5 Ideas To Incorporate AI In Your eLearning Course — from elearningindustry.com by Christopher Pappas

Summary: 

Artificial Intelligence is now taking the world of learning by storm. Here are 5 ways you can successfully incorporate AI in online learning.

Let’s say you’re training sales reps on handling different customer personalities. You can use this technology to diversify your branching scenarios so that trainees can also speak and not only type. This way, not only will the training become more realistic, but you’ll also be able to assess and work on additional elements, such as tone of voice, volume, speech tempo, etc.

 

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.

 

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.
 

How edtech companies should create and empower lifelong learners — from chieflearningofficer.com by Oleg Vilchinski

Excerpt:

Now is the ideal time for a flexible and competent market leader to emerge and seize this opportunity, delivering personalized and lifelong educational solutions and experiences that meet the needs of a learning-hungry populace.

Edtech businesses can address this widening skills gap and need for frequent job-switching through those same data-driven ecosystems, which can support the user through their career and leisure activities. For example, a user could sync their profile with their work’s employee portal to receive further professional development. Simultaneously, the technology would support the user during their spare time as they take courses or watch video content ranging from Adobe InDesign to gardening, further refining their skills. And, when it comes time to retire, the user’s trusted ecosystem has a backlog of data to recommend applicable hobbies and community events.

For example, a user could sync their profile with their work’s employee portal to receive further professional development.

 

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.

 

 

Unschooler: Your AI Vocational Mentor — from techacute.com by Gabriel Scharffenorth

Excerpt (emphasis DSC):

AI to help realize your dream career
The Unschooler mentor helps you understand what you need to do to achieve your dream career. You can select one of six broad areas of expertise: science, people, tech, info, art, and business. The platform will then ask questions related to your future career.

It also has some other useful features. Unschooler keeps track of your skills by adding them to a skill map that’s unique to you. You can also ask it to expand on the information it has already given you. This is done by selecting the text and clicking one of four buttons: more, example, how to, explain, and a question mark icon that defines the selected text. There’s also a mobile app that analyzes text from pictures and explains tasks or concepts.

From DSC:
This integration of AI is part of the vision that I’ve been tracking at:

Learning from the living class room -- a vision that continues to develop, where the pieces are coming into place

Learning from the living [class] room
A vision that continues to develop, where the pieces are finally coming into place!

 

Education is about to radically change: AI for the masses — from gettingsmart.com by Nate McClennen and Rachelle Dené Poth

Key Points:

  • AI already does and will continue to impact education – along with every other sector.
  • Innovative education leaders have an opportunity to build the foundation for the most personalized learning system we have ever seen.

Action

Education leaders need to consider these possible futures now. There is no doubt that K-12 and higher ed learners will be using these tools immediately. It is not a question of preventing “AI plagiarism” (if such a thing could exist), but a question of how to modify teaching to take advantage of these new tools.

From DSC:
They go on to list some solid ideas and experiments to try out — both for students and for teachers. Thanks Nate and Rachelle!


Also from Rachelle, see:


 

Accelerated Learning — Schools’ Answer for ‘Learning Loss’ — Hits Some Speed Bumps — from edsurge.com by Nadia Tamez-Robledo

The main finding? Accelerated learning simply requires more. More staff, more resources, more energy, more buy-in from teachers.

As district leaders talked about their day-to-day realities, they shared how those things were all tough to come by when everyone in the system was already stretched thin.

Not necessarily related to the above item, but I wanted to pass this one along to you as well:

QAA Report on Badging and Micro-Credentialing: How Education and Employment Can Benefit from Using Skills Profiles  — from gettingsmart.com by Rupert Ward

Key Points

  • Skills profiles make it easier for educators and employers to understand how skills gained in learning can be transferred to those required in earning.
  • This QAA Collaborative Enhancement Project Report demonstrates both how badges and microcredentials can be incorporated into a range of higher education courses and, through doing this, how we can ultimately personalise learning and earning.
 

What does the ‘metaverse’ mean for education? — from hechingerreport.org by Javeria Salman
Experts warn educators to think twice before jumping on new technologies

Excerpt:

Sometime in the past year or two, you’ve likely heard the word “metaverse.” It’s the future, the next big frontier of the internet, if you ask technology CEOs or researchers.

While the term has become the latest buzzword in education circles, what it means for teaching and learning largely remains to be seen. Experts say much of what we see marketed as the metaverse from education technology companies isn’t actually the metaverse.

In a true metaverse experience, your digital identity travels between the physical and virtual worlds, Platt said. With the help of blockchain technology, that identity — your preferences, your achievements, your educational records, other elements of who you are — is maintained across platforms and applications.

 

New Mexico College Publishes Report to Advance a National Learning and Employment Record for Skills-based Credentialing and Hiring — from prnewswire.com by Central New Mexico Community College

Excerpt (emphasis DSC):

ALBUQUERQUE, N.M.Oct. 11, 2022 /PRNewswire/ — In the current job market, applicants are usually asked to provide a broad résumé that lists the basics of their qualifications including college degrees and past work experience. It’s an outdated and inefficient system and one that Central New Mexico Community College (CNM) is now helping to improve.

Thanks to a grant from Walmart, CNM produced a comprehensive report that researches several independent efforts underway in order to build a model for creating a national Learner and Employment Records (LER) infrastructure. An LER enables the exchange of skills-based digital records that facilitate more efficient pathways from learning to earning.

An LER is more efficient and secure for both employers and job-seekers because it uses blockchain technology to provide security, trust, and transparency.

From DSC:
I still am learning about how secure blockchain-based applications are — or aren’t. But this idea of a Learner and Employment Record — which I’ve referred to on this blog as a “cloud-based learner profile” — seems to hold a lot of potential as we move into the future. Especially when the focus is increasingly on which skills a position needs and which skills an individual has.

I have used the term cloud-based learner profiles instead of LERs but the idea is the same

 

What might the ramifications be for text-to-everything? [Christian]

From DSC:

  • We can now type in text to get graphics and artwork.
  • We can now type in text to get videos.
  • There are several tools to give us transcripts of what was said during a presentation.
  • We can search videos for spoken words and/or for words listed within slides within a presentation.

Allie Miller’s posting on LinkedIn (see below) pointed these things out as well — along with several other things.



This raises some ideas/questions for me:

  • What might the ramifications be in our learning ecosystems for these types of functionalities? What affordances are forthcoming? For example, a teacher, professor, or trainer could quickly produce several types of media from the same presentation.
  • What’s said in a videoconference or a webinar can already be captured, translated, and transcribed.
  • Or what’s said in a virtual courtroom, or in a telehealth-based appointment. Or perhaps, what we currently think of as a smart/connected TV will give us these functionalities as well.
  • How might this type of thing impact storytelling?
  • Will this help someone who prefers to soak in information via the spoken word, or via a podcast, or via a video?
  • What does this mean for Augmented Reality (AR), Mixed Reality (MR), and/or Virtual Reality (VR) types of devices?
  • Will this kind of thing be standard in the next version of the Internet (Web3)?
  • Will this help people with special needs — and way beyond accessibility-related needs?
  • Will data be next (instead of typing in text)?

Hmmm….interesting times ahead.

 

The next chapter for Learning on YouTube — from blog.youtube by Jonathan Katzman

Next year, qualified creators can begin offering free or paid Courses to provide in-depth, structured learning experiences for viewers. Viewers who choose to buy a Course can watch the video ad-free and play it in the background.

…to help learners apply what they’ve learned, we’re introducing Quizzes — a new way for creators to help viewers test their knowledge.”

.

 
© 2022 | Daniel Christian