A Spotify model of personalised higher education — from timeshighereducation.com by Michael Rosemann and Martin Betts
With technology offering greater potential for a personalised approach to higher education, Michael Rosemann and Martin Betts look at what universities can learn from the ubiquitous music platform Spotify

Excerpts (emphasis DSC):

Selection, or the P(upil)-route as educationalist Dan Buckley calls it, means personalisation driven by the learner. This is the fastest-moving form of personalised learning. Not only do students benefit from true omnichannel education – choosing between face to face and online – they also independently navigate the internet’s resources and online databases in search of the knowledge that will help them to achieve their learning targets.

Automation,  or the A-route, is the new enabler of personalised learning. As with personalised medicine, finance or entertainment, education is starting to use digital technologies to unlock new models of tailored engagement. While for most universities, AI-driven, personalised education is not an option as the required capabilities are missing and significant investments would be necessary, there is a range of alternative forms of automated personalised learning. For this, we look to providers outside the sector for inspiration.

Here are Spotify-inspired ideas that universities ambitious enough to provide personalised learning could explore.

From DSC:
Rosemann & Betts use the term “omnichannel education” — I like that term. Very nice.

 

Territorium Introduces AI-Powered System to Track Skills and Competencies from K–12 to Career — from campustechnology.com by Kate Lucariello

Excerpt:

Global ed tech provider Territorium has launched LifeJourney, a suite of AI-powered tools for users to keep track of education, job skills, and career readiness capabilities. With the LifeJourney toolkit’s comprehensive individual records all in one place, students can provide quick and easily accessible information to prospective employers, according to the company. The suite of tools keeps track of progress and achievements from K–12 through higher education and career readiness.

Comprehensive Learner Records -- The Territorium CLR is a holistic picture of an individual’s skills and competencies

From DSC:
This type of comprehensive learner record is a piece of the vision that I’ve been tracking at “Learning from the Living [Class] Room” — where I call it a Cloud-Based Learner Profile.

 


Also relevant/see:

College Accreditation 101: How It Works & Why It Matters — from business-essay.com; with thanks to Lili North for this resource

Excerpt:

Entering a prestigious college and getting a quality education is one of the top priorities for high school graduates. But how do you know if the college you are considering is really worth it?

Well, luckily, there is accreditation: a process of evaluating educational institutions. Accreditation is an important factor to consider when selecting a college: after all, unaccredited schools don’t provide you with widely recognized diplomas and can leave you with insufficient knowledge and skills.

Want to know more? You’re in the right place! This article covers the essential information every college applicant should know about accreditation.


Also relevant/see:


Addendum on 3/18/23:

Credentialing Everything: A Primer on Learning and Employment Records and Digital Wallets — from gettingsmart.com by Nate McClennen and Rachelle Dené Poth

Key Points

  • Credentials and learner records are accelerating the shift to competency-based learning.
  • They help learners manage unbundled learning by collecting evidence from multiple providers and provide quicker and more personalized onramps to high-wage employment.

Measuring Learning Growth: Competencies and Standards — from gettingsmart.com by Nate McClennen and Rebecca Midles

Key Points

  • The role of competencies has become increasingly important as employers, students and educators realize the impact of transferable skill deficit in young people.
  • The challenge, however, becomes implementation.
 


Description of video:

Sal Khan walks through Khan Academy’s GPT-4 integration (not generally available yet). Folks can join the waitlist at Khanacademy.org. To learn more about Khanmigo, visit: khanacademy.org/khan-labs

We believe that AI has the potential to transform learning in a positive way, but we are also keenly aware of the risks. To test the possibilities, we’re inviting our district partners to opt in to Khan Labs, a new space for testing learning technology. We want to ensure that our work always puts the needs of students and teachers first, and we are focused on ensuring that the benefits of AI are shared equally across society. In addition to teachers and students, we’re inviting the general public to join a waitlist to test Khanmigo. Teachers, students and donors will be our partners on this learning journey, helping us test AI to see if we can harness it as a learning tool for all.


GPT-4 has arrived. It will blow ChatGPT out of the water. — from washingtonpost.com by Drew Harwell and Nitasha Tiku
The long-awaited tool, which can describe images in words, marks a huge leap forward for AI power — and another major shift for ethical norms


Introducing Our Virtual Volunteer Tool for People who are Blind or Have Low Vision, Powered by OpenAI’s GPT-4 — from bemyeyes.com
We are thrilled to announce Be My Eyes Virtual Volunteer™, the first-ever digital visual assistant powered by OpenAI’s new GPT-4 language model.


 

For example, [GPT-4] passes a simulated bar exam with a score around the top 10% of test takers; in contrast, GPT-3.5’s score was around the bottom 10%. 

Source

 


 


 

HOW DUOLINGO’S AI LEARNS WHAT YOU NEED TO LEARN — from spectrum.ieee.org by Klinton Bicknell, Claire Brust, and Burr Settles
The AI that powers the language-learning app today could disrupt education tomorrow

Excerpt:

It’s lunchtime when your phone pings you with a green owl who cheerily reminds you to “Keep Duo Happy!” It’s a nudge from Duolingo, the popular language-learning app, whose algorithms know you’re most likely to do your 5 minutes of Spanish practice at this time of day. The app chooses its notification words based on what has worked for you in the past and the specifics of your recent achievements, adding a dash of attention-catching novelty. When you open the app, the lesson that’s queued up is calibrated for your skill level, and it includes a review of some words and concepts you flubbed during your last session.

The AI systems we continue to refine are necessary to scale the learning experience beyond the more than 50 million active learners who currently complete about 1 billion exercises per day on the platform.

Although Duolingo is known as a language-learning app, the company’s ambitions go further. We recently launched apps covering childhood literacy and third-grade mathematics, and these expansions are just the beginning. We hope that anyone who wants help with academic learning will one day be able to turn to the friendly green owl in their pocket who hoots at them, “Ready for your daily lesson?”


Also relevant/see:

GPT-4 deepens the conversation on Duolingo

Duolingo turned to OpenAI’s GPT-4 to advance the product with two new features: Role Play, an AI conversation partner, and Explain my Answer, which breaks down the rules when you make a mistake, in a new subscription tier called Duolingo Max. 

“We wanted AI-powered features that were deeply integrated into the app and leveraged the gamified aspect of Duolingo that our learners love,” says Bodge.


Also relevant/see:

The following is a quote from Donald Clark’s posting on LinkedIn.com today:

The whole idea of AI as a useful teacher is here. Honestly it’s astounding. They have provided a Socratic approach to an algebra problem that is totally on point. Most people learn in the absence of a teacher or lecturer. They need constant scaffolding, someone to help them move forward, with feedback. This changes our whole relationship with what we need to know, and how we get to know it. Its reasoning ability is also off the scale.

We now have human teachers, human learners but also AI teachers and AI that learns. It used to be a diad, it is now a tetrad – that is the basis of the new pedAIgogy.

Personalised, tutor-led learning, in any subject, anywhere, at any time for anyone. That has suddenly become real.

Also relevant/see:

Introducing Duolingo Max, a learning experience powered by GPT-4 — from blog.duolingo.com

Excerpts:

We believe that AI and education make a great duo, and we’ve leveraged AI to help us deliver highly-personalized language lessons, affordable and accessible English proficiency testing, and more. Our mission to make high-quality education available to everyone in the world is made possible by advanced AI technology.

Explain My Answer offers learners the chance to learn more about their response in a lesson (whether their answer was correct or incorrect!)

Roleplay allows learners to practice real-world conversation skills with world characters in the app.

 

ChatGPT as a teaching tool, not a cheating tool — from timeshighereducation.com by Jennifer Rose
How to use ChatGPT as a tool to spur students’ inner feedback and thus aid their learning and skills development

Excerpt:

Use ChatGPT to spur student’s inner feedback
One way that ChatGPT answers can be used in class is by asking students to compare what they have written with a ChatGPT answer. This draws on David Nicol’s work on making inner feedback explicit and using comparative judgement. His work demonstrates that in writing down answers to comparative questions students can produce high-quality feedback for themselves which is instant and actionable. Applying this to a ChatGPT answer, the following questions could be used:

  • Which is better, the ChatGPT response or yours? Why?
  • What two points can you learn from the ChatGPT response that will help you improve your work?
  • What can you add from your answer to improve the ChatGPT answer?
  • How could the assignment question set be improved to allow the student to demonstrate higher-order skills such as critical thinking?
  • How can you use what you have learned to stay ahead of AI and produce higher-quality work than ChatGPT?
 

Challenging ‘Bad’ Online Policies and Attitudes — from insidehighered.com by Susan D’Agostino
Academic and industry leaders spoke with conviction at the SXSW EDU conference this week about approaches that impede educational access to motivated, capable learners.

Excerpts:

“It’s driven by artificial intelligence,” Barnes said of IBM’s training and reskilling effort. “It’s a Netflix-like interface that pushes content. Or an employee can select content…

The leaders discussed the ways in which colleges, policymakers, and employers might work together to help more Americans find or advance in viable employment, while also addressing the workforce skills gap. But some “bad” policies and attitudes about online learning undermine their efforts to work together, expand access and deliver outcomes to motivated, capable learners.

“Employers were saying, ‘We have job openings we can’t fill, and we want to work with the education system, but it is so unbelievably frustrating because they’re very rigid, and they don’t want to customize to our needs,’” Hansen said. These employers sought workforce training that could produce a pipeline of learners-turned-employees, and Hansen said they told him, “If you can do that, I’ll pay you.”

 

Fostering sustainable learning ecosystems — from linkedin.com by Patrick Blessinger

Excerpt (emphasis DSC):

Learning ecosystems
As today’s global knowledge society becomes increasingly interconnected and begins to morph into a global learning society, it is likely that formal, nonformal, and informal learning will become increasingly interconnected. For instance, there has been an explosion of new self-directed e-learning platforms such as Khan Academy, Open Courseware, and YouTube, among others, that help educate billions of people around the world.

A learning ecosystem includes all the elements that contribute to a learner’s overall learning experience. The components of a learning ecosystem are numerous, including people, technology platforms, knowledge bases, culture, governance, strategy, and other internal and external elements that have an impact on learning. Therefore, moving forward, it is crucial to integrate learning across formal, nonformal, and informal learning processes and activities in a more strategic way.

Learning ecosystems -- formal, informal, and nonformal sources of learning will become more tightly integrated in the future

 

ChatGPT is Everywhere — from chronicle.com by Beth McMurtrie
Love it or hate it, academics can’t ignore the already pervasive technology.

Excerpt:

Many academics see these tools as a danger to authentic learning, fearing that students will take shortcuts to avoid the difficulty of coming up with original ideas, organizing their thoughts, or demonstrating their knowledge. Ask ChatGPT to write a few paragraphs, for example, on how Jean Piaget’s theories on childhood development apply to our age of anxiety and it can do that.

Other professors are enthusiastic, or at least intrigued, by the possibility of incorporating generative AI into academic life. Those same tools can help students — and professors — brainstorm, kick-start an essay, explain a confusing idea, and smooth out awkward first drafts. Equally important, these faculty members argue, is their responsibility to prepare students for a world in which these technologies will be incorporated into everyday life, helping to produce everything from a professional email to a legal contract.

“Artificial-intelligence tools present the greatest creative disruption to learning that we’ve seen in my lifetime.”

Sarah Eaton, associate professor of education at the University of Calgary



Artificial intelligence and academic integrity, post-plagiarism — from universityworldnews.com Sarah Elaine Eaton; with thanks to Robert Gibson out on LinkedIn for the resource

Excerpt:

The use of artificial intelligence tools does not automatically constitute academic dishonesty. It depends how the tools are used. For example, apps such as ChatGPT can be used to help reluctant writers generate a rough draft that they can then revise and update.

Used in this way, the technology can help students learn. The text can also be used to help students learn the skills of fact-checking and critical thinking, since the outputs from ChatGPT often contain factual errors.

When students use tools or other people to complete homework on their behalf, that is considered a form of academic dishonesty because the students are no longer learning the material themselves. The key point is that it is the students, and not the technology, that is to blame when students choose to have someone – or something – do their homework for them.

There is a difference between using technology to help students learn or to help them cheat. The same technology can be used for both purposes.

From DSC:
These couple of sentences…

In the age of post-plagiarism, humans use artificial intelligence apps to enhance and elevate creative outputs as a normal part of everyday life. We will soon be unable to detect where the human written text ends and where the robot writing begins, as the outputs of both become intertwined and indistinguishable.

…reminded me of what’s been happening within the filmmaking world for years (i.e., such as in Star Wars, Jurrasic Park, and many others). It’s often hard to tell what’s real and what’s been generated by a computer.
 

Industry insight: Blockchaining to track current and potential employees’ skills — from chieflearningofficer.com by Tanya Boyd

Excerpts:

A learner who is aware of their unique strengths and development needs, as well as their preferred approach for gaining new skills, is often able to find the learning opportunities that they need more effectively and efficiently.

A global language for skills
While we might be tempted to focus within, looking for ways to address our own company’s talent challenges in isolation, this common concern invites a more global solution. We would all be better off if we could build a global language for skills. It’s at least one step toward achieving global processes for evaluating and developing them.

The top three challenges with skills and skill-based practices, as cited by McKinsey’s 2021 state of hiring survey, are: the ability to validate skills, sourcing job seekers with the right skills and scaling this approach.

Having a validated “chain” of skills for an employee helps not only in the selection process, but also as L&D departments seek to personalize learning. Blockchain creates a more valid approach to personalizing learning based on each employee’s competencies and skills gathered across their career, rather than just the skills they are demonstrating in their current organization and role.

 

Introducing Q-Chat, the world’s first AI tutor built with OpenAI’s ChatGPT — from quizlet.com by Lex Bayer

Excerpt:

Modeled on research demonstrating that the most effective form of learning is one-on-one tutoring1, Q-Chat offers students the experience of interacting with a personal AI tutor in an effective and conversational way. Whether they’re learning French vocabulary or Roman History, Q-Chat engages students with adaptive questions based on relevant study materials delivered through a fun chat experience. Pulling from Quizlet’s massive educational content library and using the question-based Socratic method to promote active learning, Q-Chat has the ability to test a student’s knowledge of educational content, ask in-depth questions to get at underlying concepts, test reading comprehension, help students learn a language and encourage students on healthy learning habits.

Quizlet's Q-Chat -- choose a study prompt to be quizzed on the material, to deepen your understanding or to learn through a story.

 


Speaking of AI-related items, also see:

OpenAI debuts Whisper API for speech-to-text transcription and translation — from techcrunch.com by Kyle Wiggers

Excerpt:

To coincide with the rollout of the ChatGPT API, OpenAI today launched the Whisper API, a hosted version of the open source Whisper speech-to-text model that the company released in September.

Priced at $0.006 per minute, Whisper is an automatic speech recognition system that OpenAI claims enables “robust” transcription in multiple languages as well as translation from those languages into English. It takes files in a variety of formats, including M4A, MP3, MP4, MPEG, MPGA, WAV and WEBM.

Introducing ChatGPT and Whisper APIs — from openai.com
Developers can now integrate ChatGPT and Whisper models into their apps and products through our API.

Excerpt:

ChatGPT and Whisper models are now available on our API, giving developers access to cutting-edge language (not just chat!) and speech-to-text capabilities.



Everything you wanted to know about AI – but were afraid to ask — from theguardian.com by Dan Milmo and Alex Hern
From chatbots to deepfakes, here is the lowdown on the current state of artificial intelligence

Excerpt:

Barely a day goes by without some new story about AI, or artificial intelligence. The excitement about it is palpable – the possibilities, some say, are endless. Fears about it are spreading fast, too.

There can be much assumed knowledge and understanding about AI, which can be bewildering for people who have not followed every twist and turn of the debate.

 So, the Guardian’s technology editors, Dan Milmo and Alex Hern, are going back to basics – answering the questions that millions of readers may have been too afraid to ask.


Nvidia CEO: “We’re going to accelerate AI by another million times” — from
In a recent earnings call, the boss of Nvidia Corporation, Jensen Huang, outlined his company’s achievements over the last 10 years and predicted what might be possible in the next decade.

Excerpt:

Fast forward to today, and CEO Jensen Huang is optimistic that the recent momentum in AI can be sustained into at least the next decade. During the company’s latest earnings call, he explained that Nvidia’s GPUs had boosted AI processing by a factor of one million in the last 10 years.

“Moore’s Law, in its best days, would have delivered 100x in a decade. By coming up with new processors, new systems, new interconnects, new frameworks and algorithms and working with data scientists, AI researchers on new models – across that entire span – we’ve made large language model processing a million times faster,” Huang said.

From DSC:
NVIDA is the inventor of the Graphics Processing Unit (GPU), which creates interactive graphics on laptops, workstations, mobile devices, notebooks, PCs, and more. They are a dominant supplier of artificial intelligence hardware and software.


 

Donald Clark’s recent thoughts regarding how ChatGPT is and will impact the Learning & Development world — from linkedin.com by Donald Clark

Excerpts:

Fascinating chat with three people heading up L&D in a major international company. AI has led them to completely re-evaluate their strategy. Key concepts were performance, process and data. What I liked was their focus on that oft-quoted issue of aligning L&D with the business goals – unlike most, they really meant it.

The technology that puts that in the hands of learners has arrived. Performance support will be a teacher or trainer at your fingertips.

We also talked about prompting, the need to see it as ‘CHAT’gpt, an iterative process, where you need to understand how to speak to the tech. It’s a bit like speaking to an alien from space, as it has no comprehension or consciousness but it is still competent and smart. We have put together 100 prompt tips for learning professionals and taking it out on the road soon. All good in the hood.

Also from Donald Clark, see:

OpenAI releases massive wave of innovation — from donaldclarkplanb.blogspot.com

Excerpt:

With LLMs, OpenAI’s ChatGPT, based on GPT 3.5, started a race where:

  • AI is integrated into mainstream tools like Teams
  • Larger LLMs are being built
  • LLMs are changing ‘search’
  • LLMs are being used on a global scale in real businesses
  • Real businesses are being built on the back of LLMs
  • LLMs as part of ensembes of other tools are being researched to solve accuracy, updatability & provenance issues
  • Open, transparent LLMs (Bloom) are being built
 

Meet MathGPT: a Chatbot Tutor Built Specific to a Math Textbook — from thejournal.com by Kristal Kuykendall

Excerpt:

Micro-tutoring platform PhotoStudy has unveiled a new chatbot built on OpenAI’s ChatGPT APIs that can teach a complete elementary algebra textbook with “extremely high accuracy,” the company said.

“Textbook publishers and teachers can now transform their textbooks and teaching with a ChatGPT-like assistant that can teach all the material in a textbook, assess student progress, provide personalized help in weaker areas, generate quizzes with support for text, images, audio, and ultimately a student customized avatar for video interaction,” PhotoStudy said in its news release.

Some sample questions the MathGPT tool can answer:

    • “I don’t know how to solve a linear equation…”
    • “I have no idea what’s going on in class but we are doing Chapter 2. Can we start at the top?”
    • “Can you help me understand how to solve this mixture of coins problem?”
    • “I need to practice for my midterm tomorrow, through Chapter 6. Help.”
 

Educator considerations for ChatGPT — from platform.openai.com; with thanks to Anna Mills for this resource

Excerpt:

Streamlined and personalized teaching
Some examples of how we’ve seen educators exploring how to teach and learn with tools like ChatGPT:

  • Drafting and brainstorming for lesson plans and other activities
  • Help with design of quiz questions or other exercises
  • Experimenting with custom tutoring tools
  • Customizing materials for different preferences (simplifying language, adjusting to different reading levels, creating tailored activities for different interests)
  • Providing grammatical or structural feedback on portions of writing
  • Use in upskilling activities in areas like writing and coding (debugging code, revising writing, asking for explanations)
  • Critique AI generated text

While several of the above draw on ChatGPT’s potential to be explored as a tool for personalization, there are risks associated with such personalization as well, including student privacy, biased treatment, and development of unhealthy habits. Before students use tools that offer these services without direct supervision, they and their educators should understand the limitations of the tools outlined below.

Also relevant/see:

Excerpt (emphasis DSC):
David Wiley wrote a thoughtful post on the ways in which AI and Large Language Models (LLMs) can “provide instructional designers with first drafts of some of the work they do.” He says “imagine you’re an instructional designer who’s been paired with a faculty member to create a course in microeconomics. These tools might help you quickly create first drafts of” learning outcomes, discussion prompts, rubrics, and formative assessment items.  The point is that LLMs can quickly generate rough drafts that are mostly accurate drafts, that humans can then “review, augment, and polish,” potentially shifting the work of instructional designers from authors to editors. The post is well worth your time.

The question that I’d like to spend some time thinking about is the following: What new knowledge, capacities, and skills do  instructional designers need in their role as editors and users of LLMs?

This resonated with me. Instructional Designer positions are starting to require AI and ML chops. I’m introducing my grad students to AI and ChatGPT this semester. I have an assignment based on it.

(This ain’t your father’s instructional design…)

Robert Gibson


 

Unbundled: Designing Personalized Pathways for Every Learner — from gettingsmart.com by Nate McClennen “with contributions from the Getting Smart team and numerous friends and partners in the field”

Excerpts:

In this publication, we articulate the critical steps needed to unbundle the learning ecosystem, build core competencies, design learning experiences, curate new opportunities, and rebundle these experiences into coherent pathways.
.

Building the Unbundled Ecosystem

Vision

Every learner deserves an unlimited number of unbundled opportunities to explore, engage, and define experiences that advance their progress along a co-designed educational pathway. Each pathway provides equitable and personalized access to stacked learning experiences leading to post-secondary credentials and secure family-sustaining employment. Throughout the journey, supportive coaches focus on helping learners build skills to navigate with agency. In parallel, learners develop foundational skills (literacy, math), technical skills, and durable skills and connect these to challenging co-designed experiences. The breadth and depth of experiences increase over time, and, in partnership, learners and coaches map progress towards reaching community-defined goals. This vision is only enabled by an unbundled learning ecosystem.

Recommendations

Solutions already exist in the ecosystem and need to be combined and scaled. Funding models (like My Tech High), badging/credentialing at the competency level (like VLACS), coaching models (like Big Thought), and open ecosystems (like NH Learn Everywhere) provide an excellent foundation. Thus, building unbundled systems has already begun but needs systemic changes to become widely available and accepted.

      1. Build a robust competency-based system.
      2. Create a two-way marketplace for unbundled learning.
      3. Implement policy to support credit for out-of-system experiences.
      4. Invest in technology infrastructure for Learning and Employment Records.
      5. Design interoperable badging systems that connect to credentials.
 
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