How to use NotebookLM for personalized knowledge synthesis — from ai-supremacy.com by Michael Spencer and Alex McFarland
Two powerful workflows that unlock everything else. Intro: Golden Age of AI Tools and AI agent frameworks begins in 2025.

What is Google Learn about?
Google’s new AI tool, Learn About, is designed as a conversational learning companion that adapts to individual learning needs and curiosity. It allows users to explore various topics by entering questions, uploading images or documents, or selecting from curated topics. The tool aims to provide personalized responses tailored to the user’s knowledge level, making it user-friendly and engaging for learners of all ages.

Is Generative AI leading to a new take on Educational technology? It certainly appears promising heading into 2025.

The Learn About tool utilizes the LearnLM AI model, which is grounded in educational research and focuses on how people learn. Google insists that unlike traditional chatbots, it emphasizes interactive and visual elements in its responses, enhancing the educational experience. For instance, when asked about complex topics like the size of the universe, Learn About not only provides factual information but also includes related content, vocabulary building tools, and contextual explanations to deepen understanding.

 

What DICE does in this posting will be available 24x7x365 in the future [Christian]

From DSC:
First of all, when you look at the following posting:


What Top Tech Skills Should You Learn for 2025? — from dice.com by Nick Kolakowski


…you will see that they outline which skills you should consider mastering in 2025 if you want to stay on top of the latest career opportunities. They then list more information about the skills, how you apply the skills, and WHERE to get those skills.

I assert that in the future, people will be able to see this information on a 24x7x365 basis.

  • Which jobs are in demand?
  • What skills do I need to do those jobs?
  • WHERE do I get/develop those skills?


And that last part (about the WHERE do I develop those skills) will pull from many different institutions, people, companies, etc.

BUT PEOPLE are the key! Oftentimes, we need to — and prefer to — learn with others!


 

“The Value of Doing Things: What AI Agents Mean for Teachers” — from nickpotkalitsky.substack.com by guest author Jason Gulya, Professor of English and Applied Media at Berkeley College in New York City

AI Agents make me nervous. Really nervous.

I wish they didn’t.

I wish I could write that the last two years have made me more confident, more self-assured that AI is here to augment workers rather than replace them.

But I can’t.

I wish I could write that I know where schools and colleges will end up. I wish I could say that AI Agents will help us get where we need to be.

But I can’t.

At this point, today, I’m at a loss. I’m not sure where the rise of AI agents will take us, in terms of how we work and learn. I’m in the question-asking part of my journey. I have few answers.

So, let’s talk about where (I think) AI Agents will take education. And who knows? Maybe as I write I’ll come up with something more concrete.

It’s worth a shot, right?

From DSC: 
I completely agree with Jason’s following assertion:

A good portion of AI advancement will come down to employee replacement. And AI Agents push companies towards that. 

THAT’s where/what the ROI will be for corporations. They will make their investments up in the headcount area, and likely in other areas as well (product design, marketing campaigns, engineering-related items, and more). But how much time it takes to get there is a big question mark.

One last quote here…it’s too good not to include:

Behind these questions lies a more abstract, more philosophical one: what is the relationship between thinking and doing in a world of AI Agents and other kinds of automation?


How Good are Claude, ChatGPT & Gemini at Instructional Design? — from drphilippahardman.substack.com by Dr Philippa Hardman
A test of AI’s Instruction Design skills in theory & in practice

By examining models across three AI families—Claude, ChatGPT, and Gemini—I’ve started to identify each model’s strengths, limitations, and typical pitfalls.

Spoiler: my findings underscore that until we have specialised, fine-tuned AI copilots for instructional design, we should be cautious about relying on general-purpose models and ensure expert oversight in all ID tasks.


From DSC — I’m going to (have Nick) say this again:
I simply asked my students to use AI to brainstorm their own learning objectives. No restrictions. No predetermined pathways. Just pure exploration. The results? Astonishing.

Students began mapping out research directions I’d never considered. They created dialogue spaces with AI that looked more like intellectual partnerships than simple query-response patterns. 


The Digital Literacy Quest: Become an AI Hero — from gamma.app

From DSC:
I have not gone through all of these online-based materials, but I like what they are trying to get at:

  • Confidence with AI
    Students gain practical skills and confidence in using AI tools effectively.
  • Ethical Navigation
    Learn to navigate the ethical landscape of AI with integrity and responsibility. Make informed decisions about AI usage.
  • Mastering Essential Skills
    Develop critical thinking and problem-solving skills in the context of AI.

 


Expanding access to the Gemini app for teen students in education — from workspaceupdates.googleblog.com

Google Workspace for Education admins can now turn on the Gemini app with added data protection as an additional service for their teen users (ages 13+ or the applicable age in your country) in the following languages and countries. With added data protection, chats are not reviewed by human reviewers or otherwise used to improve AI models. The Gemini app will be a core service in the coming weeks for Education Standard and Plus users, including teens,


5 Essential Questions Educators Have About AI  — from edsurge.com by Annie Ning

Recently, I spoke with several teachers regarding their primary questions and reflections on using AI in teaching and learning. Their thought-provoking responses challenge us to consider not only what AI can do but what it means for meaningful and equitable learning environments. Keeping in mind these reflections, we can better understand how we move forward toward meaningful AI integration in education.


FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AI — from epoch.ai
FrontierMath presents hundreds of unpublished, expert-level mathematics problems that specialists spend days solving. It offers an ongoing measure of AI complex mathematical reasoning progress.

We’re introducing FrontierMath, a benchmark of hundreds of original, expert-crafted mathematics problems designed to evaluate advanced reasoning capabilities in AI systems. These problems span major branches of modern mathematics—from computational number theory to abstract algebraic geometry—and typically require hours or days for expert mathematicians to solve.


Rising demand for AI courses in UK universities shows 453% growth as students adapt to an AI-driven job market — from edtechinnovationhub.com

The demand for artificial intelligence courses in UK universities has surged dramatically over the past five years, with enrollments increasing by 453%, according to a recent study by Currys, a UK tech retailer.

The study, which analyzed UK university admissions data and surveyed current students and recent graduates, reveals how the growing influence of AI is shaping students’ educational choices and career paths.

This growth reflects the broader trend of AI integration across industries, creating new opportunities while transforming traditional roles. With AI’s influence on career prospects rising, students and graduates are increasingly drawn to AI-related courses to stay competitive in a rapidly changing job market.

 

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.

.

.


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.

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!

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:

 

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

The landscape of education is on the brink of a profound transformation, driven by rapid advancements in artificial intelligence. This shift was highlighted recently by Andrej Karpathy’s announcement of Eureka Labs, a venture aimed at creating an “AI-native” school. As we look ahead, it’s clear that the integration of AI in education will reshape how we learn, teach, and think about schooling altogether.

Traditional textbooks will begin to be replaced by interactive, AI-powered learning materials that adapt in real-time to a student’s progress.

As we approach 2029, the line between physical and virtual learning environments will blur significantly.

Curriculum design will become more flexible and personalized, with AI systems suggesting learning pathways based on each student’s interests, strengths, and career aspirations.

The boundaries between formal education and professional development will blur, creating a continuous learning ecosystem.

 

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).


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.

  1. Personalized Learning and Tutoring
  2. Teacher Tools
  3. Alternatives to College
  4. 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?
 

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

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

 

Education Technology Organization of Michigan -- ETOM -- Spring 2024 Retreat on June 6-7

PowerPoint slides of Daniel Christian's presentation at ETOM

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

 


Plus several more slides re: this vision.

 

Where a developing, new kind of learning ecosystem is likely headed [Christian]

From DSC:
As I’ve long stated on the Learning from the Living [Class]Room vision, we are heading toward a new AI-empowered learning platform — where humans play a critically important role in making this new learning ecosystem work.

Along these lines, I ran into this site out on X/Twitter. We’ll see how this unfolds, but it will be an interesting space to watch.

Project Chiron's vision: Our vision for education Every child will soon have a super-intelligent AI teacher by their side. We want to make sure they instill a love of learning in children.


From DSC:
This future learning platform will also focus on developing skills and competencies. Along those lines, see:

Scale for Skills-First — from the-job.beehiiv.com by Paul Fain
An ed-tech giant’s ambitious moves into digital credentialing and learner records.

A Digital Canvas for Skills
Instructure was a player in the skills and credentials space before its recent acquisition of Parchment, a digital transcript company. But that $800M move made many observers wonder if Instructure can develop digital records of skills that learners, colleges, and employers might actually use broadly.

Ultimately, he says, the CLR approach will allow students to bring these various learning types into a coherent format for employers.

Instructure seeks a leadership role in working with other organizations to establish common standards for credentials and learner records, to help create consistency. The company collaborates closely with 1EdTech. And last month it helped launch the 1EdTech TrustEd Microcredential Coalition, which aims to increase quality and trust in digital credentials.

Paul also links to 1EDTECH’s page regarding the Comprehensive Learning Record

 

Introducing Teach AI — Empowering educators to teach w/ AI & about AI [ISTE & many others]


Teach AI -- Empowering educators to teach with AI and about AI


Also relevant/see:

 

Credentialed learning for all -- from Getting Smart

 

Why credential section -- from Getting Smart's Credentialed Learning for All

Credentialed Learning For All — from gettingsmart.com

Vision

Learning happens throughout life and is not isolated to the K-12 or higher education sectors. Yet, often, validations of learning only happen in these specific areas. The system of evaluation based on courses, grades, and credit serves as a poor proxy for communicating skills given the variation in course content, grade inflation, and inclusion of participation and extra credit within course grades.

Credentialed learning provides a way to accurately document human capability for all learners throughout their life. A lifetime credentialed learning ecosystem provides better granularity around learning, better documentation of the learning, and more relevance for both the credential recipient and reviewer. This improves the match between higher education and/or employment with the individual, while also providing a more clear and accurate lifetime learning pathway.

With a fully-credentialed system, individuals can own well-documented evidence of a lifetime of learning and choose what and when to share this data. This technology enables every learner to have more opportunities for finding the best career match without today’s existing barriers around cost, access, and proxies.


Addendum on 4/28/23 — speaking of credentials:

First Rung — from the-job.beehiiv.com by Paul Fain
New research shows stacking credentials pays off for low-income learners.

Stacking credentials pays off for many low-income students, new research finds, but only if learners move up the education ladder. Also, Kansas is hoping a new grant program will attract more companies to participate in microinternships.


 

From DSC:
Let’s put together a nationwide campaign that would provide a website — or a series of websites if an agreement can’t be reached amongst the individual states — about learning how to learn. In business, there’s a “direct-to-consumer” approach. Well, we could provide a “direct-to-learner” approach — from cradle to grave. Seeing as how everyone is now required to be a lifelong learner, such a campaign would have enormous benefits to all of the United States. This campaign would be located in airports, subway stations, train stations, on billboards along major highways, in libraries, and in many more locations.

We could focus on things such as:

  • Quizzing yourself / retrieval practice
  • Spaced retrieval
  • Interleaving
  • Elaboration
  • Chunking
  • Cognitive load
  • Learning by doing (active learning)
  • Journaling
  • The growth mindset
  • Metacognition (thinking about one’s thinking)
  • Highlighting doesn’t equal learning
  • There is deeper learning in the struggle
  • …and more.

A learn how to learn campaign covering airports, billboards, subways, train stations, highways, and more

 

A learn how to learn campaign covering airports, billboards, subways, train stations, highways, and more

 

A learn how to learn campaign covering airports, billboards, subways, train stations, highways, and more

 

A learn how to learn campaign covering airports, billboards, subways, train stations, highways, and more


NOTE:
The URL I’m using above doesn’t exist, at least not at the time of this posting.
But I’m proposing that it should exist.


A group of institutions, organizations, and individuals could contribute to this. For example The Learning Scientists, Daniel Willingham, Donald Clark, James Lang, Derek Bruff, The Learning Agency Lab, Robert Talbert, Pooja Agarwal and Patrice Bain, Eva Keffenheim, Benedict Carey, Ken Bain, and many others.

Perhaps there could be:

  • discussion forums to provide for social interaction/learning
  • scheduled/upcoming webinars
  • how to apply the latest evidence-based research in the classroom
  • link(s) to learning-related platforms and/or resources
 

Some example components of a learning ecosystem [Christian]

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

Some example components:

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

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

 

 

Thriving education systems, thriving youth — from events.economist.com by Economist Impact

Some of the key topics to be discussed include:

  • What are the challenges in how we measure learning outcomes today, and how does this need to transform?
  •  What is a learning ecosystem? What does a successful learning ecosystem look like?  
  • What factors enable the development of thriving learning ecosystems?  
  • Who are the key stakeholders that make up the learning ecosystem? How do different stakeholders see their role in the learning ecosystem?
  • Which national policies need to be in place to support effective education ecosystems?
  • What information and data do we need to assess how well learning ecosystems are performing?
  • What data do we need to collect so that we don’t perpetuate traditional approaches to defining and measuring success? 

 

What if smart TVs’ new killer app was a next-generation learning-related platform? [Christian]

TV makers are looking beyond streaming to stay relevant — from protocol.com by Janko Roettgers and Nick Statt

A smart TV's main menu listing what's available -- application wise

Excerpts:

The search for TV’s next killer app
TV makers have some reason to celebrate these days: Streaming has officially surpassed cable and broadcast as the most popular form of TV consumption; smart TVs are increasingly replacing external streaming devices; and the makers of these TVs have largely figured out how to turn those one-time purchases into recurring revenue streams, thanks to ad-supported services.

What TV makers need is a new killer app. Consumer electronics companies have for some time toyed with the idea of using TV for all kinds of additional purposes, including gaming, smart home functionality and fitness. Ad-supported video took priority over those use cases over the past few years, but now, TV brands need new ways to differentiate their devices.

Turning the TV into the most useful screen in the house holds a lot of promise for the industry. To truly embrace this trend, TV makers might have to take some bold bets and be willing to push the envelope on what’s possible in the living room.

 


From DSC:
What if smart TVs’ new killer app was a next-generation learning-related platform? Could smart TVs deliver more blended/hybrid learning? Hyflex-based learning?
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The Living [Class] Room -- by Daniel Christian -- July 2012 -- a second device used in conjunction with a Smart/Connected TV

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Or what if smart TVs had to do with delivering telehealth-based apps? Or telelegal/virtual courts-based apps?


 

The future of learning: Co-creating skills development strategies with employee preferences — from chieflearningofficer.com by Stacey Young Rivers
The limitations of developing just-in-time learning strategies perpetuate a paradigm where learning and development can appear ineffective for teams that have to move quickly and fail fast.

Excerpt:

I believe the future of learning will be a system where employees and learning teams co-create experiences. No longer will skills development programs be created in silos for employees to consume. Gone will be the days of conducting exhaustive needs analysis that can add layers of complexity for program delivery.

The limitations of developing just-in-time learning strategies perpetuate a paradigm where learning and development can appear ineffective for teams that have to move quickly and fail fast. Thinking about how to overcome these challenges conjures a solution similar to a metaverse, a persistent virtual world that is always open. One value proposition of a metaverse is that everyone can create their own adventure in an ecosystem supporting curiosity and experimentation, two areas undergirding skills development.

With this lens, understanding employee preferences for learning is the beginning of co-creating experiences, and one approach for how L&D leaders can begin to structure skills development programs. While conducting a study to engage employees in training, we uncovered new insights into where corporate L&D is headed in the future.

Also relevant here, see:

Workplace Learning: Still a Mess — from eliterate.us by Michael Feldstein

Excerpt:

There’s a mantra these days that higher education needs to get better at listening to industry so they can better prepare students for work. And while there is definitely some truth to that, it assumes that “industry” knows what it needs its workers to know. Former HP CEO Lew Platt once famously said, “If only Hewlett Packard knew what Hewlett Packard knows, we’d be three times more productive.”

In other words, a lot of vital know-how is locked up in pockets within the organization. It doesn’t reach either the training folks or the HR folks. So how are either universities or EdTech professional development companies supposed to serve an invisible need?

It’s not that they don’t know how to learn or they don’t like to learn online. It’s because their experience tells them that their valuable time spent “learning” might not equate to actual skills development.


Addendum on 8/15/22:


 
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