liberal arts

Exploring blockchain’s potential impact on the education sector — from e27.co by Moch Akbar Azzihad M
By the year 2024, the application of blockchain technology is anticipated to have a substantial influence on the education sector

Areas mentioned include:

Credentials that are both secure and able to be verified
Records of accomplishments that are not hidden
Enrollment process that is both streamlined and automated
Storage of information that is both secure and decentralised
Financing and decentralised operations

Instructional Designers as Institutional Change Agents [Bond, Lockee, & Blevins]

On 11/27/2023, in change, changing business models, colleges, community colleges, higher education, innovation, instructional design, leadership, learning, learning ecosystem, Learning Experience Design, liberal arts, reinvent, strategy, teaching & learning, United States, universities, by Daniel Christian

Instructional Designers as Institutional Change Agents — from er.educause.edu/ by Aaron Bond, Barb Lockee and Samantha Blevins

Systems thinking and change strategies can be used to improve the overall functioning of a system. Because instructional designers typically use systems thinking to facilitate behavioral changes and improve institutional performance, they are uniquely positioned to be change agents at higher education institutions.

In higher education, instructional designers are often seen as “change agents” because they help to facilitate behavioral changes and improve performance at their institutions. Due to their unique position of influence among higher education leaders and faculty and their use of systems thinking, instructional designers can help bridge institutional priorities and the specific needs of various stakeholders. COVID-19 and the switch to emergency remote teaching raised awareness of the critical services instructional designers provide, including preparing faculty to teach—and students to learn—in well-designed learning environments. Today, higher education institutions increasingly rely on the experience and expertise of instructional designers.

Figure 1. How Instructional Designers Employ Systems Thinking
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“13 Nuggets of AI Wisdom for Higher Education Leaders” [Klitgaard Stricker] + other AI-related items for our learning ecosystems

On 11/10/2023, in 21st century, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, corporate / business world, corporate universities / corporate training, education, education reform, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, IT in HE, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, liberal arts, library / librarians, lifelong learning, Microsoft, platforms, teaching & learning, trends, universities, by Daniel Christian

A future-facing minister, a young inventor and a shared vision: An AI tutor for every student — from news.microsoft.com by Chris Welsch

The Ministry of Education and Pativada see what has become known as the U.A.E. AI Tutor as a way to provide students with 24/7 assistance as well as help level the playing field for those families who cannot afford a private tutor. At the same time, the AI Tutor would be an aid to teachers, they say. “We see it as a tool that will support our teachers,” says Aljughaiman. “This is a supplement to classroom learning.”

If everything goes according to plan, every student in the United Arab Emirates’ school system will have a personal AI tutor – that fits in their pockets.

It’s a story that involves an element of coincidence, a forward-looking education minister and a tech team led by a chief executive officer who still lives at home with his parents.

In February 2023, the U.A.E.’s education minister, His Excellency Dr. Ahmad Belhoul Al Falasi, announced that the ministry was embracing AI technology and pursuing the idea of an AI tutor to help Emirati students succeed. And he also announced that the speech he presented had been written by ChatGPT. “We should not demonize AI,” he said at the time.

Fostering deep learning in humans and amplifying our intelligence in an AI World — from stefanbauschard.substack.com by Stefan Bauschard
A free 288-page report on advancements in AI and related technology, their effects on education, and our practical support for AI-amplified human deep learning

Six weeks ago, Dr. Sabba Quidwai and I accidentally stumbled upon an idea to compare the deep learning revolution in computer science to the mostly lacking deep learning efforts in education (Mehta & Fine). I started writing, and as these things often go with me, I thought there were many other things that would be useful to think through and for educators to know, and we ended up with this 288-page report.

***

Here’s an abstract from that report:

This report looks at the growing gap between the attention paid to the development of intelligence in machines and humans. While computer scientists have made great strides in developing human intelligence capacities in machines using deep learning technologies, including the abilities of machines to learn on their own, a significant part of the education system has not kept up with developing the intelligence capabilities in people that will enable them to succeed in the 21st century. Instead of fully embracing pedagogical methods that place primary emphasis on promoting collaboration, critical thinking, communication, creativity, and self-learning through experiential, interdisciplinary approaches grounded in human deep learning and combined with current technologies, a substantial portion of the educational system continues to heavily rely on traditional instructional methods and goals. These methods and goals prioritize knowledge acquisition and organization, areas in which machines already perform substantially better than people.

Also from Stefan Bauschard, see:

Debating in the World of AI
Performative assessment, learning to collaborate with humans and machines, and developing special human qualities

13 Nuggets of AI Wisdom for Higher Education Leaders — from jeppestricker.substack.com by Jeppe Klitgaard Stricker
Actionable AI Guidance for Higher Education Leaders

Incentivize faculty AI innovation with AI.

Invest in people first, then technology.

On teaching, learning, and assessment. AI has captured the attention of all institutional stakeholders. Capitalize to reimagine pedagogy and evaluation. Rethink lectures, examinations, and assignments to align with workforce needs. Consider incorporating Problem-Based Learning, building portfolios and proof of work, and conducting oral exams. And use AI to provide individualized support and assess real-world skills.

Actively engage students.

Some thoughts from George Siemens re: AI:

Sensemaking, AI, and Learning (SAIL), a regular look at how AI is impacting learning.

Our education system has a uni-dimensional focus: learning things. Of course, we say we care about developing the whole learner, but the metrics that matter (grade, transcripts) that underpin the education system are largely focused on teaching students things that have long been Google-able but are now increasingly doable by AI. Developments in AI matters in ways that calls into question large parts of what happens in our universities. This is not a statement that people don’t need to learn core concepts and skills. My point is that the fulcrum of learning has shifted. Knowing things will continue to matter less and less going forward as AI improves its capabilities. We’ll need to start intentionally developing broader and broader attributes of learners: metacognition, wellness, affect, social engagement, etc. Education will continue to shift toward human skills and away from primary assessment of knowledge gains disconnected from skills and practice and ways of being.

AI, the Next Chapter for College Librarians — from insidehighered.com by Lauren Coffey
Librarians have lived through the disruptions of fax machines, websites and Wikipedia, and now they are bracing to do it again as artificial intelligence tools go mainstream: “Maybe it’s our time to shine.”

A few months after ChatGPT launched last fall, faculty and students at Northwestern University had many questions about the building wave of new artificial intelligence tools. So they turned to a familiar source of help: the library.

“At the time it was seen as a research and citation problem, so that led them to us,” said Michelle Guittar, head of instruction and curriculum support at Northwestern University Libraries.

In response, Guittar, along with librarian Jeanette Moss, created a landing page in April, “Using AI Tools in Your Research.” At the time, the university itself had yet to put together a comprehensive resource page.

From Dr. Nick Jackson’s recent post on LinkedIn:

Last night the Digitech team of junior and senior teachers from Scotch College Adelaide showcased their 2023 experiments, innovation, successes and failures with technology in education. Accompanied by Student digital leaders, we saw the following:

AI used for languagelearning where avatars can help with accents
Motioncapture suits being used in mediastudies
AI used in assessment and automatic grading of work
AR used in designtechnology
VR used for immersive Junior school experiences
A teacher’s AI toolkit that has changed teaching practice and workflow
AR and the EyeJack app used by students to create dynamic art work
VR use in careers education in Senior school
How ethics around AI is taught to Junior school students from Year 1
Experiments with MyStudyWorks

Almost an Agent: What GPTs can do — from oneusefulthing.org by Ethan Mollick

What would a real AI agent look like? A simple agent that writes academic papers would, after being given a dataset and a field of study, read about how to compose a good paper, analyze the data, conduct a literature review, generate hypotheses, test them, and then write up the results, all without intervention. You put in a request, you get a Word document that contains a draft of an academic paper.

A process kind of like this one:

What I Learned From an Experiment to Apply Generative AI to My Data Course — from edsurge.com by Wendy Castillo

As an educator, I have a duty to remain informed about the latest developments in generative AI, not only to ensure learning is happening, but to stay on top of what tools exist, what benefits and limitations they have, and most importantly, how students might be using them.

However, it’s also important to acknowledge that the quality of work produced by students now requires higher expectations and potential adjustments to grading practices. The baseline is no longer zero, it is AI. And the upper limit of what humans can achieve with these new capabilities remains an unknown frontier.

Artificial Intelligence in Higher Education: Trick or Treat? — from tytonpartners.com by Kristen Fox and Catherine Shaw
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Two items from the Teaching newsletter out at the Chronicle of Higher Education

On 11/10/2023, in 21st century, adjunct faculty, change, changing business models, collaboration, colleges, communities of practice, community colleges, digital audio, digital learning, digital video, distance education, education technology, engagement / engaging students, experimentation, faculty/staff, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), innovation, instructional design, internet, IT in HE, law schools, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, liberal arts, multimedia, new business models, new media literacies, online learning, online media, online tutoring, platforms, teaching & learning, teaching online, technologies for your home, telecommunications, tools, United States, universities, vendors, videoconferencing, by Daniel Christian

What happens to teaching after Covid? — from chronicle.com by Beth McMurtrie

It’s an era many instructors would like to put behind them: black boxes on Zoom screens, muffled discussions behind masks, students struggling to stay engaged. But how much more challenging would teaching during the pandemic have been if colleges did not have experts on staff to help with the transition? On many campuses, teaching-center directors, instructional designers, educational technologists, and others worked alongside professors to explore learning-management systems, master video technology, and rethink what and how they teach.

A new book out this month, Higher Education Beyond Covid: New Teaching Paradigms and Promise, explores this period through the stories of campus teaching and learning centers. Their experiences reflect successes and failures, and what higher education could learn as it plans for the future.

Beth also mentioned/link to:

Centers for Teaching and Learning: The New Landscape in Higher Education by Mary C. Wright

How to hold difficult discussions online — from chronicle.com by Beckie Supiano

As usual, our readers were full of suggestions. Kathryn Schild, the lead instructional designer in faculty development and instructional support at the University of Alaska at Anchorage, shared a guide she’s compiled on holding asynchronous discussions, which includes a section on difficult topics.

In an email, Schild also pulled out a few ideas she thought were particularly relevant to Le’s question, including:

Set the ground rules as a class. One way to do this is to share your draft rules in a collaborative document and ask students to annotate it and add suggestions.
Plan to hold fewer difficult discussions than in a face-to-face class, and work on quality over quantity. This could include multiweek discussions, where you spiral through the same issue with fresh perspectives as the class learns new approaches.
Start with relationship-building interactions in the first few weeks, such as introductions, low-stakes group assignments, or peer feedback, etc.

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/staff, 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/Agents/LLMs/and Related, 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/staff, 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/Agents/LLMs/and Related, 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/staff, 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.
.

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.

Learning Ecosystems

Instructional Designers as Institutional Change Agents [Bond, Lockee, & Blevins]

Two items from the Teaching newsletter out at the Chronicle of Higher Education

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

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

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