instructional design

14+ resources regarding AI in our learning ecosystems

On 08/13/2024, in adjunct faculty, adult learning, Australia, CMS/LMS, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education technology, elearning, emerging technologies, experimentation, faculty/staff, Google, heutagogy, higher education, human-computer interaction (HCI), ideas, instructional design, intelligent systems, IT in HE, K-12 related, law schools, leadership, learning, learning ecosystem, Learning Experience Design, learning theories, lifelong learning, Microsoft, multimedia, Open AI, platforms, policy, productivity / tips and tricks, religion, strategy, student-related, teachers, teaching & learning, tools, training / L&D, United States, universities, vendors, by Daniel Christian

What Students Want When It Comes To AI — from onedtech.philhillaa.com by Glenda Morgan
The Digital Education Council Global AI Student Survey 2024

The Digital Education Council (DEC) this week released the results of a global survey of student opinions on AI. It’s a large survey with nearly 4,000 respondents conducted across 16 countries, but more importantly, it asks some interesting questions. There are many surveys about AI out there right now, but this one stands out. I’m going to go into some depth here, as the entire survey report is worth reading.

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AI is forcing a teaching and learning evolution — from eschoolnews.com by Laura Ascione
AI and technology tools are leading to innovative student learning–along with classroom, school, and district efficiency

Key findings from the 2024 K-12 Educator + AI Survey, which was conducted by Hanover Research, include:

Teachers are using AI to personalize and improve student learning, not just run classrooms more efficiently, but challenges remain
While post-pandemic challenges persist, the increased use of technology is viewed positively by most teachers and administrators
…and more

From DSC:
I wonder…how will the use of AI in education square with the issues of using smartphones/laptops within the classrooms? See:

Why Schools Are Racing to Ban Student Phones — from nytimes.com by Natasha Singer; via GSV
As the new school year starts, a wave of new laws that aim to curb distracted learning is taking effect in Indiana, Louisiana and other states.

A three-part series from Dr. Phillippa Hardman:

Part 1: Writing Learning Objectives
The Results Part 1: Writing Learning Objectives

In this week’s post I will dive into the results from task 1: writing learning objectives. Stay tuned over the next two weeks to see all of the the results.

Part 2: Selecting Instructional Strategies.
The Results Part 2: Selecting an Instructional Strategy

Welcome back to our three-part series exploring the impact of AI on instructional design.
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This week, we’re tackling a second task and a crucial aspect of instructional design: selecting instructional strategies. The ability to select appropriate instructional strategies to achieve intended objectives is a mission-critical skill for any instructional designer. So, can AI help us do a good job of it? Let’s find out!

Part 3: How Close is AI to Replacing Instructional Designers?
The Results Part 3: Creating a Course Outline

Today, we’re diving into what many consider to be the role-defining task of the instructional designer: creating a course design outline.

ChatGPT Cheat Sheet for Instructional Designers! — from Alexandra Choy Youatt EdD

Instructional Designers!
Whether you’re new to the field or a seasoned expert, this comprehensive guide will help you leverage AI to create more engaging and effective learning experiences.

What’s Inside?
Roles and Tasks: Tailored prompts for various instructional design roles and tasks.
Formats: Different formats to present your work, from training plans to rubrics.
Learning Models: Guidance on using the ADDIE model and various pedagogical strategies.
Engagement Tips: Techniques for online engagement and collaboration.
Specific Tips: Industry certifications, work-based learning, safety protocols, and more.

Who Can Benefit?
Corporate Trainers
Curriculum Developers
E-Learning Specialists
Instructional Technologists
Learning Experience Designers
And many more!
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ChatGPT Cheat Sheet | Instructional Designer

5 AI Tools I Use Every Day (as a Busy Student) — from theaigirl.substack.com by Diana Dovgopol
AI tools that I use every day to boost my productivity.
#1 Gamma
#2 Perplexity
#3 Cockatoo

I use this AI tool almost every day as well. Since I’m still a master’s student at university, I have to attend lectures and seminars, which are always in English or German, neither of which is my native language. With the help of Cockatoo, I create scripts of the lectures and/or translations into my language. This means I don’t have to take notes in class and then manually translate them afterward. All I need to do is record the lecture audio on any device or directly in Cockatoo, upload it, and then you’ll have the audio and text ready for you.

…and more

Students Worry Overemphasis on AI Could Devalue Education — from insidehighered.com by Juliette Rowsell
Report stresses that AI is “new standard” and universities need to better communicate policies to learners.

Rising use of AI in higher education could cause students to question the quality and value of education they receive, a report warns.

This year’s Digital Education Council Global AI Student Survey, of more than 3,800 students from 16 countries, found that more than half (55 percent) believed overuse of AI within teaching devalued education, and 52 percent said it negatively impacted their academic performance.

Despite this, significant numbers of students admitted to using such technology. Some 86 percent said they “regularly” used programs such as ChatGPT in their studies, 54 percent said they used it on a weekly basis, and 24 percent said they used it to write a first draft of a submission.

Higher Ed Leadership Is Excited About AI – But Investment Is Lacking — from forbes.com by Vinay Bhaskara

As corporate America races to integrate AI into its core operations, higher education finds itself in a precarious position. I conducted a survey of 63 university leaders revealing that while higher ed leaders recognize AI’s transformative potential, they’re struggling to turn that recognition into action.

This struggle is familiar for higher education — gifted with the mission of educating America’s youth but plagued with a myriad of operational and financial struggles, higher ed institutions often lag behind their corporate peers in technology adoption. In recent years, this gap has become threateningly large. In an era of declining enrollments and shifting demographics, closing this gap could be key to institutional survival and success.

The survey results paint a clear picture of inconsistency: 86% of higher ed leaders see AI as a “massive opportunity,” yet only 21% believe their institutions are prepared for it. This disconnect isn’t just a minor inconsistency – it’s a strategic vulnerability in an era of declining enrollments and shifting demographics.

(Generative) AI Isn’t Going Anywhere but Up — from stefanbauschard.substack.com by Stefan Bauschard
“Hype” claims are nonsense.

There has been a lot of talk recently about an “AI Bubble.” Supposedly, the industry, or at least the generative AI subset of it, will collapse. This is known as the “Generative AI Bubble.” A bubble — a broad one or a generative one — is nonsense. These are the reasons we will continue to see massive growth in AI.

AI Readiness: Prepare Your Workforce to Embrace the Future — from learningguild.com by Danielle Wallace

Artificial Intelligence (AI) is revolutionizing industries, enhancing efficiency, and unlocking new opportunities. To thrive in this landscape, organizations need to be ready to embrace AI not just technologically but also culturally.

Learning leaders play a crucial role in preparing employees to adapt and excel in an AI-driven workplace. Transforming into an AI-empowered organization requires more than just technological adoption; it demands a shift in organizational mindset. This guide delves into how learning leaders can support this transition by fostering the right mindset attributes in employees.

Claude AI for eLearning Developers — from learningguild.com by Bill Brandon

Claude is fast, produces grammatically correct text, and outputs easy-to-read articles, emails, blog posts, summaries, and analyses. Take some time to try it out. If you worry about plagiarism and text scraping, put the results through Grammarly’s plagiarism checker (I did not use Claude for this article, but I did send the text through Grammarly).

Survey: Top Teacher Uses of AI in the Classroom — from thejournal.com by Rhea Kelly

A new report from Cambium Learning Group outlines the top ways educators are using artificial intelligence to manage their classrooms and support student learning. Conducted by Hanover Research, the 2024 K-12 Educator + AI Survey polled 482 teachers and administrators at schools and districts that are actively using AI in the classroom.

More than half of survey respondents (56%) reported that they are leveraging AI to create personalized learning experiences for students. Other uses included providing real-time performance tracking and feedback (cited by 52% of respondents), helping students with critical thinking skills (50%), proofreading writing (47%), and lesson planning (44%).

On the administrator side, top uses of AI included interpreting/analyzing student data (61%), managing student records (56%), and managing professional development (56%).

Addendum on 8/14/24:

Digital Writing Lab

About this Project

The Digital Writing Lab is a key component of the Australian national Teaching Digital Writing project, which runs from 2022-2025.

This stage of the broader project involves academic and secondary English teacher collaboration to explore how teachers are conceptualising the teaching of digital writing and what further supports they may need.

Previous stages of the project included archival research reviewing materials related to digital writing in Australia’s National Textbook Collection, and a national survey of secondary English teachers. You can find out more about the whole project via the project blog.

Who runs the project?

Project Lead Lucinda McKnight is an Associate Professor and Australian Research Council (ARC) DECRA Fellow researching how English teachers can connect the teaching of writing to contemporary media and students’ lifeworlds.

She is working with Leon Furze, who holds the doctoral scholarship attached to this project, and Chris Zomer, the project Research Fellow. The project is located in the Research for Educational Impact (REDI) centre at Deakin University, Melbourne.

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Using Class Discussions as AI-Proof Assessments [McPhillips]

On 08/05/2024, in Artificial Intelligence/Agents/LLMs/and Related, assessment, collaboration, communications, education, education technology, ideas, instructional design, K-12 related, learning, learning ecosystem, Learning Experience Design, participation, pedagogy, teachers, youth, by Daniel Christian

Using Class Discussions as AI-Proof Assessments — from edutopia.org by Kara McPhillips
Classroom discussions are one way to ensure that students are doing their own work in the age of artificial intelligence.

I admit it: Grading essays has never topped my list of teaching joys. Sure, the moments when a student finally nails a skill after months of hard work make me shout for joy, startling my nearby colleagues (sorry, Ms. Evans), but by and large, it’s hard work. Yet lately, as generative artificial intelligence (AI) headlines swirl in my mind, a new anxiety has crept into my grading life. I increasingly wonder, am I looking at their hard work?

Do you know when I don’t feel this way? During discussions. A ninth grader wiggling the worn corner of her text, leaning forward with excitement over what she’s cleverly noticed about Kambili, rarely makes me wonder, “Are these her ideas?”

While I’ve always thought discussion is important, AI is elevating that importance. This year, I wonder, how can I best leverage discussion in my classroom?

How to Set Up District-Wide Choice-Based Professional Development [Kersznowski]

On 08/05/2024, in innovation, instructional design, learning ecosystem, Learning Experience Design, more voice more choice more control, platforms, productivity / tips and tricks, professional development, teachers, teaching & learning, United States, by Daniel Christian

How to Set Up District-Wide Choice-Based Professional Development — from edutopia.org by Kathi Kersznowski
This district reimagined PD by tapping interested teachers to guide PD sessions on new software, creating a model that can be used for smaller initiatives as well.

As an edtech coach, I constantly seek innovative ways to deliver impactful professional development (PD), and when our district decided to transition from Microsoft to Google, I saw an opportunity to reimagine our approach to PD. My team of edtech specialists, plus our administrators and I.T. department, and I created Google Day, setting up a transformative model that engaged our entire staff and created lasting impact.

While our focus was a major platform change, this model can be adapted for any professional development topics or district-wide rollouts. Whether you‘re introducing a new curriculum or teaching strategies or starting any other initiative, the principles we applied can help you create a dynamic, effective PD experience.

The key elements—leveraging in-house expertise, offering choice in sessions, and creating a lasting set of resources—can be applied to virtually any PD need.

“For college students—and for higher ed itself—AI is a required course” [Merisotis] + other items re: AI in our learning ecosystems

On 08/03/2024, in 21st century, 24x7x365 access, accessibility / UDL, adjunct faculty, apprenticeships, Artificial Intelligence/Agents/LLMs/and Related, Bias | Diversity Equity & Inclusion (DE&I), bots, career development, colleges, community colleges, content development, aggregation, repositories, copyright/ownership/NFTs, education, education technology, emerging technologies, faculty/staff, future, future of higher education, game-changing environment, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, platforms, productivity / tips and tricks, real-world assignments, reinvent, skills, student-related, teachers, teaching & learning, teaching online, technologies for your home, technology (general), tools, trends, United States, universities, vendors, vision/possibilities, workplace, youth, by Daniel Christian

For college students—and for higher ed itself—AI is a required course — from forbes.com by Jamie Merisotis

Some of the nation’s biggest tech companies have announced efforts to reskill people to avoid job losses caused by artificial intelligence, even as they work to perfect the technology that could eliminate millions of those jobs.

It’s fair to ask, however: What should college students and prospective students, weighing their choices and possible time and financial expenses, think of this?

The news this spring was encouraging for people seeking to reinvent their careers to grab middle-class jobs and a shot at economic security.

Addressing Special Education Needs With Custom AI Solutions — from teachthought.com
AI can offer many opportunities to create more inclusive and effective learning experiences for students with diverse learning profiles.

For too long, students with learning disabilities have struggled to navigate a traditional education system that often fails to meet their unique needs. But what if technology could help bridge the gap, offering personalized support and unlocking the full potential of every learner?

Artificial intelligence (AI) is emerging as a powerful ally in special education, offering many opportunities to create more inclusive and effective learning experiences for students with diverse learning profiles.

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11 Summer AI Developments Important to Educators — from stefanbauschard.substack.com by Stefan Bauschard
Equity demands that we help students prepare to thrive in an AI-World

*SearchGPT
*Smaller & on-device (phones, glasses) AI models
*AI TAs
*Access barriers decline, equity barriers grow
*Claude Artifacts and Projects
*Agents, and Agent Teams of a million+
*Humanoid robots & self-driving cars
*AI Curricular integration
*Huge video and video-segmentation gains
*Writing Detectors — The final blow
*AI Unemployment, Student AI anxiety, and forward-thinking approaches
*Alternative assessments

Academic Fracking: When Publishers Sell Scholars Work to AI — from aiedusimplified.substack.com by Lance Eaton
Further discussion of publisher practices selling scholars’ work to AI companies

Last week, I explored AI and academic publishing in response to an article that came out a few weeks ago about a deal Taylor & Francis made to sell their books to Microsoft and one other AI company (unnamed) for a boatload of money.

Since then, two more pieces have been widely shared including this piece from Inside Higher Ed by Kathryn Palmer (and to which I was interviewed and mentioned in) and this piece from Chronicle of Higher Ed by Christa Dutton. Both pieces try to cover the different sides talking to authors, scanning the commentary online, finding some experts to consult and talking to the publishers. It’s one of those things that can feel like really important and also probably only to a very small amount of folks that find themselves thinking about academic publishing, scholarly communication, and generative AI.

At the Crossroads of Innovation: Embracing AI to Foster Deep Learning in the College Classroom — from er.educause.edu by Dan Sarofian-Butin
AI is here to stay. How can we, as educators, accept this change and use it to help our students learn?

The Way Forward
So now what?

In one respect, we already have a partial answer. Over the last thirty years, there has been a dramatic shift from a teaching-centered to a learning-centered education model. High-impact practices, such as service learning, undergraduate research, and living-learning communities, are common and embraced because they help students see the real-world connections of what they are learning and make learning personal.11

Therefore, I believe we must double down on a learning-centered model in the age of AI.

The first step is to fully and enthusiastically embrace AI.
…
The second step is to find the “jagged technological frontier” of using AI in the college classroom.

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Futures Thinking in Education — from gettingsmart.com by Getting Smart Staff

Key Points

Educators should leverage these tools to prepare for rapid changes driven by technology, climate, and social dynamics.
Cultivating empathy for future generations can help educators design more impactful and forward-thinking educational practices.

Virtual Coaching Videos: Answering Your Questions [Tucker]

On 08/01/2024, in blended learning, content development, aggregation, repositories, digital learning, education, education technology, hybrid learning, instructional design, K-12 related, learning, learning ecosystem, Learning Experience Design, more voice more choice more control, online media, student-related, teachers, United States, web-based collaboration, by Daniel Christian

Virtual Coaching Videos: Answering Your Questions — from catlintucker.com by Catlin Tucker
(Emphasis below by DSC — and I would like to thank Catlin and people like her who are sharing their knowledge — free of charge — as they help others learn and grow!)

I am excited to announce the launch of a new video series on YouTube called “Virtual Coaching.” I have the privilege of working with thousands of educators every year who are expanding their teaching toolboxes to include blended learning models, UDL, and student-led instructional strategies. I understand how challenging it can be to shift practice. I encourage the educators I work with to reach out if they hit bumps, have questions, or need support as they implement new instructional models. Every year, I field hundreds of questions from the educators I work with and people who read my blog or listen to my podcast.

Having a reliable resource to ask questions and receive timely, practical responses when trying something new is crucial. That’s the goal of my new video series, “Virtual Coaching.” I want to answer your questions, tapping into my experiences and resources as a teacher, coach, and professional learning facilitator. I hope these videos will be valuable as you strive to design and facilitate engaging, effective, and equitable learning experiences.

Each virtual coaching video is designed to provide you with actionable advice that you can apply immediately. These videos cover various topics, including implementing new teaching strategies, overcoming classroom challenges, and exploring innovative ways to engage students. Time is a limited commodity, so I keep my videos short and sweet. The goal is to provide my community of educators with support, insights, and inspiration without overwhelming you or consuming too much of your time.

Also from Catlin, see:

Why Don’t We Trust Students? — from catlintucker.com by Catlin Tucker

As someone who regularly works with teachers on topics like blended learning, Universal Design for Learning (UDL), and student-led learning, one recurring theme I encounter is control. There’s a pervasive fear among educators when it comes to releasing control and allowing students to take more ownership and responsibility for their learning. This begs the question: Why don’t we trust our students? What is it that we really fear?

If we maintain all the control, we hinder our students’ ability to develop the essential skills they will need in the future. The rapidly changing demands of the workplace and life require individuals who are self-motivated, adaptable, and capable of critical thinking and problem-solving. By not allowing students to take more responsibility for their learning, we risk leaving them unprepared for these future challenges.

From DSC:
This item re: control makes me think of this graphic, which readers of this blog will recognize.

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

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/Agents/LLMs/and Related, 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/Agents/LLMs/and Related, 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
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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.
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Traditional textbooks will begin to be replaced by interactive, AI-powered learning materials that adapt in real-time to a student’s progress.
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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/Agents/LLMs/and Related, bots, career development, change, changing business models, colleges, community colleges, computer science, digital learning, education, education technology, emerging technologies, Europe, experimentation, faculty/staff, 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:

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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/staff, 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/Agents/LLMs/and Related, assessment, Canvas - and other Instructure-related items, CMS/LMS, colleges, community colleges, content development, aggregation, repositories, digital learning, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, 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/Agents/LLMs/and Related, colleges, community colleges, digital video, education, education technology, emerging technologies, experimentation, faculty/staff, 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/Agents/LLMs/and Related, 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.

Learning Ecosystems

How to Set Up District-Wide Choice-Based Professional Development [Kersznowski]

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

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