On the K-12 side of things:

6 Ways to Use ChatGPT to Save Time — from edutopia.org by Todd Finley
Teachers can use the artificial intelligence tool to effectively automate some routine tasks.

Excerpt:

In the paragraphs that follow, I’ve divided these tasks into the following categories: planning instruction, handouts and materials, differentiation, correspondence, assessment, and writing instruction and feedback. Welcome to the revolution.

Lesson plans: Ask ChatGPT to write a lesson plan on, say, Westward Expansion. The tool composes assessments, activities, scaffolding, and objectives. Want that in the form of problem-based learning or revised for a flipped classroom? ChatGPT can adjust the lesson plan according to your instructions. 

I’m a high school math and science teacher who uses ChatGPT, and it’s made my job much easier — from businessinsider-com.cdn.ampproject.org by Aaron Mok; with thanks to Robert Gibson on LinkedIn for this resource

Shannon Ahern teaching her class with the help of a ChatGPT-generated slide. Photo courtesy of Shannon Ahern

Excerpt:

  • Shannon Ahern, a high school math and science teacher, was afraid that ChatGPT would take her job.
  • But her mind changed after she started using the AI for class prep, which saved her hours of time.
  • Here’s how Ahern is using ChatGPT to make her job easier, as told to Insider’s Aaron Mok.

On the higher education side of things:

Using AI to make teaching easier & more impactful — from oneusefulthing.substack.com by Ethan Mollick
Here are five strategies and prompts that work for GPT-3.5 & GPT-4

Excerpt:

But one thing that is not changing is the best way for people to learn. We have made large advances in recent years in understanding pedagogy – the science of learning. We know some of the most effective techniques for making sure material sticks and that it can be retrieved and used when needed most.

Unfortunately, many of these advanced pedagogical techniques are time-consuming to prepare, and many instructors are often overworked and do not have the resources and time to add them to their teaching repertoire. But AI can help. In the rush to deliver AI benefits directly to students, the role of teachers is often overlooked.

Teaching: What You Need to Know About ChatGPT — from chronicle.com by Beth McMurtrie

Excerpt:

Digital literacy is more important than ever. Artificial-intelligence tools, and generative AI in particular, raise a host of ethical, political, economic, and social questions. Plus, this tech is soon going to be everywhere, including students’ future professions. (The technology behind ChatGPT, in fact, just got an upgrade this week.) Colleges need to figure out how to graduate digitally savvy students in all disciplines.

“The integration of technology into our lives is so pervasive that the restriction of education about AI to the computer scientists and the computer engineers makes no more sense than the restriction of taking English classes by English majors,” said Weber.

 

Designing Virtual Edtech Faculty Development Workshops That Stick: 10 Guiding Principles — from er.educause.edu by Tolulope (Tolu) Noah
These ten principles offer guidance on ways to design and facilitate effective and engaging virtual workshops that leave faculty feeling better equipped to implement new edtech tools.

Excerpt:

I share here ten guiding principles that have shaped my design and facilitation of virtual synchronous edtech workshops. These guiding principles are based on lessons learned in both my previous role as a professional learning specialist at a major technology company and my current role as a faculty developer at a university. In the spirit of James M. Lang’s book Small Teaching, my hope is that the principles shared here may prompt reflection on the small yet impactful moves academic technology specialists, instructional designers, and educational developers can make to create virtual learning experiences whereby faculty leave feeling better equipped to implement the edtech tools they have learned.


Somewhat relevant/see:

Evidence-Based Learning Design 101 — by Dr. Philippa Hardman
A practical guide on how to bake the science of learning into the art of course design

Excerpt:

As I reflect on the experience and what I’ve learned so far, I thought I’d share a response to the question I probably get asked most: what process do you use to go from an idea to a designed learning experience?

So, let’s do a rapid review of the four step process I and my bootcamp alumni use – aka the DOMS™? process – to go from zero to a designed learning experience.

 

ChatGPT as a teaching tool, not a cheating tool — from timeshighereducation.com by Jennifer Rose
How to use ChatGPT as a tool to spur students’ inner feedback and thus aid their learning and skills development

Excerpt:

Use ChatGPT to spur student’s inner feedback
One way that ChatGPT answers can be used in class is by asking students to compare what they have written with a ChatGPT answer. This draws on David Nicol’s work on making inner feedback explicit and using comparative judgement. His work demonstrates that in writing down answers to comparative questions students can produce high-quality feedback for themselves which is instant and actionable. Applying this to a ChatGPT answer, the following questions could be used:

  • Which is better, the ChatGPT response or yours? Why?
  • What two points can you learn from the ChatGPT response that will help you improve your work?
  • What can you add from your answer to improve the ChatGPT answer?
  • How could the assignment question set be improved to allow the student to demonstrate higher-order skills such as critical thinking?
  • How can you use what you have learned to stay ahead of AI and produce higher-quality work than ChatGPT?
 

Promoting Student Agency in Learning — from rdene915.com by Rachelle Dené Poth

Excerpts (emphasis DSC):

In many conversations, teachers are starting to shift from what has been a focus on “learning loss” and instead focus on reflecting on the skills that students gained by learning in different yet challenging ways. Some skills such as digital citizenship, how to collaborate and build relationships when not in the classroom together, and essential technology skills. Teachers learned a lot about themselves and the importance of reflecting on their practice. We learned in new ways and now, we have to continue to provide more authentic and meaningful learning experiences for all students.

From DSC:
I couldn’t agree more. There was a different type of learning going on during the pandemic. And that type of learning will be very helpful as our students live the rest of their days in an increasingly Volatile, Uncertain, Complex, and Ambiguous (VOCA) world. That kind of learning wasn’t assessed in our normal standardized tests. It may not have shown up in official transcripts. But it will come in handy in the real world.

When students experience learning that is meaningful, purposeful, and relevant to their lives, it boosts student engagement and amplifies their learning potential, to better prepare students for their future careers.

— Rachelle Dené Poth

 

Using Stories to Support Mathematical Thinking in Young Students — from edutopia.org by Kathleen Crawford-McKinney and Asli Özgün-Koca
Children’s books often contain valuable lessons that can help young students begin to think like mathematicians.

Excerpt:

Many students and teachers view math as a subject for numbers and computation, instead of one that benefits from discussion and interpretation. Based on our experience as children’s literature and mathematics teacher-educators, we’ve found that providing the context to mathematical problems through literature supports students’ learning—children’s books can be used to integrate math and literacy and to provide context for math.

Also from edutopia.org, see:

Things Professional Writers Do That Students Should Too — by Andrew Boryga
Everyone gets stumped when they begin a new writing project—even the professionals. Here are some strategies the world’s best writers use to push past the doldrums and generate higher-quality writing.

Excerpt:

Asking students to read aloud, while focusing on things like tone, sentence structure, and cadence, is a simple, effective, and researched-backed way to improve their writing—particularly during the revision stage.

That insight got us thinking about other easy strategies—used by real pros—that students can also employ to improve their writing.

The Power of a Compliment — by Scott Wisniewski
A project that invites students to anonymously compliment their classmates and teachers has improved the culture at one high school.

Excerpt:

A small act of kindness can change the complexion of someone’s day. Giving someone a compliment, telling them how much they mean to you, or just sharing words of encouragement can change a person’s overall outlook.

 

Some Ideas for Using ChatGPT in Middle and High School Classes — from edutopia.org by Geoff Richman
Teachers can use tools like ChatGPT as one strategy in their efforts to teach students how to think critically and write effectively.

Excerpts:

There can be an upside, however.  In a social studies classroom, students might craft a prompt about a topic they’ve been considering and then examine the machine’s response in forensic detail. This may involve a sentence-by-sentence dissection of what the AI has written. By unearthing possible inconsistencies or straight-up inaccuracies, students reinforce their correct understanding of the topic.

For a playful exercise, share two or three pieces of human writing from the past year or two and slip in an example from ChatGPT, and have students discuss what makes these examples human—or decidedly not. Nuance, passion, and, perhaps, even fallibility will be clues that students can investigate.

 

Does ‘Flipped Learning’ Work? A New Analysis Dives Into the Research — from edsurge.com by Jeffrey R. Young

Excerpt:

The researchers do think that flipped learning has merit — if it is done carefully. They end their paper by presenting a model of flipped learning they refer to as “fail, flip, fix and feed,” which they say applies the most effective aspects they learned from their analysis. Basically they argue that students should be challenged with a problem even if they can’t properly solve it because they haven’t learned the material yet, and then the failure to solve it will motivate them to watch the lecture looking for the necessary information. Then classroom time can be used to fix student misconceptions, with a mix of a short lecture and student activities. Finally, instructors assess the student work and give feedback.

From DSC:
Interesting. I think their “fail, flip, fix and feed” method makes sense.

Also, I do think there’s merit in presenting information ahead of time so that students can *control the pace* of listening/processing/absorbing what’s being relayed. (This is especially helpful for native language differences.) If flipped learning would have been a part of my college experience, it would have freed me from just being a scribe. I could have tried to actually process the information while in class.

 

Podcast Special: Using Generative AI in Education — from drphilippahardman.substack.com by Dr. Philippa Hardman
An exploration of the risks and benefits of Generative AI in education, in conversation with Mike Palmer

Excerpt:

Among other things, we discussed:

  • The immediate challenges that Generative AI presents for learning designers, educators and students.
  • The benefits & opportunities that Generative AI might offer the world of education, both in terms of productivity and pedagogy.
  • How bringing together the world of AI and the world of learning science, we might revolutionise the way we design and deliver learning experiences.

Speaking of podcasts, this article lists some podcasts to check out for those working in — or interested in — higher education.


Also relevant/see:

 


Also relevant/see:

Are librarians the next prompt engineers? — from linkedin.com by Laura Solomon

Excerpt:

  • Without the right prompt, AI fails to provide what someone might be looking for. This probably is a surprise to no one, especially librarians. If you remember the days before Google, you know exactly how this tended to play out. Google became dominant in large part to its inherent ability to accept natural language queries.
  • A small industry is now popping up to provide people with the correct, detailed prompts to get what they want when interacting with AI. The people doing this work are referred to as “prompt engineers.”
  • Prompt engineers aren’t just people who write queries to be directed to an AI. They also have tend to have a great deal of technical expertise and a deep understanding of how artificial intelligences and natural language can intersect.
  • Prompt engineers don’t work for free.

The above item links to The Most Important Job Skill of This Century — from theatlantic.com by Charlie Warzel
Your work future could depend on how well you can talk to AI. 


Also relevant/see:

My class required AI. Here’s what I’ve learned so far. — from oneusefulthing.substack.com by Ethan Mollick
(Spoiler alert: it has been very successful, but there are some lessons to be learned)

Excerpt:

I fully embraced AI for my classes this semester, requiring students to use AI tools in a number of ways. This policy attracted a lot of interest, and I thought it worthwhile to reflect on how it is going so far. The short answer is: great! But I have learned some early lessons that I think are worth passing on.

AI is everywhere already
Even if I didn’t embrace AI, it is also clear that AI is now everywhere in classes. For example, students used it to help them come up with ideas for class projects, even before I even taught them how to do that. As a result, the projects this semester are much better than previous pre-AI classes. This has led to greater project success rates and more engaged teams. On the downside, I find students also raise their hands to ask questions less. I suspect this might be because, as one of them told me, they can later ask ChatGPT to explain things they didn’t get without needing to speak in front of the class. The world of teaching is now more complicated in ways that are exciting, as well as a bit unnerving.

 

Introducing: ChatGPT Edu-Mega-Prompts — from drphilippahardman.substack.com by Dr. Philippa Hardman; with thanks to Ray Schroeder out on LinkedIn for this resource
How to combine the power of AI + learning science to improve your efficiency & effectiveness as an educator

From DSC:
Before relaying some excerpts, I want to say that I get the gist of what Dr. Hardman is saying re: quizzes. But I’m surprised to hear she had so many pedagogical concerns with quizzes. I, too, would like to see quizzes used as an instrument of learning and to practice recall — and not just for assessment. But I would give quizzes a higher thumbs up than what she did. I think she was also trying to say that quizzes don’t always identify misconceptions or inaccurate foundational information. 

Excerpts:

The Bad News: Most AI technologies that have been built specifically for educators in the last few years and months imitate and threaten to spread the use of broken instructional practices (i.e. content + quiz).

The Good News: Armed with prompts which are carefully crafted to ask the right thing in the right way, educators can use AI like GPT3 to improve the effectiveness of their instructional practices.

As is always the case, ChatGPT is your assistant. If you’re not happy with the result, you can edit and refine it using your expertise, either alone or through further conversation with ChatGPT.

For example, once the first response is generated, you can ask ChatGPT to make the activity more or less complex, to change the scenario and/or suggest more or different resources – the options are endless.

Philippa recommended checking out Rob Lennon’s streams of content. Here’s an example from his Twitter account:


Also relevant/see:

3 trends that may unlock AI's potential for Learning and Development in 2023

3 Trends That May Unlock AI’s Potential for L&D in 2023 — from learningguild.com by Juan Naranjo

Excerpts:

AI-assisted design and development work
This is the trend most likely to have a dramatic evolution this year.

Solutions like large language models, speech generators, content generators, image generators, translation tools, transcription tools, and video generators, among many others, will transform the way IDs create the learning experiences our organizations use. Two examples are:

1. IDs will be doing more curation and less creation:

  • Many IDs will start pulling raw material from content generators (built using natural language processing platforms like Open AI’s GPT-3, Microsoft’s LUIS, IBM’s Watson, Google’s BERT, etc.) to obtain ideas and drafts that they can then clean up and add to the assets they are assembling. As technology advances, the output from these platforms will be more suitable to become final drafts, and the curation and clean-up tasks will be faster and easier.
  • Then, the designer can leverage a solution like DALL-E 2 (or a product developed based on it) to obtain visuals that can (or not) be modified with programs like Illustrator or Photoshop (see image below for Dall-E’s “Cubist interpretation of AI and brain science.”

2. IDs will spend less, and in some cases no time at all, creating learning pathways

AI engines contained in LXPs and other platforms will select the right courses for employees and guide these learners from their current level of knowledge and skill to their goal state with substantially less human intervention.

 


The Creator of ChatGPT Thinks AI Should Be Regulated — from time.com by John Simons

Excerpts:

Somehow, Mira Murati can forthrightly discuss the dangers of AI while making you feel like it’s all going to be OK.

A growing number of leaders in the field are warning of the dangers of AI. Do you have any misgivings about the technology?

This is a unique moment in time where we do have agency in how it shapes society. And it goes both ways: the technology shapes us and we shape it. There are a lot of hard problems to figure out. How do you get the model to do the thing that you want it to do, and how you make sure it’s aligned with human intention and ultimately in service of humanity? There are also a ton of questions around societal impact, and there are a lot of ethical and philosophical questions that we need to consider. And it’s important that we bring in different voices, like philosophers, social scientists, artists, and people from the humanities.


Whispers of A.I.’s Modular Future — from newyorker.com by James Somers; via Sam DeBrule

Excerpts:

Gerganov adapted it from a program called Whisper, released in September by OpenAI, the same organization behind ChatGPTand dall-e. Whisper transcribes speech in more than ninety languages. In some of them, the software is capable of superhuman performance—that is, it can actually parse what somebody’s saying better than a human can.

Until recently, world-beating A.I.s like Whisper were the exclusive province of the big tech firms that developed them.

Ever since I’ve had tape to type up—lectures to transcribe, interviews to write down—I’ve dreamed of a program that would do it for me. The transcription process took so long, requiring so many small rewindings, that my hands and back would cramp. As a journalist, knowing what awaited me probably warped my reporting: instead of meeting someone in person with a tape recorder, it often seemed easier just to talk on the phone, typing up the good parts in the moment.

From DSC:
Journalism majors — and even seasoned journalists — should keep an eye on this type of application, as it will save them a significant amount of time and/or money.

Microsoft Teams Premium: Cut costs and add AI-powered productivity — from microsoft.com by Nicole Herskowitz

Excerpt:

Built on the familiar, all-in-one collaborative experience of Microsoft Teams, Teams Premium brings the latest technologies, including Large Language Models powered by OpenAI’s GPT-3.5, to make meetings more intelligent, personalized, and protected—whether it’s one-on-one, large meetings, virtual appointments, or webinars.


 

Best Document Cameras for Teachers — from techlearning.com by Luke Edwards
Get the best document camera for teachers to make the classroom more digitally immersive

Along the lines of edtech, also see:

Tech & Learning Names Winners of the Best of 2022 Awards — from techlearning.com by TL Editors
This annual award celebrates recognizing the very best in EdTech from 2022

.
The Tech & Learning Awards of Excellence: Best of 2022 celebrate educational technology from the last 12 months that has excelled in supporting teachers, students, and education professionals in the classroom, for professional development, or general management of education resources and learning. Nominated products are divided into three categories: Primary, Secondary, or Higher Education.

 

Educator considerations for ChatGPT — from platform.openai.com; with thanks to Anna Mills for this resource

Excerpt:

Streamlined and personalized teaching
Some examples of how we’ve seen educators exploring how to teach and learn with tools like ChatGPT:

  • Drafting and brainstorming for lesson plans and other activities
  • Help with design of quiz questions or other exercises
  • Experimenting with custom tutoring tools
  • Customizing materials for different preferences (simplifying language, adjusting to different reading levels, creating tailored activities for different interests)
  • Providing grammatical or structural feedback on portions of writing
  • Use in upskilling activities in areas like writing and coding (debugging code, revising writing, asking for explanations)
  • Critique AI generated text

While several of the above draw on ChatGPT’s potential to be explored as a tool for personalization, there are risks associated with such personalization as well, including student privacy, biased treatment, and development of unhealthy habits. Before students use tools that offer these services without direct supervision, they and their educators should understand the limitations of the tools outlined below.

Also relevant/see:

Excerpt (emphasis DSC):
David Wiley wrote a thoughtful post on the ways in which AI and Large Language Models (LLMs) can “provide instructional designers with first drafts of some of the work they do.” He says “imagine you’re an instructional designer who’s been paired with a faculty member to create a course in microeconomics. These tools might help you quickly create first drafts of” learning outcomes, discussion prompts, rubrics, and formative assessment items.  The point is that LLMs can quickly generate rough drafts that are mostly accurate drafts, that humans can then “review, augment, and polish,” potentially shifting the work of instructional designers from authors to editors. The post is well worth your time.

The question that I’d like to spend some time thinking about is the following: What new knowledge, capacities, and skills do  instructional designers need in their role as editors and users of LLMs?

This resonated with me. Instructional Designer positions are starting to require AI and ML chops. I’m introducing my grad students to AI and ChatGPT this semester. I have an assignment based on it.

(This ain’t your father’s instructional design…)

Robert Gibson


 

Colleges consider overhauling grading system for freshmen to ease transition to higher learning — from mercurynews.com by Kate Hull
Supporters say ‘ungrading’ could result in less stress and a more level playing field for students from less rigorous high schools  

Excerpt:

Dubbed “weed-out” or “gatekeeper” classes, they can be dream-crushing for many students — especially those hoping to enter the science, technology, engineering and math (STEM) fields. And a growing body of research says the courses can be particularly discriminatory toward historically excluded groups such as Latinos and Black and Indigenous people.

One possible remedy, some educators say, is “ungrading,” a style of teaching and assessment that seeks to evaluate students in other ways besides A-F letter grades — usually just in their freshman year.

“You’re trying to move the focus from a score to the learning,” said Robin Dunkin, who teaches biology and is the assistant faculty director at UCSC’s Center for Innovations in Teaching and Learning.  “For that reason, it’s immensely powerful.”


Also relevant see the #Ungrading hashtag on Twitter, from which the below item was taken:

Excerpts from Jesse Stommel’s Ungrading: an Introduction presentation:

An excerpt from Ungrading - an Introduction by Jesse Stommel

An excerpt from Ungrading - an Introduction by Jesse Stommel

An excerpt from Ungrading - an Introduction by Jesse Stommel


Also relevant/see Robert Talbert’s Grading for Growth.


 

 

Retrieval Practice, Scaffolding, and the Socratic Method — from scholarlyteacher.com by Todd Zakrajsek
Revisit the Socratic method by using it to enact retrieval practice and scaffolding in courses and refresh thinking about applying recommendations from the Scholarship of Teaching and Learning (SOTL)

Excerpt:

When students think they know course material because they have collected reams and reams of information, retrieval practice, much like Socratic questioning, forces students to stop, think, reflect, and reconsider. It meets students where they are (e.g., overwhelmed with information), encourages effortful struggle associated with learning (e.g., presents a desirable difficulty), and offers the discipline of practice (or, perhaps, the practice of discipline). The goal of retrieval practice, getting information out, reflects the goal of so many of Socrates’s questions, to make his interlocutors give an account of and become more aware of their thinking.

When faculty chunk up material, assist students as they move through Bloom’s taxonomy, model approaches to help students get started and maintain momentum, make the student an active participant in developing and reflecting on knowledge, they are incorporating key elements of some of the most important recommendations from the Scholarship of Teaching and Learning. All these techniques help students build or generate knowledge.

 

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

Excerpt:

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

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

 

Some example components of a learning ecosystem [Christian]

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

Some example components:

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

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

 

 
© 2022 | Daniel Christian