are involved in hiring processes at their workplaces to find out about their companies’ use of AI interviews.

The results:

43% of companies already have or plan to adopt AI interviews by 2024
Two-thirds of this group believe AI interviews will increase hiring efficiency
15% say that AI will be used to make decisions on candidates without any human input
More than half believe AI will eventually replace human hiring managers

Watch OpenAI CEO Sam Altman on the Future of AI — from bloomberg.com
Sam Altman, CEO & Co-Founder, OpenAI discusses the explosive rise of OpenAI and its products and what an AI-laced future can look like with Bloomberg’s Emily Chang at the Bloomberg Technology Summit.

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PowerSchool Announces Collaboration with Microsoft Azure OpenAI Service to Provide Personalized Learning at Scale in K-12 Education — from powerschool.com
Large-scale language models integrated within PowerSchool Performance Matters and PowerSchool LearningNav products will empower educators in delivering transformative personalized learning pathways

The implementation of generative AI within these products will dramatically improve educators’ ability to deliver personalized learning to students at scale by enabling the application of personalized assessments and learning pathways based on individual student needs and learning goals. K-12 educators will also benefit from access to OpenAI technology…

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FETC 2023 Virtual Roundtable: How AI Will Transform K-12 Education

AI could be the great equalizer!

Holly Clark

Example screenshots:

“2023 Higher Education Trends” [Clark, Cluver, & Selingo] + many other HE-related items

On 05/24/2023, in adjunct faculty, adult learning, blended learning, business side of he, career development, change, changing business models, colleges, community colleges, cost of getting a degree, credentialing, curriculum, experimentation, faculty, future of higher education, game-changing environment, generational differences, higher education, history, hybrid learning, Hyflex learning, leadership, learning ecosystem, Learning Experience Design, learning preferences, liberal arts, lifelong learning, more voice more choice more control, new business models, online learning, parents/guardians, psychology, real-world assignments, reinvent, religion, skills, society, sociology, student-related, surviving, traditional / tradition, trends, United States, universities, workplace, by Daniel Christian

Trend No. 3: The business model faces a full-scale transformation — from www2.deloitte.com by Cole Clark, Megan Cluver, and Jeffrey J. Selingo
The traditional business model of higher education is broken as institutions can no longer rely on rising tuition among traditional students as the primary driver of revenue.

Excerpt:

Yet the opportunities for colleges and universities that shift their business model to a more student-centric one, serving the needs of a wider diversity of learners at different stages of their lives and careers, are immense. Politicians and policymakers are looking for solutions to the demographic cliff facing the workforce and the need to upskill and reskill generations of workers in an economy where the half-life of skills is shrinking. This intersection of needs—higher education needs students; the economy needs skilled workers—means that colleges and universities, if they execute on the right set of strategies, could play a critical role in developing the workforce of the future. For many colleges, this shift will require a significant rethinking of mission and structure as many institutions weren’t designed for workforce development and many faculty don’t believe it’s their job to get students a job. But if a set of institutions prove successful on this front, they could in the process improve the public perception of higher education, potentially leading to more political and financial support for growing this evolving business model in the future.

Also see:

Trend No. 2: The value of the degree undergoes further questioning — from www2.deloitte.com by Cole Clark, Megan Cluver, and Jeffrey J. Selingo
The perceived value of higher education has fallen as the skills needed to keep up in a job constantly change and learners have better consumer information on outcomes.

Excerpt:

Higher education has yet to come to grips with the trade-offs that students and their families are increasingly weighing with regard to obtaining a four-year degree.
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But the problem facing the vast majority of colleges and universities is that they are no longer perceived to be the best source for the skills employers are seeking. This is especially the case as traditional degrees are increasingly competing with a rising tide of microcredentials, industry-based certificates, and well-paying jobs that don’t require a four-year degree.

Trend No. 1: College enrollment reaches its peak — from www2.deloitte.com by Cole Clark, Megan Cluver, and Jeffrey J. Selingo
Enrollment rates in higher education have been declining in the United States over the years as other countries catch up.

Excerpt:

Higher education in the United States has only known growth for generations. But enrollment of traditional students has been falling for more than a decade, especially among men, putting pressure both on the enrollment pipeline and on the work ecosystem it feeds. Now the sector faces increased headwinds as other countries catch up with the aggregate number of college-educated adults, with China and India expected to surpass the United States as the front runners in educated populations within the next decade or so.

Plus the other trends listed here >>

Also related to higher education, see the following items:

Number of Colleges in Distress Is Up 70% From 2012 — from bloomberg.com by Nic Querolo (behind firewall)
More schools see falling enrollement and tuition revenue | Small private, public colleges most at risk, report show

About 75% of students want to attend college — but far fewer expect to actually go — from highereddive.com by Jeremy Bauer-Wolf

There Is No Going Back: College Students Want a Live, Remote Option for In-Person Classes — from campustechnology.com by Eric Paljug

Excerpt:

Based on a survey of college students over the last three semesters, students understand that remotely attending a lecture via remote synchronous technology is less effective for them than attending in person, but they highly value the flexibility of this option of attending when they need it.

Future Prospects and Considerations for AR and VR in Higher Education Academic Technology — from er.educause.edu by Owen McGrath, Chris Hoffman and Shawna Dark
Imagining how the future might unfold, especially for emerging technologies like AR and VR, can help prepare for what does end up happening.

Black Community College Enrollment is Plummeting. How to Get Those Students Back — from the74million.org by Karen A. Stout & Francesca I. Carpenter
Stout & Carpenter: Schools need a new strategy to bolster access for learners of color who no longer see higher education as a viable pathway

As the Level Up coalition reports ,“the vast majority — 80% — of Black Americans believe that college is unaffordable.” This is not surprising given that Black families have fewer assets to pay for college and, as a result, incur significantly more student loan debt than their white or Latino peers. This is true even at the community college level. Only one-third of Black students are able to earn an associate degree without incurring debt.

Repairing Gen Ed | Colleges struggle to help students answer the question, ‘Why am I taking this class?’ — from chronicle.com by Beth McMurtrie
Students Are Disoriented by Gen Ed. So Colleges Are Trying to Fix It.

Excerpts:

Less than 30 percent of college graduates are working in a career closely related to their major, and the average worker has 12 jobs in their lifetime. That means, he says, that undergraduates must learn to be nimble and must build transferable skills. Why can’t those skills and ways of thinking be built into general education?
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“Anyone paying attention to the nonacademic job market,” he writes, “will know that skills, rather than specific majors, are the predominant currency.”

Micro-credentials Survey. 2023 Trends and Insights. — from holoniq.com
HolonIQ’s 2023 global survey on micro-credentials

3 Keys to Making Microcredentials Valid for Learners, Schools, and Employers — from campustechnology.com by Dave McCool
To give credentials value in the workplace, the learning behind them must be sticky, visible, and scalable.

Positive Partnership: Creating Equity in Gateway Course Success — from insidehighered.com by Ashley Mowreader
The Gardner Institute’s Courses and Curricula in Urban Ecosystems initiative works alongside institutions to improve success in general education courses.

American faith in higher education is declining: one poll — from bryanalexander.org by Bryan Alexander

Excerpt:

The main takeaway is that our view of higher education’s value is souring. Fewer of us see post-secondary learning as worth the cost, and now a majority think college and university degrees are no longer worth it: “56% of Americans think earning a four-year degree is a bad bet compared with 42% who retain faith in the credential.”
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Again, this is all about one question in one poll with a small n. But it points to directions higher ed and its national setting are headed in, and we should think hard about how to respond.

Learning Ecosystems

Preparing Students for the AI-Enhanced Workforce [Schroeder] + other AI/learning ecosystems related items

Are your students prepared for active learning? You can help them! [Mihai]

“11 AI Educators to Follow”, “Teaching in the Age of AI,” + numerous other items re: AI in pedagogy

Time will tell whether this statement from Jeff Maggioncalda, Coursera’s CEO, will be the case. [Christian]

“The economic potential of generative AI” [McKinsey & Co.] + using AI in the classroom + other AI-related items

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