instructional design

The Three Wave Strategy of AI Implementation — from aiczar.blogspot.com by Alexander “Sasha” Sidorkin

The First Wave: Low-Hanging Fruit
…
These are just examples:

Student services
Resume and Cover Letter Review (Career Services)Offering individual resume critiques
Academic Policy Development and Enforcement (Academic Affairs)…
Health Education and Outreach (Health and Wellness Services) …
Sustainability Education and Outreach (Sustainability and Environmental Initiatives) …
Digital Marketing and Social Media Management (University Communications and Marketing) …
Grant Proposal Development and Submission (Research and Innovation) …
Financial Aid Counseling (Financial Aid and Scholarships) …
Alumni Communications (Alumni Relations and Development) …
Scholarly Communications (Library Services) …
International Student and Scholar Services (International Programs and Global Engagement)

Duolingo Max: A Paid Subscription to Learn a Language Using ChatGPT AI (Worth It?) — from theaigirl.substack.com by Diana Dovgopol (behind paywall for the most part)
The integration of AI in language learning apps could be game-changing.

Research Insights #12: Copyrights and Academia — from aiedusimplified.substack.com by Lance Eaton
Scholarly authors are not going to be happy…

A while back, I wrote about some of my thoughts on generative AI around the copyright issues. Not much has changed since then, but a new article (Academic authors ‘shocked’ after Taylor & Francis sells access to their research to Microsoft AI) is definitely stirring up all sorts of concerns by academic authors. The basics of that article are that Taylor & Francis sold access to authors’ research to Microsoft for AI development without informing the authors, sparking significant concern among academics and the Society of Authors about transparency, consent, and the implications for authors’ rights and future earnings.

The stir can be seen as both valid and redundant. Two folks’ points stick out to me in this regard.

“Deep Learning: Five New Superpowers of Higher Education” [Klitgaard] + other items re: AI in our learning ecosystems

On 07/19/2024, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, bots, Canvas - and other Instructure-related items, change, changing business models, CMS/LMS, colleges, community colleges, content development, aggregation, repositories, credentialing, digital learning, education, education technology, emerging technologies, engagement / engaging students, experimentation, future, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, interactivity, IT in HE, K-12 related, languages and translation, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning spaces, liberal arts, Natural Language Processing (NLP), personalized/customized learning, platforms, productivity / tips and tricks, professional development, student-related, teachers, teaching & learning, tools, United States, universities, vendors, vision/possibilities, voice recognition / voice enabled interfaces, by Daniel Christian

What aspects of teaching should remain human? — from hechingerreport.org by Chris Berdik
Even techno optimists hesitate to say teaching is best left to the bots, but there’s a debate about where to draw the line

ATLANTA — Science teacher Daniel Thompson circulated among his sixth graders at Ron Clark Academy on a recent spring morning, spot checking their work and leading them into discussions about the day’s lessons on weather and water. He had a helper: As Thompson paced around the class, peppering them with questions, he frequently turned to a voice-activated AI to summon apps and educational videos onto large-screen smartboards.

When a student asked, “Are there any animals that don’t need water?” Thompson put the question to the AI. Within seconds, an illustrated blurb about kangaroo rats appeared before the class.

Nitta said there’s something “deeply profound” about human communication that allows flesh-and-blood teachers to quickly spot and address things like confusion and flagging interest in real time.

Deep Learning: Five New Superpowers of Higher Education — from jeppestricker.substack.com by Jeppe Klitgaard Stricker
How Deep Learning is Transforming Higher Education

While the traditional model of education is entrenched, emerging technologies like deep learning promise to shake its foundations and usher in an age of personalized, adaptive, and egalitarian education. It is expected to have a significant impact across higher education in several key ways.
…
…deep learning introduces adaptivity into the learning process. Unlike a typical lecture, deep learning systems can observe student performance in real-time. Confusion over a concept triggers instant changes to instructional tactics. Misconceptions are identified early and remediated quickly. Students stay in their zone of proximal development, constantly challenged but never overwhelmed. This adaptivity prevents frustration and stagnation.

InstructureCon 24 Conference Notes — from onedtech.philhillaa.com by Glenda Morgan
Another solid conference from the market leader, even with unclear roadmap

The new stuff: AI
Instructure rolled out multiple updates and improvements – more than last year. These included many AI-based or focused tools and services as well as some functional improvements. I’ll describe the AI features first.

Sal Khan was a surprise visitor to the keynote stage to announce the September availability of the full suite of AI-enabled Khanmigo Teacher Tools for Canvas users. The suite includes 20 tools, such as tools to generate lesson plans and quiz questions and write letters of recommendation. Next year, they plan to roll out tools for students themselves to use.
…
Other AI-based features include.

- Discussion tool summaries and AI-generated responses…
- Translation of inbox messages and discussions…
- Smart search …
- Intelligent Insights…

School 3.0: Reimagining Education in 2026, 2029, and 2034 [Borish]

On 07/19/2024, in 21st century, 24x7x365 access, A/V -- audio/visual, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, education, education technology, emerging technologies, engagement / engaging students, experimentation, face-to-face, flipping -- inverted learning, future, game-changing environment, heutagogy, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, online learning, online media, online tutoring, pace of change, reinvent, skills, staying relevant, teachers, teaching & learning, United States, vision/possibilities, by Daniel Christian

School 3.0: Reimagining Education in 2026, 2029, and 2034 — from davidborish.com by David Borish
.

The landscape of education is on the brink of a profound transformation, driven by rapid advancements in artificial intelligence. This shift was highlighted recently by Andrej Karpathy’s announcement of Eureka Labs, a venture aimed at creating an “AI-native” school. As we look ahead, it’s clear that the integration of AI in education will reshape how we learn, teach, and think about schooling altogether.
…
Traditional textbooks will begin to be replaced by interactive, AI-powered learning materials that adapt in real-time to a student’s progress.
…
As we approach 2029, the line between physical and virtual learning environments will blur significantly.

Curriculum design will become more flexible and personalized, with AI systems suggesting learning pathways based on each student’s interests, strengths, and career aspirations.
…
The boundaries between formal education and professional development will blur, creating a continuous learning ecosystem.

How AI will change education [Woodbury], Introducing Eureka Labs [Karpathy] + numerous other items re: AI in our learning ecosystems

On 07/18/2024, in adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, bots, career development, change, changing business models, colleges, community colleges, computer science, digital learning, education, education technology, emerging technologies, Europe, experimentation, faculty, future, future of higher education, game-changing environment, generational differences, heutagogy, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learning ecosystem, Learning from the Living [Class] Room, lifelong learning, Open AI, platforms, productivity / tips and tricks, professional development, programming, student-related, teachers, teaching & learning, tools, UK, United States, universities, vendors, writing, by Daniel Christian

Introducing Eureka Labs — “We are building a new kind of school that is AI native.” — by Andrej Karpathy, Previously Director of AI @ Tesla, founding team @ OpenAI

However, with recent progress in generative AI, this learning experience feels tractable. The teacher still designs the course materials, but they are supported, leveraged and scaled with an AI Teaching Assistant who is optimized to help guide the students through them. This Teacher + AI symbiosis could run an entire curriculum of courses on a common platform. If we are successful, it will be easy for anyone to learn anything, expanding education in both reach (a large number of people learning something) and extent (any one person learning a large amount of subjects, beyond what may be possible today unassisted).

?? Excited to share that I am starting an AI+Education company called Eureka Labs.
The announcement:

—
We are Eureka Labs and we are building a new kind of school that is AI native.

How can we approach an ideal experience for learning something new? For example, in the case… pic.twitter.com/RHPkqdjB8R

— Andrej Karpathy (@karpathy) July 16, 2024

After Tesla and OpenAI, Andrej Karpathy’s startup aims to apply AI assistants to education — from techcrunch.com by Rebecca Bellan

Andrej Karpathy, former head of AI at Tesla and researcher at OpenAI, is launching Eureka Labs, an “AI native” education platform. In tech speak, that usually means built from the ground up with AI at its core. And while Eureka Labs’ AI ambitions are lofty, the company is starting with a more traditional approach to teaching.

San Francisco-based Eureka Labs, which Karpathy registered as an LLC in Delaware on June 21, aims to leverage recent progress in generative AI to create AI teaching assistants that can guide students through course materials.

What does it mean for students to be AI-ready? — from timeshighereducation.com by David Joyner
Not everyone wants to be a computer scientist, a software engineer or a machine learning developer. We owe it to our students to prepare them with a full range of AI skills for the world they will graduate into, writes David Joyner

We owe it to our students to prepare them for this full range of AI skills, not merely the end points. The best way to fulfil this responsibility is to acknowledge and examine this new category of tools. More and more tools that students use daily – word processors, email, presentation software, development environments and more – have AI-based features. Practising with these tools is a valuable exercise for students, so we should not prohibit that behaviour. But at the same time, we do not have to just shrug our shoulders and accept however much AI assistance students feel like using.

Teachers say AI usage has surged since the school year started — from eschoolnews.com by Laura Ascione
Half of teachers report an increase in the use of AI and continue to seek professional learning

Fifty percent of educators reported an increase in AI usage, by both students and teachers, over the 2023–24 school year, according to The 2024 Educator AI Report: Perceptions, Practices, and Potential, from Imagine Learning, a digital curriculum solutions provider.

The report offers insight into how teachers’ perceptions of AI use in the classroom have evolved since the start of the 2023–24 school year.

OPINION: What teachers call AI cheating, leaders in the workforce might call progress — from hechingerreport.org by C. Edward Waston and Jose Antonio Bowen
Authors of a new guide explore what AI literacy might look like in a new era

Excerpt (emphasis DSC):

But this very ease has teachers wondering how we can keep our students motivated to do the hard work when there are so many new shortcuts. Learning goals, curriculums, courses and the way we grade assignments will all need to be reevaluated.

The new realities of work also must be considered. A shift in employers’ job postings rewards those with AI skills. Many companies report already adopting generative AI tools or anticipate incorporating them into their workflow in the near future.

A core tension has emerged: Many teachers want to keep AI out of our classrooms, but also know that future workplaces may demand AI literacy.

What we call cheating, business could see as efficiency and progress.

It is increasingly likely that using AI will emerge as an essential skill for students, regardless of their career ambitions, and that action is required of educational institutions as a result.

Teaching Writing With AI Without Replacing Thinking: 4 Tips — from by Erik Ofgang
AI has a lot of potential for writing students, but we can’t let it replace the thinking parts of writing, says writing professor Steve Graham

Reconciling these two goals — having AI help students learn to write more efficiently without hijacking the cognitive benefits of writing — should be a key goal of educators. Finding the ideal balance will require more work from both researchers and classroom educators, but Graham shares some initial tips for doing this currently.

Why I ban AI use for writing assignments — from timeshighereducation.com by James Stacey Taylor
Students may see handwriting essays in class as a needlessly time-consuming approach to assignments, but I want them to learn how to engage with arguments, develop their own views and convey them effectively, writes James Stacey Taylor

Could they use AI to generate objections to the arguments they read? Of course. AI does a good job of summarising objections to Singer’s view. But I don’t want students to parrot others’ objections. I want them to think of objections themselves.

Could AI be useful for them in organising their exegesis of others’ views and their criticisms of them? Yes. But, again, part of what I want my students to learn is precisely what this outsources to the AI: how to organise their thoughts and communicate them effectively.

How AI Will Change Education — from digitalnative.tech by Rex Woodbury
Predicting Innovation in Education, from Personalized Learning to the Downfall of College

This week explores how AI will bleed into education, looking at three segments of education worth watching, then examining which business models will prevail.

Personalized Learning and Tutoring
Teacher Tools
Alternatives to College
Final Thoughts: Business Models and Why Education Matters

New Guidance from TeachAI and CSTA Emphasizes Computer Science Education More Important than Ever in an Age of AI — from csteachers.org by CSTA
The guidance features new survey data and insights from teachers and experts in computer science (CS) and AI, informing the future of CS education.

SEATTLE, WA – July 16, 2024 – Today, TeachAI, led by Code.org, ETS, the International Society of Technology in Education (ISTE), Khan Academy, and the World Economic Forum, launches a new initiative in partnership with the Computer Science Teachers Association (CSTA) to support and empower educators as they grapple with the growing opportunities and risks of AI in computer science (CS) education.
…

The briefs draw on early research and insights from CSTA members, organizations in the TeachAI advisory committee, and expert focus groups to address common misconceptions about AI and offer a balanced perspective on critical issues in CS education, including:

Why is it Still Important for Students to Learn to Program?
How Are Computer Science Educators Teaching With and About AI?
How Can Students Become Critical Consumers and Responsible Creators of AI?

How can schools prepare for ADA digital accessibility requirements? — from k12dive.com by Kara Arundel
A new U.S. Department of Justice rule aims to ensure that state and local government web content and mobile apps are accessible for people with disabilities.

A newly issued federal rule to ensure web content and mobile apps are accessible for people with disabilities will require public K-12 and higher education institutions to do a thorough inventory of their digital materials to make sure they are in compliance, accessibility experts said.

The update to regulations for Title II of the Americans with Disabilities Act, published April 24 by the U.S. Department of Justice, calls for all state and local governments to verify that their web content — including mobile apps and social media postings — is accessible for those with vision, hearing, cognitive and manual dexterity disabilities.

Learning Engineering: New Profession or Transformational Process? [Grush & Wagner]

On 07/16/2024, in colleges, community colleges, education, faculty, higher education, instructional design, learning, learning ecosystem, Learning Experience Design, learning spaces, learning theories, research, teachers, teaching & learning, United States, universities, by Daniel Christian

Learning Engineering: New Profession or Transformational Process? A Q&A with Ellen Wagner — from campustechnology.com by Mary Grush and Ellen Wagner

“Learning is one of the most personal things that people do; engineering provides problem-solving methods to enable learning at scale. How do we resolve this paradox?“

—Ellen Wagner

Wagner: Learning engineering offers us a process for figuring that out! If we think of learning engineering as a process that can transform research results into learning action there will be evidence to guide that decision-making at each point in the value chain. I want to get people to think of learning engineering as a process for applying research in practice settings, rather than as a professional identity. And by that I mean that learning engineering is a bigger process than what any one person can do on their own.

From DSC:
Instructional Designers, Learning Experience Designers, Professors, Teachers, and Directors/Staff of Teaching & Learning Centers will be interested in this article. It made me think of the following graphic I created a while back:
.

We need to take more of the research from learning science and apply it in our learning spaces.

“Content can be turned into interactive learning games” [Cheung] + other items re: AI in our LE’s

On 07/11/2024, in 21st century, 24x7x365 access, adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, assessment, Canvas - and other Instructure-related items, CMS/LMS, colleges, community colleges, content development, aggregation, repositories, digital learning, education technology, emerging technologies, experimentation, faculty, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, law schools, learning ecosystem, liberal arts, online media, personalized/customized learning, platforms, student-related, teachers, teaching & learning, tools, United States, universities, vendors, vision/possibilities, by Daniel Christian

Higher Education Has Not Been Forgotten by Generative AI — from insidehighered.com by Ray Schroeder
The generative AI (GenAI) revolution has not ignored higher education; a whole host of tools are available now and more revolutionary tools are on the way.

Some of the apps that have been developed for general use can be customized for specific topical areas in higher ed. For example, I created a version of GPT, “Ray’s EduAI Advisor,” that builds onto the current GPT-4o version with specific updates and perspectives on AI in higher education. It is freely available to users. With few tools and no knowledge of the programming involved, anyone can build their own GPT to supplement information for their classes or interest groups.

Excerpts from Ray’s EduAI Advisor bot:

AI’s global impact on higher education, particularly in at-scale classes and degree programs, is multifaceted, encompassing several key areas:

1. Personalized Learning…

2. Intelligent Tutoring Systems…

3. Automated Assessment…

4. Enhanced Accessibility…

5. Predictive Analytics…

6. Scalable Virtual Classrooms

7. Administrative Efficiency…

8. Continuous Improvement…

Instructure and Khan Academy Announce Partnership to Enhance Teaching and Learning With Khanmigo, the AI Tool for Education — from instructure.com
Shiren Vijiasingam and Jody Sailor make an exciting announcement about a new partnership sure to make a difference in education everywhere.

“Student AI Use Surges, Leaving Faculty Behind” + other items re: AI in our learning ecosystems

On 07/03/2024, in adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, colleges, community colleges, digital video, education, education technology, emerging technologies, experimentation, faculty, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, Microsoft, platforms, presentations, productivity / tips and tricks, professional development, skills, student-related, teachers, teaching & learning, tools, United States, universities, vendors, youth, by Daniel Christian

A New Digital Divide: Student AI Use Surges, Leaving Faculty Behind— from insidehighered.com by Lauren Coffey
While both students and faculty have concerns with generative artificial intelligence, two new reports show a divergence in AI adoption.

Meanwhile, a separate survey of faculty released Thursday by Ithaka S+R, a higher education consulting firm, showcased that faculty—while increasingly familiar with AI—often do not know how to use it in classrooms. Two out of five faculty members are familiar with AI, the Ithaka report found, but only 14 percent said they are confident in their ability to use AI in their teaching. Just slightly more (18 percent) said they understand the teaching implications of generative AI.

“Serious concerns about academic integrity, ethics, accessibility, and educational effectiveness are contributing to this uncertainty and hostility,” the Ithaka report said.

The diverging views about AI are causing friction. Nearly a third of students said they have been warned to not use generative AI by professors, and more than half (59 percent) are concerned they will be accused of cheating with generative AI, according to the Pearson report, which was conducted with Morning Consult and surveyed 800 students.

What teachers want from AI — from hechingerreport.org by Javeria Salman
When teachers designed their own AI tools, they built math assistants, tools for improving student writing, and more

An AI chatbot that walks students through how to solve math problems. An AI instructional coach designed to help English teachers create lesson plans and project ideas. An AI tutor that helps middle and high schoolers become better writers.

These aren’t tools created by education technology companies. They were designed by teachers tasked with using AI to solve a problem their students were experiencing.

Over five weeks this spring, about 300 people – teachers, school and district leaders, higher ed faculty, education consultants and AI researchers – came together to learn how to use AI and develop their own basic AI tools and resources. The professional development opportunity was designed by technology nonprofit Playlab.ai and faculty at the Relay Graduate School of Education.

The Comprehensive List of Talks & Resources for 2024 — from aiedusimplified.substack.com by Lance Eaton
Resources, talks, podcasts, etc that I’ve been a part of in the first half of 2024

Resources from things such as:

Lightning Talks
Talks & Keynotes
Workshops
Podcasts & Panels
Honorable Mentions

Next-Gen Classroom Observations, Powered by AI — from educationnext.org by Michael J. Petrilli
The use of video recordings in classrooms to improve teacher performance is nothing new. But the advent of artificial intelligence could add a helpful evaluative tool for teachers, measuring instructional practice relative to common professional goals with chatbot feedback.

Multiple companies are pairing AI with inexpensive, ubiquitous video technology to provide feedback to educators through asynchronous, offsite observation. It’s an appealing idea, especially given the promise and popularity of instructional coaching, as well as the challenge of scaling it effectively (see “Taking Teacher Coaching To Scale,” research, Fall 2018).
…

Enter AI. Edthena is now offering an “AI Coach” chatbot that offers teachers specific prompts as they privately watch recordings of their lessons. The chatbot is designed to help teachers view their practice relative to common professional goals and to develop action plans to improve.

To be sure, an AI coach is no replacement for human coaching.

Personalized AI Tutoring as a Social Activity: Paradox or Possibility? — from er.educause.edu by Ron Owston
Can the paradox between individual tutoring and social learning be reconciled though the possibility of AI?

We need to shift our thinking about GenAI tutors serving only as personal learning tools. The above activities illustrate how these tools can be integrated into contemporary classroom instruction. The activities should not be seen as prescriptive but merely suggestive of how GenAI can be used to promote social learning. Although I specifically mention only one online activity (“Blended Learning”), all can be adapted to work well in online or blended classes to promote social interaction.

Stealth AI — from higherai.substack.com by Jason Gulya (a Professor of English at Berkeley College) talks to Zack Kinzler
What happens when students use AI all the time, but aren’t allowed to talk about it?

In many ways, this comes back to one of my general rules: You cannot ban AI in the classroom. You can only issue a gag rule.

And if you do issue a gag rule, then it deprives students of the space they often need to make heads and tails of this technology.

We need to listen to actual students talking about actual uses, and reflecting on their actual feelings. No more abstraction.

In this conversation, Jason Gulya (a Professor of English at Berkeley College) talks to Zack Kinzler about what students are saying about Artificial Intelligence and education.

What’s New in Microsoft EDU | ISTE Edition June 2024 — from techcommunity.microsoft.com

Welcome to our monthly update for Teams for Education and thank you so much for being part of our growing community! We’re thrilled to share over 20 updates and resources and show them in action next week at ISTELive 24 in Denver, Colorado, US.
…
Copilot for Microsoft 365 – Educator features
Guided Content Creation
Coming soon to Copilot for Microsoft 365 is a guided content generation experience to help educators get started with creating materials like assignments, lesson plans, lecture slides, and more. The content will be created based on the educator’s requirements with easy ways to customize the content to their exact needs.
Standards alignment and creation
Quiz generation through Copilot in Forms
Suggested AI Feedback for Educators
Teaching extension
To better support educators with their daily tasks, we’ll be launching a built-in Teaching extension to help guide them through relevant activities and provide contextual, educator-based support in Copilot.
Education data integration

Copilot for Microsoft 365 – Student features
Interactive practice experiences
Flashcards activity
Guided chat activity
Learning extension in Copilot for Microsoft 365
…

New AI tools for Google Workspace for Education — from blog.google by Akshay Kirtikar and Brian Hendricks
We’re bringing Gemini to teen students using their school accounts to help them learn responsibly and confidently in an AI-first future, and empowering educators with new tools to help create great learning experiences.

“Anthropic Introduces Claude 3.5 Sonnet” + “Train Students on AI with Claude 3.5” [Clay]

On 06/24/2024, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, computer science, economics, emerging technologies, innovation, instructional design, intelligent systems, journalism, Learning Experience Design, pedagogy, student-related, teachers, teaching & learning, tools, vendors, web design and production, writing, by Daniel Christian

Anthropic Introduces Claude 3.5 Sonnet — from anthropic.com

What’s new?

Frontier intelligence
Claude 3.5 Sonnet sets new industry benchmarks for graduate-level reasoning (GPQA), undergraduate-level knowledge (MMLU), and coding proficiency (HumanEval). It shows marked improvement in grasping nuance, humor, and complex instructions and is exceptional at writing high-quality content with a natural, relatable tone.
2x speed
State-of-the-art vision
Introducing Artifacts—a new way to use Claude
We’re also introducing Artifacts on claude.ai, a new feature that expands how you can interact with Claude. When you ask Claude to generate content like code snippets, text documents, or website designs, these Artifacts appear in a dedicated window alongside your conversation. This creates a dynamic workspace where you can see, edit, and build upon Claude’s creations in real-time, seamlessly integrating AI-generated content into your projects and workflows.

Train Students on AI with Claude 3.5 — from automatedteach.com by Graham Clay
I show how and compare it to GPT-4o.

If you teach computer science, user interface design, or anything involving web development, you can have students prompt Claude to produce web pages’ source code, see this code produced on the right side, preview it after it has compiled, and iterate through code+preview combinations.
If you teach economics, financial analysis, or accounting, you can have students prompt Claude to create analyses of markets or businesses, including interactive infographics, charts, or reports via React. Since it shows its work with Artifacts, your students can see how different prompts result in different statistical analyses, different representations of this information, and more.
If you teach subjects that produce purely textual outputs without a code intermediary, like philosophy, creative writing, or journalism, your students can compare prompting techniques, easily review their work, note common issues, and iterate drafts by comparing versions.

I see this as the first serious step towards improving the otherwise terrible user interfaces of LLMs for broad use. It may turn out to be a small change in the grand scheme of things, but it sure feels like a big improvement — especially in the pedagogical context.

And speaking of training students on AI, also see:

AI Literacy Needs to Include Preparing Students for an Unknown World — from stefanbauschard.substack.com by Stefan Bauschard
Preparing students for it is easier than educators think

Schools could enhance their curricula by incorporating debate, Model UN and mock government programs, business plan competitions, internships and apprenticeships, interdisciplinary and project-based learning initiatives, makerspaces and innovation labs, community service-learning projects, student-run businesses or non-profits, interdisciplinary problem-solving challenges, public speaking, and presentation skills courses, and design thinking workshop.

These programs foster essential skills such as recognizing and addressing complex challenges, collaboration, sound judgment, and decision-making. They also enhance students’ ability to communicate with clarity and precision, while nurturing creativity and critical thinking. By providing hands-on, real-world experiences, these initiatives bridge the gap between theoretical knowledge and practical application, preparing students more effectively for the multifaceted challenges they will face in their future academic and professional lives.

Addendum on 6/28/24:

Collaborate with Claude on Projects — from anthropic.com

Our vision for Claude has always been to create AI systems that work alongside people and meaningfully enhance their workflows. As a step in this direction, Claude.ai Pro and Team users can now organize their chats into Projects, bringing together curated sets of knowledge and chat activity in one place—with the ability to make their best chats with Claude viewable by teammates. With this new functionality, Claude can enable idea generation, more strategic decision-making, and exceptional results.

Projects are available on Claude.ai for all Pro and Team customers, and can be powered by Claude 3.5 Sonnet, our latest release which outperforms its peers on a wide variety of benchmarks. Each project includes a 200K context window, the equivalent of a 500-page book, so users can add all of the relevant documents, code, and insights to enhance Claude’s effectiveness.

Reflections on “The Musician’s Rule and GenAI in Education” [Wiley]

On 06/19/2024, in adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, colleges, community colleges, content development, aggregation, repositories, Daniel S. Christian, education technology, emerging technologies, experimentation, faculty, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, IT in HE, leadership, learning, learning agents, learning ecosystem, Learning Experience Design, learning theories, liberal arts, pace of change, pedagogy, platforms, professional development, research, strategy, teaching & learning, tools, trends, United States, universities, using teams, by Daniel Christian

The Musician’s Rule and GenAI in Education — from opencontent.org by David Wiley

We have to provide instructors the support they need to leverage educational technologies like generative AI effectively in the service of learning. Given the amount of benefit that could accrue to students if powerful tools like generative AI were used effectively by instructors, it seems unethical not to provide instructors with professional development that helps them better understand how learning occurs and what effective teaching looks like. Without more training and support for instructors, the amount of student learning higher education will collectively “leave on the table” will only increase as generative AI gets more and more capable. And that’s a problem.

From DSC:
As is often the case, David put together a solid posting here. A few comments/reflections on it:

I agree that more training/professional development is needed, especially regarding generative AI. This would help achieve a far greater ROI and impact.
The pace of change makes it difficult to see where the sand is settling…and thus what to focus on
The Teaching & Learning Groups out there are also trying to learn and grow in their knowledge (so that they can train others)
The administrators out there are also trying to figure out what all of this generative AI stuff is all about; and so are the faculty members. It takes time for educational technologies’ impact to roll out and be integrated into how people teach.
As we’re talking about multiple disciplines here, I think we need more team-based content creation and delivery.
There needs to be more research on how best to use AI — again, it would be helpful if the sand settled a bit first, so as not to waste time and $$. But then that research needs to be piped into the classrooms far better.
.

We need to take more of the research from learning science and apply it in our learning spaces.

How Learning Designers Are Using AI for Analysis — from drphilippahardman.substack.com by Dr. Philippa Hardman
A practical guide on how to 10X your analysis process using free AI tools, based on real use cases

There are three key areas where AI tools make a significant impact on how we tackle the analysis part of the learning design process:

Understanding the why: what is the problem this learning experience solves? What’s the change we want to see as a result?
Defining the who: who do we need to target in order to solve the problem and achieve the intended goal?
Clarifying the what: given who our learners are and the goal we want to achieve, what concepts and skills do we need to teach?

PROOF POINTS: Teens are looking to AI for information and answers, two surveys show — from hechingerreport.org by Jill Barshay
Rapidly evolving usage patterns show Black, Hispanic and Asian American youth are often quick to adopt the new technology

Two new surveys, both released this month, show how high school and college-age students are embracing artificial intelligence. There are some inconsistencies and many unanswered questions, but what stands out is how much teens are turning to AI for information and to ask questions, not just to do their homework for them. And they’re using it for personal reasons as well as for school. Another big takeaway is that there are different patterns by race and ethnicity with Black, Hispanic and Asian American students often adopting AI faster than white students.

AI Instructional Design Must Be More Than a Time Saver — from marcwatkins.substack.com by Marc Watkins

We’ve ceded so much trust to digital systems already that most simply assume a tool is safe to use with students because a company published it. We don’t check to see if it is compliant with any existing regulations. We don’t ask what powers it. We do not question what happens to our data or our student’s data once we upload it. We likewise don’t know where its information came from or how it came to generate human-like responses. The trust we put into these systems is entirely unearned and uncritical.
…
The allure of these AI tools for teachers is understandable—who doesn’t want to save time on the laborious process of designing lesson plans and materials? But we have to ask ourselves what is lost when we cede the instructional design process to an automated system without critical scrutiny.

From DSC:
I post this to be a balanced publisher of information. I don’t agree with everything Marc says here, but he brings up several solids points.

What does Disruptive Innovation Theory have to say about AI? — from christenseninstitute.org by Michael B. Horn

As news about generative artificial intelligence (GenAI) continually splashes across social media feeds, including how ChatGPT 4o can help you play Rock, Paper, Scissors with a friend, breathtaking pronouncements about GenAI’s “disruptive” impact aren’t hard to find.

It turns out that it doesn’t make much sense to talk about GenAI as being “disruptive” in and of itself.

Can it be part of a disruptive innovation? You bet.

But much more important than just the AI technology in determining whether something is disruptive is the business model in which the AI is used—and its competitive impact on existing products and services in different markets.

On a somewhat note, also see:

National summit explores how digital education can promote deeper learning — from digitaleducation.stanford.edu by Jenny Robinson; via Eric Kunnen on Linkedin.com
The conference, held at Stanford, was organized to help universities imagine how digital innovation can expand their reach, improve learning, and better serve the public good.

The summit was organized around several key questions: “What might learning design, learning technologies, and educational media look like in three, five, or ten years at our institutions? How will blended and digital education be poised to advance equitable, just, and accessible education systems and contribute to the public good? What structures will we need in place for our teams and offices?”

“NYC High School Reimagines Career & Technical Education for the 21st Century” [Bauld] + several other items re: the K12 learning ecosystem

On 06/17/2024, in Bias | Diversity Equity & Inclusion (DE&I), career development, change, changing business models, collaboration, communications, creativity, digital audio, digital video, education, education reform, education technology, engagement / engaging students, engineering, entrepreneurship, experimentation, ideas, innovation, instructional design, journalism, K-12 related, leadership, learning, learning ecosystem, Learning Experience Design, maker movement, media/film, more voice more choice more control, multimedia, play, podcasting, real-world assignments, robotics, skills, society, sociology, special needs, strategy, student-related, teachers, United States, vision/possibilities, vocational / trades, by Daniel Christian

NYC High School Reimagines Career & Technical Education for the 21st Century — from the74million.org by Andrew Bauld
Thomas A. Edison High School is providing students with the skills to succeed in both college and career in an unusually creative way.

From DSC:
Very interesting to see the mention of an R&D department here! Very cool.

Baker said ninth graders in the R&D department designed the essential skills rubric for their grade so that regardless of what content classes students take, they all get the same immersion into critical career skills. Student voice is now so integrated into Edison’s core that teachers work with student designers to plan their units. And he said teachers are becoming comfortable with the language of career-centered learning and essential skills while students appreciate the engagement and develop a new level of confidence.
…
The R&D department has grown to include teachers from every department working with students to figure out how to integrate essential skills into core academic classes. In this way, they’re applying one of the XQ Institute’s crucial Design Principles for innovative high schools: Youth Voice and Choice.
.

Learners need: More voice. More choice. More control. -- this image was created by Daniel Christian

Student Enterprise: Invite Learners to Launch a Media Agency or Publication — from gettingsmart.com by Tom Vander Ark

Key Points

Client-connected projects have become a focal point of the Real World Learning initiative, offering students opportunities to solve real-world problems in collaboration with industry professionals.
Organizations like CAPS, NFTE, and Journalistic Learning facilitate community connections and professional learning opportunities, making it easier to implement client projects and entrepreneurship education.

Important trend: client projects. Work-based learning has been growing with career academies and renewed interest in CTE. Six years ago, a subset of WBL called client-connected projects became a focal point of the Real World Learning initiative in Kansas City where they are defined as authentic problems that students solve in collaboration with professionals from industry, not-for-profit, and community-based organizations….and allow students to: engage directly with employers, address real-world problems, and develop essential skills.

Portrait of a Community to Empower Learning Transformation — from gettingsmart.com by Rebecca Midles and Mason Pashia

Key Points

The Community Portrait approach encourages diverse voices to shape the future of education, ensuring it reflects the needs and aspirations of all stakeholders.
Active, representative community engagement is essential for creating meaningful and inclusive educational environments.

The Portrait of a Graduate—a collaborative effort to define what learners should know and be able to do upon graduation—has likely generated enthusiasm in your community. However, the challenge of future-ready graduates persists: How can we turn this vision into a reality within our diverse and dynamic schools, especially amid the current national political tensions and contentious curriculum debates?

The answer lies in active, inclusive community engagement. It’s about crafting a Community Portrait that reflects the rich diversity of our neighborhoods. This approach, grounded in the same principles used to design effective learning systems, seeks to cultivate deep, reciprocal relationships within the community. When young people are actively involved, the potential for meaningful change increases exponentially.

Q&A: Why Schools Must Redesign Learning to Include All Students — from edtechmagazine.com by Taashi Rowe
Systems are broken, not children, says K–12 disability advocate Lindsay E. Jones.

Although Lindsay E. Jones came from a family of educators, she didn’t expect that going to law school would steer her back into the family business. Over the years she became a staunch advocate for children with disabilities. And as mom to a son with learning disabilities and ADHD who is in high school and doing great, her advocacy is personal.

Jones previously served as president and CEO of the National Center for Learning Disabilities and was senior director for policy and advocacy at the Council for Exceptional Children. Today, she is the CEO at CAST, an organization focused on creating inclusive learning environments in K–12. EdTech: Focus on K–12 spoke with Jones about how digital transformation, artificial intelligence and visionary leaders can support inclusive learning environments.

Our brains are all as different as our fingerprints, and throughout its 40-year history, CAST has been focused on one core value: People are not broken, systems are poorly designed. And those systems are creating a barrier that holds back human innovation and learning.

Daniel Christian: My slides for the Educational Technology Organization of Michigan’s Spring 2024 Retreat

On 06/13/2024, in 21st century, 24x7x365 access, Access to Justice (A2J), adjunct faculty, Adobe, adult learning, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, bots, business side of he, change, cloud-based computing / apps / other cloud-related, colleges, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, cost of getting a degree, creativity, culture, dangers of the status quo, Daniel S. Christian, data related items, design, digital audio, digital learning, digital photography, digital storytelling, digital video, education technology, emerging technologies, experimentation, faculty, future of higher education, game-changing environment, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, library / librarians, lifelong learning, media/film, microlearning, more voice more choice more control, multimedia, Natural Language Processing (NLP), new business models, NVIDIA, online media, online tutoring, Open AI, pace of change, personalized/customized learning, platforms, productivity / tips and tricks, professional development, reinvent, skills, smart/connected TV, society, staying relevant, streams of content, student-related, surviving, teachers, technologies for your home, technology (general), the downsides of how people use tech, tools, training / L&D, United States, universities, user experience (UX), user interface design, vendors, vision/possibilities, web-based collaboration, workplace, by Daniel Christian

From DSC:
Last Thursday, I presented at the Educational Technology Organization of Michigan’s Spring 2024 Retreat. I wanted to pass along my slides to you all, in case they are helpful to you.

Topics/agenda:

Topics & resources re: Artificial Intelligence (AI)
- Top multimodal players
- Resources for learning about AI
- Applications of AI
- My predictions re: AI
The powerful impact of pursuing a vision
A potential, future next-gen learning platform
Share some lessons from my past with pertinent questions for you all now
The significant impact of an organization’s culture
Bonus material: Some people to follow re: learning science and edtech

Slides of the presentation (.PPTX)
Slides of the presentation (.PDF)

Plus several more slides re: this vision.

“6 AI Tools Recommended by Teachers” [Fitzpatrick] + other items re: AI in our learning ecosystems

On 06/12/2024, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, assessment, bots, business, content development, aggregation, repositories, copyright/ownership/NFTs, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, elearning, emerging technologies, engagement / engaging students, experimentation, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning ecosystem, Learning Experience Design, parents/guardians, personalized/customized learning, platforms, productivity / tips and tricks, skills, strategy, student-related, teachers, teaching & learning, technologies for your home, training / L&D, vendors, web-based collaboration, by Daniel Christian

AI Policy 101: a Beginners’ Framework — from drphilippahardman.substack.com by Dr. Philippa Hardman
How to make a case for AI experimentation & testing in learning & development

6 AI Tools Recommended By Teachers That Aren’t ChatGPT — from forbes.com by Dan Fitzpatrick

Here are six AI tools making waves in classrooms worldwide:

Brisk Teaching
SchoolAI
Diffit
Curipod
Skybox by Blockade Labs in ThingLink
Ideogram

With insights from educators who are leveraging their potential, let’s explore them in more detail.

AI Is Speeding Up L&D But Are We Losing the Learning? — from learningguild.com by Danielle Wallace

The role of learning & development
Given these risks, what can L&D professionals do to ensure generative AI contributes to effective learning? The solution lies in embracing the role of trusted learning advisors, guiding the use of AI tools in a way that prioritizes achieving learning outcomes over only speed. Here are three key steps to achieve this:

1. Playtest and Learn About AI…
2. Set the Direction for AI to Be Learner-Centered…
3. Become Trusted Learning Advisors…

Some other tools to explore:

Descript: If you can edit text, you can edit videos. — per Bloomberg’s Vlad Savov
Descript is the AI-powered, fully featured, end-to-end video editor that you already know how to use.

A video editor that works like docs and slides

No need to learn a new tool — Descript works like the tools you’ve already learned.

Audeze | Filter — per Bloomberg’s Vlad Savov

AI Chatbots in Schools Findings from a Poll of K-12 Teachers, Students, Parents, and College Undergraduates — from Impact Research; via Michael Spencer and Lily Lee

Key Findings

In the last year, AI has become even more intertwined with our education system. More teachers, parents, and students are aware of it and have used it themselves on a regular basis. It is all over our education system today.
While negative views of AI have crept up over the last year, students, teachers, and parents feel very positive about it in general. On balance they see positive uses for the technology in school, especially if they have used it themselves.
Most K-12 teachers, parents, and students don’t think their school is doing much about AI, despite its widespread use. Most say their school has no policy on it, is doing nothing to offer desired teacher training, and isn’t meeting the demand of students who’d like a career in a job that will need AI.
The AI vacuum in school policy means it is currently used “unauthorized,” while instead people want policies that encourage AI. Kids, parents, and teachers are figuring it out on their own/without express permission, whereas all stakeholders would rather have a policy that explicitly encourages AI from a thoughtful foundation.

The Value of AI in Today’s Classrooms — from waltonfamilyfoundation.org

There is much discourse about the rise and prevalence of AI in education and beyond. These debates often lack the perspectives of key stakeholders – parents, students and teachers.

In 2023, the Walton Family Foundation commissioned the first national survey of teacher and student attitudes toward ChatGPT. The findings showed that educators and students embrace innovation and are optimistic that AI can meaningfully support traditional instruction.

A new survey conducted May 7-15, 2024, showed that knowledge of and support for AI in education is growing among parents, students and teachers. More than 80% of each group says it has had a positive impact on education.

How Humans Do (and Don’t) Learn [Hardman]

On 06/03/2024, in active learning, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, instructional design, learning, Learning Experience Design, motivation, productivity / tips and tricks, psychology, research, training / L&D, by Daniel Christian

How Humans Do (and Don’t) Learn— from drphilippahardman.substack.com by Dr. Philippa Hardman
One of the biggest ever reviews of human behaviour change has been published, with some eye-opening implications for how we design & deliver learning experiences

Excerpts (emphasis DSC):

This month, researchers from the University of Pennsylvania published one of the biggest ever reviews of behaviour change efforts – i.e. interventions which do (and don’t) lead to behavioural change in humans.
…
Research into human behaviour change suggests that, in order to impact capability in real, measurable terms, we need to rethink how we typically design and deliver training.

The interventions which we use most frequently to behaviour change – such as video + quiz approaches and one off workshops – have a negligible impact on measurable changes in human behaviour.

For learning professionals who want to change how their learners think and behave, this research shows conclusively the central importance of:

1. Shifting attention away from the design of content to the design of context.
2. Delivering sustained cycles of contextualised practice, support & feedback.

Learning Ecosystems

“Scholarly authors are not going to be happy…” [Eaton] + other items re: AI in our learning ecosystems

Learning Engineering: New Profession or Transformational Process? [Grush & Wagner]

Reflections on “The Musician’s Rule and GenAI in Education” [Wiley]

How Humans Do (and Don’t) Learn [Hardman]

Categories

Tags