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.

 

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

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

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

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

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

 

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

Excerpts (emphasis DSC):

This month, researchers from the University of Pennsylvania published one of the biggest ever reviews of behaviour change efforts – i.e. interventions which do (and don’t) lead to behavioural change in humans.

Research into human behaviour change suggests that, in order to impact capability in real, measurable terms, we need to rethink how we typically design and deliver training.

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

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

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

 

 

Introducing Perplexity Pages — from perplexity.ai
You’ve used Perplexity to search for answers, explore new topics, and expand your knowledge. Now, it’s time to share what you learned.

Meet Perplexity Pages, your new tool for easily transforming research into visually stunning, comprehensive content. Whether you’re crafting in-depth articles, detailed reports, or informative guides, Pages streamlines the process so you can focus on what matters most: sharing your knowledge with the world.

Seamless creation
Pages lets you effortlessly create, organize, and share information. Search any topic, and instantly receive a well-structured, beautifully formatted article. Publish your work to our growing library of user-generated content and share it directly with your audience with a single click.

A tool for everyone
Pages is designed to empower creators in any field to share knowledge.

  • Educators: Develop comprehensive study guides for your students, breaking down complex topics into easily digestible content.

  • Researchers: Create detailed reports on your findings, making your work more accessible to a wider audience.

  • Hobbyists: Share your passions by creating engaging guides that inspire others to explore new interests.

 

How to Make the Dream of Education Equity (or Most of It) a Reality — from nataliewexler.substack.com by Natalie Wexler
Studies on the effects of tutoring–by humans or computers–point to ways to improve regular classroom instruction.

One problem, of course, is that it’s prohibitively expensive to hire a tutor for every average or struggling student, or even one for every two or three of them. This was the two-sigma “problem” that Bloom alluded to in the title of his essay: how can the massive benefits of tutoring possibly be scaled up? Both Khan and Zuckerberg have argued that the answer is to have computers, maybe powered by artificial intelligence, serve as tutors instead of humans.

From DSC:
I’m hoping that AI-backed learning platforms WILL help many people of all ages and backgrounds. But I realize — and appreciate what Natalie is saying here as well — that human beings are needed in the learning process (especially at younger ages). 

But without the human element, that’s unlikely to be enough. Students are more likely to work hard to please a teacher than to please a computer.

Natalie goes on to talk about training all teachers in cognitive science — a solid idea for sure. That’s what I was trying to get at with this graphic:
.

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

.
But I’m not as hopeful in all teachers getting trained in cognitive science…as it should have happened (in the Schools of Education and in the K12 learning ecosystem at large) by now. Perhaps it will happen, given enough time.

And with more homeschooling and blended programs of education occurring, that idea gets stretched even further. 

K-12 Hybrid Schooling Is in High Demand — from realcleareducation.com by Keri D. Ingraham (emphasis below from DSC); via GSV

Parents are looking for a different kind of education for their children. A 2024 poll of parents reveals that 72% are considering, 63% are searching for, and 44% have selected a new K-12 school option for their children over the past few years. So, what type of education are they seeking?

Additional polling data reveals that 49% of parents would prefer their child learn from home at least one day a week. While 10% want full-time homeschooling, the remaining 39% of parents desire their child to learn at home one to four days a week, with the remaining days attending school on-campus. Another parent poll released this month indicates that an astonishing 64% of parents indicated that if they were looking for a new school for their child, they would enroll him or her in a hybrid school.

 

GTC March 2024 Keynote with NVIDIA CEO Jensen Huang


Also relevant/see:




 


[Report] Generative AI Top 150: The World’s Most Used AI Tools (Feb 2024) — from flexos.work by Daan van Rossum
FlexOS.work surveyed Generative AI platforms to reveal which get used most. While ChatGPT reigns supreme, countless AI platforms are used by millions.

As the FlexOS research study “Generative AI at Work” concluded based on a survey amongst knowledge workers, ChatGPT reigns supreme.

2. AI Tool Usage is Way Higher Than People Expect – Beating Netflix, Pinterest, Twitch.
As measured by data analysis platform Similarweb based on global web traffic tracking, the AI tools in this list generate over 3 billion monthly visits.

With 1.67 billion visits, ChatGPT represents over half of this traffic and is already bigger than Netflix, Microsoft, Pinterest, Twitch, and The New York Times.

.


Artificial Intelligence Act: MEPs adopt landmark law — from europarl.europa.eu

  • Safeguards on general purpose artificial intelligence
  • Limits on the use of biometric identification systems by law enforcement
  • Bans on social scoring and AI used to manipulate or exploit user vulnerabilities
  • Right of consumers to launch complaints and receive meaningful explanations


The untargeted scraping of facial images from CCTV footage to create facial recognition databases will be banned © Alexander / Adobe Stock


A New Surge in Power Use Is Threatening U.S. Climate Goals — from nytimes.com by Brad Plumer and Nadja Popovich
A boom in data centers and factories is straining electric grids and propping up fossil fuels.

Something unusual is happening in America. Demand for electricity, which has stayed largely flat for two decades, has begun to surge.

Over the past year, electric utilities have nearly doubled their forecasts of how much additional power they’ll need by 2028 as they confront an unexpected explosion in the number of data centers, an abrupt resurgence in manufacturing driven by new federal laws, and millions of electric vehicles being plugged in.


OpenAI and the Fierce AI Industry Debate Over Open Source — from bloomberg.com by Rachel Metz

The tumult could seem like a distraction from the startup’s seemingly unending march toward AI advancement. But the tension, and the latest debate with Musk, illuminates a central question for OpenAI, along with the tech world at large as it’s increasingly consumed by artificial intelligence: Just how open should an AI company be?

The meaning of the word “open” in “OpenAI” seems to be a particular sticking point for both sides — something that you might think sounds, on the surface, pretty clear. But actual definitions are both complex and controversial.


Researchers develop AI-driven tool for near real-time cancer surveillance — from medicalxpress.com by Mark Alewine; via The Rundown AI
Artificial intelligence has delivered a major win for pathologists and researchers in the fight for improved cancer treatments and diagnoses.

In partnership with the National Cancer Institute, or NCI, researchers from the Department of Energy’s Oak Ridge National Laboratory and Louisiana State University developed a long-sequenced AI transformer capable of processing millions of pathology reports to provide experts researching cancer diagnoses and management with exponentially more accurate information on cancer reporting.


 

Immersive virtual reality tackles depression stigma says study — from inavateonthenet.net

A new study from the University of Tokyo has highlighted the positive effect that immersive virtual reality experiences have for depression anti-stigma and knowledge interventions compared to traditional video.

The study found that depression knowledge improved for both interventions, however, only the immersive VR intervention reduced stigma. The VR-powered intervention saw depression knowledge score positively associated with a neural response in the brain that is indicative of empathetic concern. The traditional video intervention saw the inverse, with participants demonstrating a brain-response which suggests a distress-related response.

From DSC:
This study makes me wonder why we haven’t heard of more VR-based uses in diversity training. I’m surprised we haven’t heard of situations where we are put in someone else’s mocassins so to speak. We could have a lot more empathy for someone — and better understand their situation — if we were to experience life as others might experience it. In the process, we would likely uncover some hidden biases that we have.


Addendum on 3/12/24:

Augmented reality provides benefit for Parkinson’s physical therapy — from inavateonthenet.net

 

How AI Is Already Transforming the News Business — from politico.com by Jack Shafer
An expert explains the promise and peril of artificial intelligence.

The early vibrations of AI have already been shaking the newsroom. One downside of the new technology surfaced at CNET and Sports Illustrated, where editors let AI run amok with disastrous results. Elsewhere in news media, AI is already writing headlines, managing paywalls to increase subscriptions, performing transcriptions, turning stories in audio feeds, discovering emerging stories, fact checking, copy editing and more.

Felix M. Simon, a doctoral candidate at Oxford, recently published a white paper about AI’s journalistic future that eclipses many early studies. Swinging a bat from a crouch that is neither doomer nor Utopian, Simon heralds both the downsides and promise of AI’s introduction into the newsroom and the publisher’s suite.

Unlike earlier technological revolutions, AI is poised to change the business at every level. It will become — if it already isn’t — the beginning of most story assignments and will become, for some, the new assignment editor. Used effectively, it promises to make news more accurate and timely. Used frivolously, it will spawn an ocean of spam. Wherever the production and distribution of news can be automated or made “smarter,” AI will surely step up. But the future has not yet been written, Simon counsels. AI in the newsroom will be only as bad or good as its developers and users make it.

Also see:

Artificial Intelligence in the News: How AI Retools, Rationalizes, and Reshapes Journalism and the Public Arena — from cjr.org by Felix Simon

TABLE OF CONTENTS



EMO: Emote Portrait Alive – Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions — from humanaigc.github.io Linrui Tian, Qi Wang, Bang Zhang, and Liefeng Bo

We proposed EMO, an expressive audio-driven portrait-video generation framework. Input a single reference image and the vocal audio, e.g. talking and singing, our method can generate vocal avatar videos with expressive facial expressions, and various head poses, meanwhile, we can generate videos with any duration depending on the length of input video.


Adobe previews new cutting-edge generative AI tools for crafting and editing custom audio — from blog.adobe.com by the Adobe Research Team

New experimental work from Adobe Research is set to change how people create and edit custom audio and music. An early-stage generative AI music generation and editing tool, Project Music GenAI Control allows creators to generate music from text prompts, and then have fine-grained control to edit that audio for their precise needs.

“With Project Music GenAI Control, generative AI becomes your co-creator. It helps people craft music for their projects, whether they’re broadcasters, or podcasters, or anyone else who needs audio that’s just the right mood, tone, and length,” says Nicholas Bryan, Senior Research Scientist at Adobe Research and one of the creators of the technologies.


How AI copyright lawsuits could make the whole industry go extinct — from theverge.com by Nilay Patel
The New York Times’ lawsuit against OpenAI is part of a broader, industry-shaking copyright challenge that could define the future of AI.

There’s a lot going on in the world of generative AI, but maybe the biggest is the increasing number of copyright lawsuits being filed against AI companies like OpenAI and Stability AI. So for this episode, we brought on Verge features editor Sarah Jeong, who’s a former lawyer just like me, and we’re going to talk about those cases and the main defense the AI companies are relying on in those copyright cases: an idea called fair use.


FCC officially declares AI-voiced robocalls illegal — from techcrunch.com by Devom Coldewey

The FCC’s war on robocalls has gained a new weapon in its arsenal with the declaration of AI-generated voices as “artificial” and therefore definitely against the law when used in automated calling scams. It may not stop the flood of fake Joe Bidens that will almost certainly trouble our phones this election season, but it won’t hurt, either.

The new rule, contemplated for months and telegraphed last week, isn’t actually a new rule — the FCC can’t just invent them with no due process. Robocalls are just a new term for something largely already prohibited under the Telephone Consumer Protection Act: artificial and pre-recorded messages being sent out willy-nilly to every number in the phone book (something that still existed when they drafted the law).


EIEIO…Chips Ahoy! — from dashmedia.co by Michael Moe, Brent Peus, and Owen Ritz


Here Come the AI Worms — from wired.com by Matt Burgess
Security researchers created an AI worm in a test environment that can automatically spread between generative AI agents—potentially stealing data and sending spam emails along the way.

Now, in a demonstration of the risks of connected, autonomous AI ecosystems, a group of researchers have created one of what they claim are the first generative AI worms—which can spread from one system to another, potentially stealing data or deploying malware in the process. “It basically means that now you have the ability to conduct or to perform a new kind of cyberattack that hasn’t been seen before,” says Ben Nassi, a Cornell Tech researcher behind the research.

 

From DSC:
Given this need…

We need to take more of the research from learning science and apply it in our learning spaces.
…I’m highlighting the following resources:


How Learning Happens  — from edutopia.org
In this series, we explore how educators can guide all students, regardless of their developmental starting points, to become productive and engaged learners.

These techniques have resonated with educators everywhere: They are focused on taking advantage of the incredible opportunity to help children reach their full potential by creating positive relationships, experiences, and environments in which every student can thrive. In fact, the science is beginning to hint at even more dramatic outcomes. Practices explicitly designed to integrate social, emotional, and cognitive skills in the classroom, the research suggests, can reverse the damages wrought by childhood trauma and stress—while serving the needs of all students and moving them onto a positive developmental and academic path.


Also from edutopia.org recently, see:

How to Introduce Journaling to Young Children — from edutopia.org by Connie Morris
Students in preschool through second grade can benefit from drawing or writing to explore their thoughts and feelings.

The symbiotic relationship between reading and writing can help our youngest students grow their emergent literacy skills. The idea of teaching writing at an early age can seem daunting. However, meeting children where they are developmentally can make a journaling activity become a magical experience—and they don’t have to write words but can convey thoughts in pictures.

7 Digital Tools That Help Bring History to Life — from edutopia.org by Daniel Leonard
Challenging games, fun projects, and a healthy dose of AI tools round out our top picks for breathing new life into history lessons.

We’ve compiled a list of seven teacher-tested tools, and we lay out how educators are using them both to enhance their lessons and to bring history closer to the present than ever.

Integrating Technology Into Collaborative Professional Learning — from edutopia.org by Roxi Thompson
Incorporating digital collaboration into PD gives teachers a model to replicate when setting up tech activities for students.

 

Google hopes that this personalized AI -- called Notebook LM -- will help people with their note-taking, thinking, brainstorming, learning, and creating.

Google NotebookLM (experiment)

From DSC:
Google hopes that this personalized AI/app will help people with their note-taking, thinking, brainstorming, learning, and creating.

It reminds me of what Derek Bruff was just saying in regards to Top Hat’s Ace product being able to work with a much narrower set of information — i.e., a course — and to be almost like a personal learning assistant for the course you are taking. (As Derek mentions, this depends upon how extensively one uses the CMS/LMS in the first place.)

 

Nearly half of CEOs believe that AI not only could—but should—replace their own jobs — from finance.yahoo.com by Orianna Rosa Royle; via Harsh Makadia

Researchers from edX, an education platform for upskilling workers, conducted a survey involving over 1,500 executives and knowledge workers. The findings revealed that nearly half of CEOs believe AI could potentially replace “most” or even all aspects of their own positions.

What’s even more intriguing is that 47% of the surveyed executives not only see the possibility of AI taking over their roles but also view it as a desirable development.

Why? Because they anticipate that AI could rekindle the need for traditional leadership for those who remain.

“Success in the CEO role hinges on effective leadership, and AI can liberate time for this crucial aspect of their role,” Andy Morgan, Head of edX for Business comments on the findings.

“CEOs understand that time saved on routine tasks can stimulate innovation, nurture creativity, and facilitate essential upskilling for their teams, fostering both individual and organizational success,” he adds.

But CEOs already know this: EdX’s research echoed that 79% of executives fear that if they don’t learn how to use AI, they’ll be unprepared for the future of work.

From DSC:
By the way, my first knee-jerk reaction to this was:

WHAT?!?!?!? And this from people who earn WAAAAY more than the average employee, no doubt.

After a chance to calm down a bit, I see that the article does say that CEOs aren’t going anywhere. Ah…ok…got it.


Strange Ways AI Disrupts Business Models, What’s Next For Creativity & Marketing, Some Provocative Data — from .implications.com by Scott Belsky
In this edition, we explore some of the more peculiar ways that AI may change business models as well as recent releases for the world of creativity and marketing.

Time-based business models are liable for disruption via a value-based overhaul of compensation. Today, as most designers, lawyers, and many trades in between continue to charge by the hour, the AL-powered step-function improvements in workflows are liable to shake things up.

In such a world, time-based billing simply won’t work anymore unless the value derived from these services is also compressed by a multiple (unlikely). The classic time-based model of billing for lawyers, designers, consultants, freelancers etc is officially antiquated. So, how might the value be captured in a future where we no longer bill by the hour? …

The worlds of creativity and marketing are rapidly changing – and rapidly coming together

#AI #businessmodels #lawyers #billablehour

It becomes clear that just prompting to get images is a rather elementary use case of AI, compared to the ability to place and move objects, change perspective, adjust lighting, and many other actions using AI.



AlphaFold DB provides open access to over 200 million protein structure predictions to accelerate scientific research. — from

AlphaFold is an AI system developed by DeepMind that predicts a protein’s 3D structure from its amino acid sequence. It regularly achieves accuracy competitive with experiment.


After 25 years of growth for the $68 billion SEO industry, here’s how Google and other tech firms could render it extinct with AI — from fortune.com by Ravi Sen and The Conversation

But one other consequence is that I believe it may destroy the $68 billion search engine optimization industry that companies like Google helped create.

For the past 25 years or so, websites, news outlets, blogs and many others with a URL that wanted to get attention have used search engine optimization, or SEO, to “convince” search engines to share their content as high as possible in the results they provide to readers. This has helped drive traffic to their sites and has also spawned an industry of consultants and marketers who advise on how best to do that.

As an associate professor of information and operations management, I study the economics of e-commerce. I believe the growing use of generative AI will likely make all of that obsolete.


ChatGPT Plus members can upload and analyze files in the latest beta — from theverge.com by Wes Davis
ChatGPT Plus members can also use modes like Browse with Bing without manually switching, letting the chatbot decide when to use them.

OpenAI is rolling out new beta features for ChatGPT Plus members right now. Subscribers have reported that the update includes the ability to upload files and work with them, as well as multimodal support. Basically, users won’t have to select modes like Browse with Bing from the GPT-4 dropdown — it will instead guess what they want based on context.


Google agrees to invest up to $2 billion in OpenAI rival Anthropic — from reuters.com by Krystal Hu

Oct 27 (Reuters) – Alphabet’s (GOOGL.O) Google has agreed to invest up to $2 billion in the artificial intelligence company Anthropic, a spokesperson for the startup said on Friday.

The company has invested $500 million upfront into the OpenAI rival and agreed to add $1.5 billion more over time, the spokesperson said.

Google is already an investor in Anthropic, and the fresh investment would underscore a ramp-up in its efforts to better compete with Microsoft (MSFT.O), a major backer of ChatGPT creator OpenAI, as Big Tech companies race to infuse AI into their applications.


 

 

Florida bar weighs whether lawyers using AI need client consent — from reuters.com by Karen Sloan; via Brainyacts

Oct 16 (Reuters) – Florida lawyers might soon be required to get their client’s consent before using artificial intelligence on their legal matters.

The Florida Bar is crafting a new advisory opinion focused on the use of AI and has asked Florida lawyers to weigh in. Florida bar leaders have tasked the Florida Board Review Committee on Professional Ethics with creating rules around the use of generative AI, such as OpenAI’s ChatGPT, Google Bard or Microsoft’s Bing.


On a somewhat related note, also see:

 

Evidence Is Mounting That Calculus Should Be Changed. Will Instructors Heed It? — from edsurge.com by Daniel Mollenkamp

Calculus is a critical on-ramp to careers in science, technology, engineering and mathematics (STEM). But getting to those careers means surviving the academic journey.

While there’s been progress of late, it’s been “uneven” and Black, Hispanic and women workers are still underrepresented in some STEM fields. Traditional methods of calculus instruction may be knocking students off the path to these vital occupations, which is why advocates warn that getting diverse students into these careers may require instructional models more responsive to students. Meanwhile, the country is struggling to fill vacancies in related fields like semiconductor manufacturing, despite sizable investments — a feat that may require stabilizing the pipeline.

Good news: There’s mounting evidence that changing calculus instruction works for the groups usually pushed out of STEM. At least, that’s according to a randomized study recently published in the peer-reviewed journal Science.

 

Student Use Cases for AI: Start by Sharing These Guidelines with Your Class — from hbsp.harvard.edu by Ethan Mollick and Lilach Mollick

To help you explore some of the ways students can use this disruptive new technology to improve their learning—while making your job easier and more effective—we’ve written a series of articles that examine the following student use cases:

  1. AI as feedback generator
  2. AI as personal tutor
  3. AI as team coach
  4. AI as learner

Recap: Teaching in the Age of AI (What’s Working, What’s Not) — from celt.olemiss.edu by Derek Bruff, visiting associate director

Earlier this week, CETL and AIG hosted a discussion among UM faculty and other instructors about teaching and AI this fall semester. We wanted to know what was working when it came to policies and assignments that responded to generative AI technologies like ChatGPT, Google Bard, Midjourney, DALL-E, and more. We were also interested in hearing what wasn’t working, as well as questions and concerns that the university community had about teaching and AI.


Teaching: Want your students to be skeptical of ChatGPT? Try this. — from chronicle.com by Beth McMurtrie

Then, in class he put them into groups where they worked together to generate a 500-word essay on “Why I Write” entirely through ChatGPT. Each group had complete freedom in how they chose to use the tool. The key: They were asked to evaluate their essay on how well it offered a personal perspective and demonstrated a critical reading of the piece. Weiss also graded each ChatGPT-written essay and included an explanation of why he came up with that particular grade.

After that, the students were asked to record their observations on the experiment on the discussion board. Then they came together again as a class to discuss the experiment.

Weiss shared some of his students’ comments with me (with their approval). Here are a few:


2023 EDUCAUSE Horizon Action Plan: Generative AI — from library.educause.edu by Jenay Robert and Nicole Muscanell

Asked to describe the state of generative AI that they would like to see in higher education 10 years from now, panelists collaboratively constructed their preferred future.
.

2023-educause-horizon-action-plan-generative-ai


Will Teachers Listen to Feedback From AI? Researchers Are Betting on It — from edsurge.com by Olina Banerji

Julie York, a computer science and media teacher at South Portland High School in Maine, was scouring the internet for discussion tools for her class when she found TeachFX. An AI tool that takes recorded audio from a classroom and turns it into data about who talked and for how long, it seemed like a cool way for York to discuss issues of data privacy, consent and bias with her students. But York soon realized that TeachFX was meant for much more.

York found that TeachFX listened to her very carefully, and generated a detailed feedback report on her specific teaching style. York was hooked, in part because she says her school administration simply doesn’t have the time to observe teachers while tending to several other pressing concerns.

“I rarely ever get feedback on my teaching style. This was giving me 100 percent quantifiable data on how many questions I asked and how often I asked them in a 90-minute class,” York says. “It’s not a rubric. It’s a reflection.”

TeachFX is easy to use, York says. It’s as simple as switching on a recording device.

But TeachFX, she adds, is focused not on her students’ achievements, but instead on her performance as a teacher.


ChatGPT Is Landing Kids in the Principal’s Office, Survey Finds — from the74million.org by Mark Keierleber
While educators worry that students are using generative AI to cheat, a new report finds students are turning to the tool more for personal problems.

Indeed, 58% of students, and 72% of those in special education, said they’ve used generative AI during the 2022-23 academic year, just not primarily for the reasons that teachers fear most. Among youth who completed the nationally representative survey, just 23% said they used it for academic purposes and 19% said they’ve used the tools to help them write and submit a paper. Instead, 29% reported having used it to deal with anxiety or mental health issues, 22% for issues with friends and 16% for family conflicts.

Part of the disconnect dividing teachers and students, researchers found, may come down to gray areas. Just 40% of parents said they or their child were given guidance on ways they can use generative AI without running afoul of school rules. Only 24% of teachers say they’ve been trained on how to respond if they suspect a student used generative AI to cheat.


Embracing weirdness: What it means to use AI as a (writing) tool — from oneusefulthing.org by Ethan Mollick
AI is strange. We need to learn to use it.

But LLMs are not Google replacements, or thesauruses or grammar checkers. Instead, they are capable of so much more weird and useful help.


Diving Deep into AI: Navigating the L&D Landscape — from learningguild.com by Markus Bernhardt

The prospect of AI-powered, tailored, on-demand learning and performance support is exhilarating: It starts with traditional digital learning made into fully adaptive learning experiences, which would adjust to strengths and weaknesses for each individual learner. The possibilities extend all the way through to simulations and augmented reality, an environment to put into practice knowledge and skills, whether as individuals or working in a team simulation. The possibilities are immense.

Thanks to generative AI, such visions are transitioning from fiction to reality.


Video: Unleashing the Power of AI in L&D — from drphilippahardman.substack.com by Dr. Philippa Hardman
An exclusive video walkthrough of my keynote at Sweden’s national L&D conference this week

Highlights

  • The wicked problem of L&D: last year, $371 billion was spent on workplace training globally, but only 12% of employees apply what they learn in the workplace
  • An innovative approach to L&D: when Mastery Learning is used to design & deliver workplace training, the rate of “transfer” (i.e. behaviour change & application) is 67%
  • AI 101: quick summary of classification, generative and interactive AI and its uses in L&D
  • The impact of AI: my initial research shows that AI has the potential to scale Mastery Learning and, in the process:
    • reduce the “time to training design” by 94% > faster
    • reduce the cost of training design by 92% > cheaper
    • increase the quality of learning design & delivery by 96% > better
  • Research also shows that the vast majority of workplaces are using AI only to “oil the machine” rather than innovate and improve our processes & practices
  • Practical tips: how to get started on your AI journey in your company, and a glimpse of what L&D roles might look like in a post-AI world

 
© 2024 | Daniel Christian