Does ‘Flipped Learning’ Work? A New Analysis Dives Into the Research — from edsurge.com by Jeffrey R. Young

Excerpt:

The researchers do think that flipped learning has merit — if it is done carefully. They end their paper by presenting a model of flipped learning they refer to as “fail, flip, fix and feed,” which they say applies the most effective aspects they learned from their analysis. Basically they argue that students should be challenged with a problem even if they can’t properly solve it because they haven’t learned the material yet, and then the failure to solve it will motivate them to watch the lecture looking for the necessary information. Then classroom time can be used to fix student misconceptions, with a mix of a short lecture and student activities. Finally, instructors assess the student work and give feedback.

From DSC:
Interesting. I think their “fail, flip, fix and feed” method makes sense.

Also, I do think there’s merit in presenting information ahead of time so that students can *control the pace* of listening/processing/absorbing what’s being relayed. (This is especially helpful for native language differences.) If flipped learning would have been a part of my college experience, it would have freed me from just being a scribe. I could have tried to actually process the information while in class.

 

Why Studying Is So Hard, and What Teachers Can Do to Help — from edutopia.org by Laura McKenna
Beginning in the upper elementary grades, research-backed study skills should be woven into the curriculum, argues psychology professor Daniel Willingham in a new book.

Excerpt:

The additional context for Willingham’s new book is that students often don’t know the best methods to study for tests, master complex texts, or take productive notes, and it’s difficult to explain to them why they should take a different tack. In the book, Willingham debunks popular myths about the best study strategies, explains why they don’t work, and recommends effective strategies that are based on the latest research in cognitive science.

I recently spoke to him about why listening to lectures isn’t like watching a movie, how our self-monitoring of learning is often flawed and self-serving, and when it’s too late to start teaching students good study skills.

 
 

Learning relies on emotions — from linkedin.com by Melanie Knight

Learning relies on emotions

From DSC:
I don’t know nearly enough about how our emotions impact our learning. But this version of the Learn About Learning newsletter reminds me of a wish I have that our nation would create a one-stop shop/resource for how we learn:

I wish we had a one-stop shop / URL for how we learn

 

Introducing: ChatGPT Edu-Mega-Prompts — from drphilippahardman.substack.com by Dr. Philippa Hardman; with thanks to Ray Schroeder out on LinkedIn for this resource
How to combine the power of AI + learning science to improve your efficiency & effectiveness as an educator

From DSC:
Before relaying some excerpts, I want to say that I get the gist of what Dr. Hardman is saying re: quizzes. But I’m surprised to hear she had so many pedagogical concerns with quizzes. I, too, would like to see quizzes used as an instrument of learning and to practice recall — and not just for assessment. But I would give quizzes a higher thumbs up than what she did. I think she was also trying to say that quizzes don’t always identify misconceptions or inaccurate foundational information. 

Excerpts:

The Bad News: Most AI technologies that have been built specifically for educators in the last few years and months imitate and threaten to spread the use of broken instructional practices (i.e. content + quiz).

The Good News: Armed with prompts which are carefully crafted to ask the right thing in the right way, educators can use AI like GPT3 to improve the effectiveness of their instructional practices.

As is always the case, ChatGPT is your assistant. If you’re not happy with the result, you can edit and refine it using your expertise, either alone or through further conversation with ChatGPT.

For example, once the first response is generated, you can ask ChatGPT to make the activity more or less complex, to change the scenario and/or suggest more or different resources – the options are endless.

Philippa recommended checking out Rob Lennon’s streams of content. Here’s an example from his Twitter account:


Also relevant/see:

3 trends that may unlock AI's potential for Learning and Development in 2023

3 Trends That May Unlock AI’s Potential for L&D in 2023 — from learningguild.com by Juan Naranjo

Excerpts:

AI-assisted design and development work
This is the trend most likely to have a dramatic evolution this year.

Solutions like large language models, speech generators, content generators, image generators, translation tools, transcription tools, and video generators, among many others, will transform the way IDs create the learning experiences our organizations use. Two examples are:

1. IDs will be doing more curation and less creation:

  • Many IDs will start pulling raw material from content generators (built using natural language processing platforms like Open AI’s GPT-3, Microsoft’s LUIS, IBM’s Watson, Google’s BERT, etc.) to obtain ideas and drafts that they can then clean up and add to the assets they are assembling. As technology advances, the output from these platforms will be more suitable to become final drafts, and the curation and clean-up tasks will be faster and easier.
  • Then, the designer can leverage a solution like DALL-E 2 (or a product developed based on it) to obtain visuals that can (or not) be modified with programs like Illustrator or Photoshop (see image below for Dall-E’s “Cubist interpretation of AI and brain science.”

2. IDs will spend less, and in some cases no time at all, creating learning pathways

AI engines contained in LXPs and other platforms will select the right courses for employees and guide these learners from their current level of knowledge and skill to their goal state with substantially less human intervention.

 


The Creator of ChatGPT Thinks AI Should Be Regulated — from time.com by John Simons

Excerpts:

Somehow, Mira Murati can forthrightly discuss the dangers of AI while making you feel like it’s all going to be OK.

A growing number of leaders in the field are warning of the dangers of AI. Do you have any misgivings about the technology?

This is a unique moment in time where we do have agency in how it shapes society. And it goes both ways: the technology shapes us and we shape it. There are a lot of hard problems to figure out. How do you get the model to do the thing that you want it to do, and how you make sure it’s aligned with human intention and ultimately in service of humanity? There are also a ton of questions around societal impact, and there are a lot of ethical and philosophical questions that we need to consider. And it’s important that we bring in different voices, like philosophers, social scientists, artists, and people from the humanities.


Whispers of A.I.’s Modular Future — from newyorker.com by James Somers; via Sam DeBrule

Excerpts:

Gerganov adapted it from a program called Whisper, released in September by OpenAI, the same organization behind ChatGPTand dall-e. Whisper transcribes speech in more than ninety languages. In some of them, the software is capable of superhuman performance—that is, it can actually parse what somebody’s saying better than a human can.

Until recently, world-beating A.I.s like Whisper were the exclusive province of the big tech firms that developed them.

Ever since I’ve had tape to type up—lectures to transcribe, interviews to write down—I’ve dreamed of a program that would do it for me. The transcription process took so long, requiring so many small rewindings, that my hands and back would cramp. As a journalist, knowing what awaited me probably warped my reporting: instead of meeting someone in person with a tape recorder, it often seemed easier just to talk on the phone, typing up the good parts in the moment.

From DSC:
Journalism majors — and even seasoned journalists — should keep an eye on this type of application, as it will save them a significant amount of time and/or money.

Microsoft Teams Premium: Cut costs and add AI-powered productivity — from microsoft.com by Nicole Herskowitz

Excerpt:

Built on the familiar, all-in-one collaborative experience of Microsoft Teams, Teams Premium brings the latest technologies, including Large Language Models powered by OpenAI’s GPT-3.5, to make meetings more intelligent, personalized, and protected—whether it’s one-on-one, large meetings, virtual appointments, or webinars.


 

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.
 

Colleges consider overhauling grading system for freshmen to ease transition to higher learning — from mercurynews.com by Kate Hull
Supporters say ‘ungrading’ could result in less stress and a more level playing field for students from less rigorous high schools  

Excerpt:

Dubbed “weed-out” or “gatekeeper” classes, they can be dream-crushing for many students — especially those hoping to enter the science, technology, engineering and math (STEM) fields. And a growing body of research says the courses can be particularly discriminatory toward historically excluded groups such as Latinos and Black and Indigenous people.

One possible remedy, some educators say, is “ungrading,” a style of teaching and assessment that seeks to evaluate students in other ways besides A-F letter grades — usually just in their freshman year.

“You’re trying to move the focus from a score to the learning,” said Robin Dunkin, who teaches biology and is the assistant faculty director at UCSC’s Center for Innovations in Teaching and Learning.  “For that reason, it’s immensely powerful.”


Also relevant see the #Ungrading hashtag on Twitter, from which the below item was taken:

Excerpts from Jesse Stommel’s Ungrading: an Introduction presentation:

An excerpt from Ungrading - an Introduction by Jesse Stommel

An excerpt from Ungrading - an Introduction by Jesse Stommel

An excerpt from Ungrading - an Introduction by Jesse Stommel


Also relevant/see Robert Talbert’s Grading for Growth.


 

 

The practical guide to using AI to do stuff — from oneusefulthing.substack.com by Ethan Mollick; with thanks to Sam DeBrule for this resource. Ethan Mollick is a professor at the Wharton School of the University of Pennsylvania where he studies entrepreneurship & innovation, as well as how we can better learn and teach.
A resource for students in my classes (and other interested people).

Excerpts:

My classes now require AI (and if I didn’t require AI use, it wouldn’t matter, everyone is using AI anyway). But how can students use AI well? Here is a basic tutorial and guide I am providing my classes. It covers some of the many ways to use AI to be more productive, creative, and successful, using the technology available in early 2023, as well as some of the risks.

Come up with ideas 
Open Source Option: Nothing very good
Best free (for now) option: ChatGPT (registration may require a phone number)
Best option if ChatGPT is down: OpenAI Playground
.


Also relevant/see:

ChatGPT for educators -- a free 17 lesson course

 



On a relevant note:

Gen Z says school is not equipping them with the skills they need to survive in a digital world — from fastcompany.com by Shalene Gupta; with thanks to Robert Gibson for this resource
According to a study from Dell Technologies, Gen Z-ers in 15 different countries feel their government could do better.

Excerpt:

They see an education and skills gap: Forty-four percent said that school only taught them very basic computing skills, while 37% said that school education (for children under age 16) didn’t prepare them with the technology skills they needed for their planned careers. Forty percent consider learning new digital skills essential to future career options.

It’s clear that Gen Z see technology as pivotal for their future prosperity. It is now up to us—leading technology providers, governments, and the public sector—to work together and set them up for success by improving the quality and access to digital learning. Forty-four percent of Gen Z feel educators and businesses should work together to bridge the digital skills gap, and with the speed at which technology continues to evolve, this will require constant collaboration.

Aongus Hegarty, president of international markets at Dell Technologies


 

Retrieval Practice, Scaffolding, and the Socratic Method — from scholarlyteacher.com by Todd Zakrajsek
Revisit the Socratic method by using it to enact retrieval practice and scaffolding in courses and refresh thinking about applying recommendations from the Scholarship of Teaching and Learning (SOTL)

Excerpt:

When students think they know course material because they have collected reams and reams of information, retrieval practice, much like Socratic questioning, forces students to stop, think, reflect, and reconsider. It meets students where they are (e.g., overwhelmed with information), encourages effortful struggle associated with learning (e.g., presents a desirable difficulty), and offers the discipline of practice (or, perhaps, the practice of discipline). The goal of retrieval practice, getting information out, reflects the goal of so many of Socrates’s questions, to make his interlocutors give an account of and become more aware of their thinking.

When faculty chunk up material, assist students as they move through Bloom’s taxonomy, model approaches to help students get started and maintain momentum, make the student an active participant in developing and reflecting on knowledge, they are incorporating key elements of some of the most important recommendations from the Scholarship of Teaching and Learning. All these techniques help students build or generate knowledge.

 

Learn Smarter Podcast — from learnsmarterpodcast.com

Learn Smarter Podcast educates, encourages and expands understanding for parents of students with different learning profiles through growing awareness of educational therapy, individualized strategies, community support, coaching, and educational content.

Learn Smarter Podcast educates, encourages and expands understanding for parents of students with different learning profiles through growing awareness of educational therapy, individualized strategies, community support, coaching, and educational content.

Somewhat along these lines…for some other resources related to the science of learning, see cogx.info’s research database:

Scientific Literature Supporting COGx Programs
COGx programs involve translation of research from over 500 scientific sources. The scientific literature below is a subset of the literature we have used and organized by subject area to facilitate access. In addition, we have worked directly with some of the authors of the scientific literature to help us translate and co-create our programs. Many of the scientific papers cited below were written by COGx Academic Partners.

Topics include:

    • Information Processing
    • Executive Function
    • Long-Term Memory
    • Metacognition
    • Emotions & Engagement
    • Cognitive Diversity

Also see:

USEFUL LEARNING WITH EFRAT FURST (S3E10)  — from edcircuit.com with Efrat Furst, Tom Sherrington, and Emma Turner

Bringing the science of learning to teachers

 


 

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.

 

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.

 

 
© 2025 | Daniel Christian