professional development

“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…

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?

Can Schools and Vendors Work Together Constructively on AI? A New Guide May Help — from edweek.org by Alyson Klein
The Education Department outlines key steps on AI development for schools

Educators need to work with vendors and tech developers to ensure artificial intelligence-driven innovations for schools go hand-in-hand with managing the technology’s risks, recommends guidance released July 8 by the U.S. Department of Education.

The guidance—called “Designing for Education with Artificial Intelligence: An Essential Guide for Developers“—includes extensive recommendations for both vendors and school district officials.

Also, on somewhat related notes see the following items:

I highly recommend the https://t.co/QE0Eze3qsr training for educators. It’s well-structured, engaging, and you learn a lot about prompting AI as you create your own custom bot for education. @shaanmasala has built something amazing. PlayLab is a nonprofit, the training is free,…

— Anna Mills, annamillsoer.bsky.social, she/her (@AnnaRMills) July 8, 2024

“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.

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.

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.

“Are two teachers better than one?” [Morton] + other K12-related items

On 05/03/2024, in change, education, education reform, K-12 related, leadership, learning ecosystem, Michigan, more voice more choice more control, pedagogy, productivity / tips and tricks, professional development, strategy, teachers, by Daniel Christian

Are two teachers better than one? More schools say yes to team teaching — from hechingerreport.org by Neal Morton
Early research shows it cuts turnover and improves teachers’ job satisfaction

The model, known as team teaching, isn’t new. It dates back to the 1960s. But Arizona State University resurrected the approach, in which teachers share large groups of students, as a way to rebrand the teaching profession and make it more appealing to prospective educators.
…
In Mesa, teachers working on a team leave their profession at lower rates, receive higher evaluations and are more likely to recommend teaching to a friend.

Early research also indicates students assigned to educator teams made more growth in reading and passed Algebra I at higher rates than their peers.

Question: What Early Advice Had a Lasting Impact on Your Teaching? — from edutopia.org
Share the pivotal advice that shaped your teaching and learn from others in our community.

What Districts With the Worst Attendance Have in Common — from edweek.org by Sarah D. Sparks

It is tough to bring students back to the classroom once chronic absenteeism rates begin to climb. As more districts struggle with historically high absenteeism, new research suggests they may need a more systemic approach to reengaging students.

A new working paper on Michigan schools released by the Annenberg Center found most school districts with severe attendance problems did not directly address absenteeism when planning school improvement strategies. Among those that did focus on improving attendance, few coordinated their interventions across schools and aligned interventions to combat the specific barriers keeping students from school.

“If you think about the reasons that families are missing school, informing families about their children’s attendance is certainly important, but it’s not like the primary driver of absenteeism,” Singer said, “so there’s a disconnect.”

3 Strategies for Successfully Starting Your Career as a School Leader — from edutopia.org by Alexandra Auriemma
An assistant principal near the end of her second year in the job shares her advice for those moving into leadership roles.

However, I’ve learned that effective leadership isn’t about having all of the answers; it’s about knowing which questions to ask. Effective leaders listen deeply and ask questions that shape people’s thinking, moving the organization from where it is to where it needs to go.

Building Better Schools: The art of leading change in education — from gettingsmart.com by Tyler Thigpen

Today’s K12 students are spending the vast majority of their time in classrooms listening to answers to questions they did not ask and following rules they did not have a hand in making. Given that this dynamic goes on for years, what is it doing to students’ minds and spirits? To their agency and empowerment? Are we unintentionally graduating dependent young adults?
…
But what if the opposite were true? What if schools empowered children to flourish? What if schools were the places where they could explore, identify, express, and develop their thoughts, feelings, and goals? There’s power in the uniqueness of every child. It’s time that school designs honor students’ unique calling, preferences, and goals, and encourage them to pursue those. It’s time to move fully into a new era for learning where learners can develop greater self-leadership than ever before.

Instructors as Innovators: a Future-focused Approach to New AI Learning Opportunities, With Prompts –from papers.ssrn.com by Ethan R. Mollick and Lilach Mollick

Abstract

This paper explores how instructors can leverage generative AI to create personalized learning experiences for students that transform teaching and learning. We present a range of AI-based exercises that enable novel forms of practice and application including simulations, mentoring, coaching, and co-creation. For each type of exercise, we provide prompts that instructors can customize, along with guidance on classroom implementation, assessment, and risks to consider. We also provide blueprints, prompts that help instructors create their own original prompts. Instructors can leverage their content and pedagogical expertise to design these experiences, putting them in the role of builders and innovators. We argue that this instructor-driven approach has the potential to democratize the development of educational technology by enabling individual instructors to create AI exercises and tools tailored to their students’ needs. While the exercises in this paper are a starting point, not a definitive solutions, they demonstrate AI’s potential to expand what is possible in teaching and learning.

The Curiosity Matrix: 9 Habits of Curious Minds [Anne-Laure Le Cunff]

On 04/23/2024, in creativity, ideas, learning, metacognition / metacognitive skills, professional development, psychology, by Daniel Christian

The Curiosity Matrix: 9 Habits of Curious Minds — from nesslabs.com by Anne-Laure Le Cunff; via Roberto Ferraro

As an adaptive trait, curiosity draws us to seek information and new experiences. It’s how we learn about ourselves, others, and the world.
…
They’re a diverse group of people, but the literature suggests that they share some common habits that support their personal and professional growth.

12 Books for Instructional Designers to Read This Year — from theelearningcoach.com by Connie Malamed

Over the past year, many excellent and resourceful books have crossed my desk or Kindle. I’m rounding them up here so you can find a few to expand your horizons. The list below is in alphabetical order by title.

Each book is unique, yet as a collection, they reflect some common themes and trends in Learning and Development: a focus on empathy and emotion, adopting best practices from other fields, using data for greater impact, aligning projects with organizational goals, and developing consultative skills. The authors listed here are optimistic and forward-thinking—they believe change is possible. I hope you enjoy the books.

What is executive function? [Belsky]

On 03/13/2024, in Bias | Diversity Equity & Inclusion (DE&I), biology, memory, parents/guardians, participation, professional development, psychology, special needs, student-related, teachers, user experience (UX), youth, by Daniel Christian

Executive function is a set of mental skills that include working memory, flexible thinking, and self-control. We use these skills every day to learn, work, and manage daily life. Trouble with executive function can make it hard to focus, follow directions, and handle emotions, among other things.

Snapshot: What executive function is
Some people describe executive function as “the management system of the brain.” That’s because the skills involved let us set goals, plan, and get things done. When people struggle with executive function, it impacts them at home, in school, and in life.

There are three main areas of executive function. They are…

Amid explosive demand, America is running out of power — from washingtonpost.com by Evan Halper
AI and the boom in clean-tech manufacturing are pushing America’s power grid to the brink. Utilities can’t keep up.

Vast swaths of the United States are at risk of running short of power as electricity-hungry data centers and clean-technology factories proliferate around the country, leaving utilities and regulators grasping for credible plans to expand the nation’s creaking power grid.
…
A major factor behind the skyrocketing demand is the rapid innovation in artificial intelligence, which is driving the construction of large warehouses of computing infrastructure that require exponentially more power than traditional data centers. AI is also part of a huge scale-up of cloud computing. Tech firms like Amazon, Apple, Google, Meta and Microsoft are scouring the nation for sites for new data centers, and many lesser-known firms are also on the hunt.

The Obscene Energy Demands of A.I. — from newyorker.com by Elizabeth Kolbert
How can the world reach net zero if it keeps inventing new ways to consume energy?

“There’s a fundamental mismatch between this technology and environmental sustainability,” de Vries said. Recently, the world’s most prominent A.I. cheerleader, Sam Altman, the C.E.O. of OpenAI, voiced similar concerns, albeit with a different spin. “I think we still don’t appreciate the energy needs of this technology,” Altman said at a public appearance in Davos. He didn’t see how these needs could be met, he went on, “without a breakthrough.” He added, “We need fusion or we need, like, radically cheaper solar plus storage, or something, at massive scale—like, a scale that no one is really planning for.”

A generative AI reset: Rewiring to turn potential into value in 2024 — from mckinsey.com by Eric Lamarre, Alex Singla, Alexander Sukharevsky, and Rodney Zemmel; via Philippa Hardman
The generative AI payoff may only come when companies do deeper organizational surgery on their business.

Figure out where gen AI copilots can give you a real competitive advantage
Upskill the talent you have but be clear about the gen-AI-specific skills you need
Form a centralized team to establish standards that enable responsible scaling
Set up the technology architecture to scale
Ensure data quality and focus on unstructured data to fuel your models
Build trust and reusability to drive adoption and scale

AI Prompt Engineering Is Dead Long live AI prompt engineering — from spectrum.ieee.org

Since ChatGPT dropped in the fall of 2022, everyone and their donkey has tried their hand at prompt engineering—finding a clever way to phrase your query to a large language model (LLM) or AI art or video generator to get the best results or sidestep protections. The Internet is replete with prompt-engineering guides, cheat sheets, and advice threads to help you get the most out of an LLM.
…
However, new research suggests that prompt engineering is best done by the model itself, and not by a human engineer. This has cast doubt on prompt engineering’s future—and increased suspicions that a fair portion of prompt-engineering jobs may be a passing fad, at least as the field is currently imagined.

What the birth of the spreadsheet teaches us about generative AI — from timharford.com by Tim Harford; via Sam DeBrule

There is one very clear parallel between the digital spreadsheet and generative AI: both are computer apps that collapse time. A task that might have taken hours or days can suddenly be completed in seconds. So accept for a moment the premise that the digital spreadsheet has something to teach us about generative AI. What lessons should we absorb?

It’s that pace of change that gives me pause. Ethan Mollick, author of the forthcoming book Co-Intelligence, tells me “if progress on generative AI stops now, the spreadsheet is not a bad analogy”. We’d get some dramatic shifts in the workplace, a technology that broadly empowers workers and creates good new jobs, and everything would be fine. But is it going to stop any time soon? Mollick doubts that, and so do I.

A Notre Dame Senior’s Perspective on AI in the Classroom — from learning.nd.edu — by Sarah Ochocki; via Derek Bruff on LinkedIn

At this moment, as a college student trying to navigate the messy, fast-developing, and varied world of generative AI, I feel more confused than ever. I think most of us can share that feeling. There’s no roadmap on how to use AI in education, and there aren’t the typical years of proof to show something works. However, this promising new tool is sitting in front of us, and we would be foolish to not use it or talk about it.
…
I’ve used it to help me understand sample code I was viewing, rather than mindlessly trying to copy what I was trying to learn from. I’ve also used it to help prepare for a debate, practicing making counterarguments to the points it came up with.

AI alone cannot teach something; there needs to be critical interaction with the responses we are given. However, this is something that is true of any form of education. I could sit in a lecture for hours a week, but if I don’t do the homework or critically engage with the material, I don’t expect to learn anything.

A Map of Generative AI for Education — from medium.com by Laurence Holt; via GSV
An update to our map of the current state-of-the-art

Last ones (for now):

Survey: K-12 Students Want More Guidance on Using AI — from govtech.com by Lauraine Langreo
Research from the nonprofit National 4-H Council found that most 9- to 17-year-olds have an idea of what AI is and what it can do, but most would like help from adults in learning how to use different AI tools.

“Preparing young people for the workforce of the future means ensuring that they have a solid understanding of these new technologies that are reshaping our world,” Jill Bramble, the president and CEO of the National 4-H Council, said in a press release.

AI School Guidance Document Toolkit, with Free Comprehensive Review — from tefanbauschard.substack.com by Stefan Bauschard and Dr. Sabba Quidwai

Two items from Derek Bruff re: teaching and learning in higher education

On 02/28/2024, in adjunct faculty, colleges, community colleges, digital learning, education technology, faculty, higher education, instructional design, IT in HE, learning, learning ecosystem, Learning Experience Design, pedagogy, productivity / tips and tricks, professional development, teaching & learning, United States, universities, by Daniel Christian

Programs, Services, and More: A Map of CTL Tactics — from derekbruff.org

My colleagues and I at the Center for Excellence in Teaching and Learning (CETL) have been reading and discussing Mary C. Wright’s new book Centers for Teaching and Learning: The New Landscape in Higher Education (Johns Hopkins University Press, 2023). Wright identified all the centers for teaching and learning (CTLs) in the United States and then did a content analysis of their websites to see what they were all about. For someone like me, who has spent his career working in CTLs, Wright’s work is a fascinating look at my own field and how it represents itself through mission statements, listings of programs and services, and annual reports.

Also from Derek, see:

Recap: Study skills, flipped learning, and more at spring STEM teaching lunches — from umcetl.substack.com
With the final spring STEM teaching lunch coming up on March 4th, here’s a recap of what you missed at the first two lunches.

- February 8th – Helping students learn how to learn
- February 20th – Reconsidering class time through flipped learning

“Using Generative AI throughout the Institution” [Eaton] + other items re: AI in our Learning Ecosystems

On 02/27/2024, in adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, colleges, community colleges, education technology, emerging technologies, faculty, future, future of higher education, game-changing environment, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, K-12 related, learning ecosystem, Learning Experience Design, platforms, policy, productivity / tips and tricks, professional development, teachers, teaching & learning, teaching online, tools, United States, universities, vendors, by Daniel Christian

Using Generative AI throughout the Institution — from aiedusimplified.substack.com by Lance Eaton
8 lightning talk on generative AI and how to use it through higher education

The magic of AI to help educators with saving time. — from magicschool.ai; via Mrs. Kendall Sajdak

Getting Better Results out of Generative AI — from aiedusimplified.substack.com by Lance Eaton
The prompt to use before you prompt generative AI

Last month, I discussed a GPT that I had created around enhancing prompts. Since then, I have been actively using my Prompt Enhancer GPT to much more effective outputs. Last week, I did a series of mini-talks on generative AI in different parts of higher education (faculty development, human resources, grants, executive leadership, etc) and structured it as “5 tips”. I included a final bonus tip in all of them—a tip that I heard from many afterwards was probably the most useful tip—especially because you can only access the Prompt Enhancer GPT if you are paying for ChatGPT.

Exploring the Opportunities and Challenges with Generative AI — from er.educause.edu by Veronica Diaz

Effectively integrating generative AI into higher education requires policy development, cross-functional engagement, ethical principles, risk assessments, collaboration with other institutions, and an exploration of diverse use cases.

Creating Guidelines for the Use of Gen AI Across Campus — from campustechnology.com by Rhea Kelly
The University of Kentucky has taken a transdisciplinary approach to developing guidelines and recommendations around generative AI, incorporating input from stakeholders across all areas of the institution. Here, the director of UK’s Center for the Enhancement of Learning and Teaching breaks down the structure and thinking behind that process.

That resulted in a set of instructional guidelines that we released in August of 2023 and updated in December of 2023. We’re also looking at guidelines for researchers at UK, and we’re currently in the process of working with our colleagues in the healthcare enterprise, UK Healthcare, to comb through the additional complexities of this technology in clinical care and to offer guidance and recommendations around those issues.

From Mean Drafts to Keen Emails — from automatedteach.com by Graham Clay

My experiences match with the results of the above studies. The second study cited above found that 83% of those students who haven’t used AI tools are “not interested in using them,” so it is no surprise that many students have little awareness of their nature. The third study cited above found that, “apart from 12% of students identifying as daily users,” most students’ use cases were “relatively unsophisticated” like summarizing or paraphrasing text.

For those of us in the AI-curious bubble, we need to continually work to stay current, but we also need to recognize that what we take to be “common knowledge” is far from common outside of the bubble.

What do superintendents need to know about artificial intelligence? — from k12dive.com by Roger Riddell
District leaders shared strategies and advice on ethics, responsible use, and the technology’s limitations at the National Conference on Education.

Despite general familiarity, however, technical knowledge shouldn’t be assumed for district leaders or others in the school community. For instance, it’s critical that any materials related to AI not be written in “techy talk” so they can be clearly understood, said Ann McMullan, project director for the Consortium for School Networking’s EmpowerED Superintendents Initiative.

To that end, CoSN, a nonprofit that promotes technological innovation in K-12, has released an array of AI resources to help superintendents stay ahead of the curve, including a one-page explainer that details definitions and guidelines to keep in mind as schools work with the emerging technology.

Learning Ecosystems

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

Instructors as Innovators: a Future-focused Approach to New AI Learning Opportunities, With Prompts [Mollick & Mollick]

The Curiosity Matrix: 9 Habits of Curious Minds [Anne-Laure Le Cunff]

12 Books for Instructional Designers to Read This Year [Malamed]

“Amid explosive demand, America is running out of power” [Halper] + other items re: AI in general

Two items from Derek Bruff re: teaching and learning in higher education

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