Top 6 Use Cases of Generative AI in Education in 2024 — from research.aimultiple.com by Cem Dilmegani

Use cases included:

  1. Personalized Lessons
  2. Course Design
  3. Content Creation for Courses
  4. Data Privacy Protection for Analytical Models
  5. Restoring Old Learning Materials
  6. Tutoring

The Next Phase of AI in Education at the U.S. Department of Education — from medium.com by Office of Ed Tech

Why are we doing this work?
Over the past two years, the U.S. Department of Education has been committed to maintaining an ongoing conversation with educators, students, researchers, developers — and the educational community at large — related to the continuous progress of Artificial Intelligence (AI) development and its implications for teaching and learning.

Many educators are seeking resources clarifying what AI is and how it will impact their work and their students. Similarly, developers of educational technology (“edtech”) products seek guidance on what guardrails exist that can support their efforts. After the release of our May 2023 report Artificial Intelligence and the Future of Teaching and Learningwe heard the desire for more.


2024 EDUCAUSE AI Landscape Study — from library.educause.edu by Jenay Robert

Moving from reaction to action, higher education stakeholders are currently exploring the opportunities afforded by AI for teaching, learning, and work while maintaining a sense of caution for the vast array of risks AI-powered technologies pose. To aid in these efforts, we present this inaugural EDUCAUSE AI Landscape Study, in which we summarize the higher education community’s current sentiments and experiences related to strategic planning and readiness, policies and procedures, workforce, and the future of AI in higher education.


AI Update for K-16 Administrators: More People Need to Step-Up and Take the AI Bull By the Horns — from stefanbauschard.substack.com by Stefan Bauschard
AI capabilities are way beyond what most schools are aware of, and they will transform education and society over the next few years.

Educational administrators should not worry about every AI development, but should, instead focus on the big picture, as those big picture changes will change the entire world and the educational system.

AI and related technologies (robotics, synthetic biology, and brain-computer interfaces) will continue to impact society and the entire educational system over the next 10 years. This impact on the system will be greater than anything that has happened over the last 100 years, including COVID-19, as COVID-19 eventually ended and the disruptive force of these technologies will only continue to develop.

AI is the bull in the China Shop, redefining the world and the educational system. Students writing a paper with AI is barely a poke in the educational world relative to what is starting to happen (active AI teachers and tutors; AI assessment; AI glasses; immersive learning environments; young students able to start their own business with AI tools; AIs replacing and changing jobs; deep voice and video fakes; intelligence leveling; individualized instruction; interactive and highly intelligent computers; computers that can act autonomously; and more).


 

 

Augment teaching with AI – this teacher has it sussed… — from donaldclarkplanb.blogspot.com by Donald Clark

Emphasis (emphasis DSC):

You’re a teacher who wants to integrate AI into your teaching. What do you do? I often get asked how should I start with AI in my school or University. This, I think, is one answer.

Continuity with teaching
One school has got this exactly right in my opinion. Meredith Joy Morris has implemented ChatGPT into the teaching process. The teacher does their thing and the chatbot picks up where the teacher stops, augmenting and scaling the teaching and learning process, passing the baton to the learners who carry on. This gives the learner a more personalised experience, encouraging independent learning by using the undoubted engagement that 1:1 dialogue provides.

There’s no way any teacher can provide this carry on support with even a handful of students, never mind a class of 30 or a course with 100. Teaching here is ‘extended’ and ‘scaled’ by AI. The feedback from the students was extremely positive.


Reflections on Teaching in the AI Age — from by Jeffrey Watson

The transition which AI forces me to make is no longer to evaluate writings, but to evaluate writers. I am accustomed to grading essays impersonally with an objective rubric, treating the text as distinct from the author and commenting only on the features of the text. I need to transition to evaluating students a bit more holistically, as philosophers – to follow along with them in the early stages of the writing process, to ask them to present their ideas orally in conversation or in front of their peers, to push them to develop the intellectual virtues that they will need if they are not going to be mastered by the algorithms seeking to manipulate them. That’s the sort of development I’ve meant to encourage all along, not paragraph construction and citation formatting. If my grading practices incentivize outsourcing to a machine intelligence, I need to change my grading practices.


4 AI Imperatives for Higher Education in 2024 — from campustechnology.com by Rhea Kelly

[Bryan Alexander] There’s a crying need for faculty and staff professional development about generative AI. The topic is complicated and fast moving. Already the people I know who are seriously offering such support are massively overscheduled. Digital materials are popular. Books are lagging but will gradually surface. I hope we see more academics lead more professional development offerings.

For an academic institution to take emerging AI seriously it might have to set up a new body. Present organizational nodes are not necessarily a good fit.


A Technologist Spent Years Building an AI Chatbot Tutor. He Decided It Can’t Be Done. — from edsurge.com by Jeffrey R. Young
Is there a better metaphor than ‘tutor’ for what generative AI can do to help students and teachers?

When Satya Nitta worked at IBM, he and a team of colleagues took on a bold assignment: Use the latest in artificial intelligence to build a new kind of personal digital tutor.

This was before ChatGPT existed, and fewer people were talking about the wonders of AI. But Nitta was working with what was perhaps the highest-profile AI system at the time, IBM’s Watson. That AI tool had pulled off some big wins, including beating humans on the Jeopardy quiz show in 2011.

Nitta says he was optimistic that Watson could power a generalized tutor, but he knew the task would be extremely difficult. “I remember telling IBM top brass that this is going to be a 25-year journey,” he recently told EdSurge.


Teachers stan AI in education–but need more support — from eschoolnews.com by Laura Ascione

What are the advantages of AI in education?
Canva’s study found 78 percent of teachers are interested in using AI education tools, but their experience with the technology remains limited, with 93 percent indicating they know “a little” or “nothing” about it – though this lack of experience hasn’t stopped teachers quickly discovering and considering its benefits:

  • 60 percent of teachers agree it has given them ideas to boost student productivity
  • 59 percent of teachers agree it has cultivated more ways for their students to be creative
  • 56 percent of teachers agree it has made their lives easier

When looking at the ways teachers are already using generative artificial intelligence, the most common uses were:

  • Creating teaching materials (43 percent)
  • Collaborative creativity/co-creation (39 percent)
  • Translating text (36 percent)
  • Brainstorming and generating ideas (35 percent)

The next grand challenge for AI — from ted.com by Jim Fan


The State of Washington Embraces AI for Public Schools — from synthedia.substack.com by Bret Kinsella; via Tom Barrett
Educational institutions may be warming up to generative AI

Washington state issued new guidelines for K-12 public schools last week based on the principle of “embracing a human-centered approach to AI,” which also embraces the use of AI in the education process. The state’s Superintendent of Public Instruction, Chris Reykdal, commented in a letter accompanying the new guidelines:


New education features to help teachers save time and support students — from by Shantanu Sinha

Giving educators time back to invest in themselves and their students
Boost productivity and creativity with Duet AI: Educators can get fresh ideas and save time using generative AI across Workspace apps. With Duet AI, they can get help drafting lesson plans in Docs, creating images in Slides, building project plans in Sheets and more — all with control over their data.

 

The Evolution of Collaboration: Unveiling the EDUCAUSE Corporate Engagement Program — from er.educause.edu

The program is designed to strengthen the collaboration between private industry and higher education institutions—and evolve the higher education technology market. The new program will do so by taking the following actions:

  • Giving higher education professionals better access to corporate thought leaders who can help create change at their institutions
  • Educating corporate partners on the nuances of higher education and the major challenges it faces so that they can help provide meaningful solutions
  • Giving the EDUCAUSE staff and leadership better access to corporate change-makers in order to advocate for change on behalf of our institutional community
  • Providing the institutional community with higher-quality content and services from companies that are deeply invested in the success of higher education
  • Providing the corporate community with custom-built packages that allow more meaningful connections with the institutional community—not only at our in-person events but also through online opportunities year-round

By building better bridges between our corporate and institutional communities, we can help accelerate our shared mission of furthering the promise of higher education.


Speaking of collaborations, also see:

Could the U.S. become an “Apprentice Nation?” — from Michael B. Horn and Ryan Craig

Intermediaries do the heavy lifting for the employers.


Bottom line: As I discussed with Michael later in the show, we already have the varied system that Leonhardt imagines—it’s just that it’s often by chaos and neglect. Just like we didn’t say to 8th graders a century ago, “go find your own high school,” we need to design a post-high school system with clear and well-designed pathways that include:

  1. Apprenticeships outside of the building trades so students can learn a variety of jobs by doing the job.
  2. Short-term certificates that lead to jobs without necessarily having the college degree immediately, but having the option to return for a college degree later on.
  3. Transfer pathways where credits earned in high school really count in college and the move from two-year college to any four-year institution is seamless.

? Listen to the complete episode here and subscribe to the podcast.

 

Nearly half of companies say they plan to eliminate bachelor’s degree requirements in 2024 — from highereddive.com by Carolyn Crist
Many employers are dropping degree requirements to create a more diverse workforce and increase job candidate numbers, survey results show.

Forty-five percent of companies plan to eliminate bachelor’s degree requirements for some positions in 2024, according to a Nov. 29 report from Intelligent.com.

In 2023, 55% of companies removed degree requirements, particularly for entry-level and mid-level roles, the survey shows. Employers said they dropped these requirements to create a more diverse workforce, increase the number of applicants for open positions and because there are other ways to gain skills.


Fitch Ratings issues deteriorating outlook for higher ed in 2024 — from highereddive.com by Natalie Schwartz
The credit ratings agency cited high labor and wage costs, elevated interest rates and uneven enrollment gains across the sector.

Dive Brief:

  • Fitch Ratings issued a deteriorating outlook Monday for U.S. colleges and universities in 2024, citing high labor and wage costs, elevated interest rates and uneven enrollment gains across the sector.
  • These challenges will limit colleges’ financial flexibility next year, according to the credit ratings agency. Moreover, Fitch analysts expect only a 2% to 4% uptick in colleges’ net tuition revenue and said tuition increases likely cannot counter rising operating expenses.
  • The outlook expects the divide to grow between large selective colleges and their smaller, less selective counterparts. “Flagship schools and selective private institutions are expected to experience relatively steady to favorable enrollment, while some regional public institutions and less-selective private schools in competitive markets have experienced declines,” according to the analysis.

Credit rating agencies split on higher ed outlook in 2024 — from highereddive.com by Jeremy Bauer-Wolf
S&P argues economic conditions will stress regional institutions, though Moody’s says the sector is stable overall.

Dive Brief:

  • Two credit rating agencies are somewhat divided in their outlooks for U.S. higher education in 2024, with one arguing the sector has stabilized, while the other forecasts tough economic conditions for less selective, regional colleges.
  • Revenue growth from sources like tuition and state funding looks promising, Moody’s Investors Service argued in an analysis Thursday. S&P Global Ratings, however, said Thursday that only highly selective institutions will enjoy student demand and healthy balance sheets. Their less selective counterparts face enrollment declines and credit pressures in turn, S&P said.
  • Both organizations agreed that labor shortages and similar challenges will squeeze colleges next year. Higher ed is contending with a boom in union activity, while widespread faculty tenure “remains a unique sector risk, limiting budget and operating flexibility,” Moody’s said.

 

 

 

More Chief Online Learning Officers Step Up to Senior Leadership Roles 
In 2024, I think we will see more Chief Online Learning Officers (COLOs) take on more significant roles and projects at institutions.

In recent years, we have seen many COLOs accept provost positions. The typical provost career path that runs up through the faculty ranks does not adequately prepare leaders for the digital transformation occurring in postsecondary education.

As we’ve seen with the professionalization of the COLO role, in general, these same leaders proved to be incredibly valuable during the pandemic due to their unique skills: part academic, part entrepreneur, part technologist, COLOs are unique in higher education. They sit at the epicenter of teaching, learning, technology, and sustainability. As institutions are evolving, look for more online and professional continuing leaders to take on more senior roles on campuses.

Julie Uranis, Senior Vice President, Online and Strategic Initiatives, UPCEA

 

Learning and employment record use cases -- from the National Governors Association

LERs Are Hot. What Are States Going To Do With Them?

Governors and state leaders are concerned about the current labor shortage, occurring during a time when many skilled workers are underemployed or even unemployed. Skills-based approaches to hiring and recruiting can shift that dynamic—making pathways to good careers accessible to a wider segment of the workforce and opening up new pools of talent for employers. They do so by focusing on what workers know and can do, not on the degrees or credentials they’ve earned.

That’s the theory. But a lot hinges on how things actually play out on the ground.

Technology will play a key role, and many states have zeroed in on learning and employment records—essentially digital resumes with verified records of people’s skills, educational experiences, and work histories—as an essential tool. A lot of important work is going into the technical design and specifications.

This project, on the other hand, aims to take a step back and look at the current state of play when it comes to the use cases for LERs. Just a few of the key questions:

  • How might employers, education providers, government agencies, and workers themselves actually use them? Will they?
  • In what areas do state policymakers have the most influence over key stakeholders and the most responsibility to invest?
  • What actions are needed now to ensure that LERs, and skills-based hiring more broadly, actually widen access to good jobs—rather than setting up a parallel system that perpetuates many of today’s inequities?
 

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 — 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
.

 

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
.

Two components of AI -- generative AI and predictive AI

 

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:


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.
 
 

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

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

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

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

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

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

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


Along these lines, also see:


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

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

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

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

 

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’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

Meet Adobe Firefly -- Adobe is going hard with the use of AI. This is a key product along those lines.


Addendums on 10/11/23:


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


 

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

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


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

AI image generators: 10 tools, 10 classroom uses


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

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

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

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


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

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

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

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

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


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

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

 
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