Login
Coming off of Reclaim Open, one of the things I’m thinking about is online resources for self-teaching beginners. When we were interviewing people for the documentary, we asked people what they were glad the internet had now, in the present, that it hadn’t had in the past. And a lot of people — not everyone, but a lot — talked about how there’s a plethora of learning resources for beginners on just about any subject. Which got me thinking about the learning resources that I’ve used and the tutorials I’ve tried to follow.
There are so many things that I want to learn. I’ve got a post in the works about teaching myself to draw. About a month ago, I hit a milestone on my Duolingo streak (800 days!). I used to practice guitar, though I’ve fallen out of that habit in the past year. For a while I was experimenting with some of the beginner guides to Unity. I have an abundance of tutorials and resources on various topics bookmarked — a beginner’s guide to Ruby on Rails, Codecademy, HackerRank, etc. — which I’ve used… at some point in the past. I keep a list of topics to research that only gets longer and longer.
All this, and I still feel like a dabbler in everything. Part of it is that I’ve put aside topics for long periods of time (almost everything except Duolingo, honestly). That’s naturally led to skill atrophy and forgetting what I was doing, which means difficulty picking up where I left off. But for the one thing I have stuck with, I don’t feel like I’m getting any better — my Italian is beginner-level at best, with a poor grasp of grammar and difficulty remembering vocabulary when I need it.
So I’m thinking: what are the differences in the resources I’ve looked at? What do they require? Where do they go together, and where do they fall short?
The framework I’ve got in my head right now for self-teaching is structured vs unstructured learning resources.
Structured resources are things like Duolingo or Codecademy, a series of tutorials designed to build on each other. Unstructured resources are more like the Youtube video tutorials that exist for drawing or guitar, and their related practice tools (guitar tab websites, figure drawing photo banks).
Structured resources are designed methodically by one group in a way that emphasizes logical progress from point A to point B to point C. There’s a general focus on fundamentals first, then building up to more advanced concepts, with exercises designed to practice each new topic. The exercises are usually short and easy enough that lessons can be completed in 5-10 minutes max, to encourage making learning a routine and habitual practice. The focus is on progressing through the course.
Unstructured resources means that there’s a wide range of sources from various unconnected groups, which all specialize in different topics. Learning is self-directed, since there’s no clear path connecting everything, and there are few if any pre-built exercises (a given resource might have 2 or 3, but none of them hang together). Learners can focus their studying in their weakest areas, or specialize in the topics that most interest them, and the lack of pre-built exercises means that their learning goals shape what they’re working on — which means that there’s more intrinsic motivation to learn, since they’re tailoring their practice to their own interests. The most common advice I hear for people who want to learn guitar is “Pick a song you like, and learn to play it.” There’s simplified versions of just about every song out there so beginners can learn the most basic version, and once they have that, they can try something more advanced. It’s learning by doing.
With structured learning, there’s issues of pacing, attention span and motivation. Short, easy lessons are designed to keep attention and build routine, so you can do a little bit every day, but if you do only a little bit every day it might feel like you’re taking months or years to get anywhere. That damages motivation, which is doubly bad because you’re working towards proficiency but not a specific intrinsic goal; that makes it extra-hard to measure progress.
Curated and designed exercises may also not be right for all learners, or self-structured online learning may create certain pitfalls. For example, one major issue I have with Duolingo is that because of the way its lessons are structured, there’s no way to have exercises strengthening true composition (written or spoken). There’s options for translating back and forth between your native language and your target language, but there’s nothing along the lines of “Write a paragraph about your favorite book” or “Talk about your most recent vacation”. That’s a major barrier to fluency, since being able to read and listen in your target language is only one half of communication, and it’s the less challenging half.
With unstructured learning, though, you still get pacing, attention span and motivation issues. This time the issue is that it’s hard to know how much time to spend on certain topics, and where to start or how to build on them. Dumping time into something while feeling like you’re stumbling in the dark trying to figure out what you need to do next is a sure way to damage motivation, which can in turn make your attention focus elsewhere.
Exercises for unstructured learning can also feel repetitive, since your resources only give you a few. Everyone says the way to get good at drawing is to practice figure drawing, which is true — I have definitely improved as a result — but I don’t know how to vary it up to keep learning fresh or which details to pay attention to in order to practice most effectively. And if it’s not repetitive, it’s chaotic — everyone has an opinion, and everyone disagrees. Who do you listen to, and how do you cut through the noise and really decide how to spend your time?
This is a long way of saying: I’ve never learned to teach, and I don’t know how to learn to learn. Because self-structured learning is way different than learning in a classroom, or in a group, or with a mentor. There’s no external framework to keep you accountable, or to provide feedback, or to provide any of the other benefits that come with a learning community.
When it comes to self-directed learning, there’s so many principles I keep hearing about — resilience, goal-setting, failing forward, varying your practice, etc. — but all the resources I’ve found assume learners are coming to them with those principles already well-developed, and that all that’s left is the skill-building section.
Which makes sense! Teaching your learners how to self-teach before teaching them what they actually came to learn, is an absurd thing to ask. But for pretty much everything I learned in school, I learned from other people; I almost never got practice teaching myself.
So there’s a lot of beginner-friendly resources out there. And they’re great for if you have one or two specific things you need to learn. But for people starting in total ignorance who want to work their way up to overarching mastery, how beginner-friendly are they really?
“Bresee helps the youth and those who are most disadvantaged. Serving Koreatown, a primarily Hispanic community, and advocate for the need of bringing peace to our community. By focusing on the youth, Bresee is able to build a better future where everyone is given equal opportunities and leads them to a successful future.” – Youth... Read more »
The post A Holistic College and Career Readiness Practice appeared first on Connected Learning Alliance.
This workshop on Developing a Reflective Practice was offered in May 2023 for the MSU COLA Fellows. It was converted to this asynchronous format for those who weren’t able to attend.
This workshop consists of four main parts, with a reflection point separating each part. You may use the reflection prompt individually, or if you have a colleague, partner (or group of them) doing these activities together you may find it helpful to discuss and reflect together. To get the full benefit of working through these materials plan to spend about 45 minutes to watch through the videos, take the time for reflection, and to make any final notes.
Reflective Practice as defined by Donald Schon is “Thinking about one’s actions so as to engage in a process of continuous learning.” By engaging in an intentional reflective practice we are able to learn about ourselves and to make meaning from our experiences in ways that help us learn to do things differently, better, or otherwise in ways that are informed by our reflection. In this part of the workshop take some time to watch this short video and then consider the reflection/discussion prompt that follows
Watch video “What is Reflective Practice?” – 3 min 42 sec
This reflection/discussion topic is around your individual approaches to reflection and reflective practice. Take 5-7 minutes to think/write/discuss your thinking on the following:
Outcome from this activity: Find common methods of reflection/tools you use, and learn about other options from your discussion partners.
Watch video “Starting Your Reflective Practice” – 3 min 32 sec
This reflection/discussion topic is about the approaches your discipline uses for reflection. Take 5-7 minutes to think/write/discuss your thinking on the following:
Outcome from this activity: Identify ways your discipline conducts reflective activities. Learn from other disciplines and identify other possible frameworks, approaches, or tools for reflecting.
Watch video “Enacting Your Reflective Practice” – 7 min 14 sec
This last reflection/discussion topic is about critically engaging in the activities of reflection and reflective practice. Take 5-7 minutes to think/write/discuss your thinking on the following:
Outcome from this activity: Consider the affordances and limitations of different ways of reflecting and where/how you might want to share your reflection or not.
Take a few minutes to gather your notes and thoughts from the previous activities and then set your timer for another 5 minutes of self-reflection to set a plan up for developing/refining your reflective practice over the coming months.
If you are in the COLA Program you have to reflect at the end of the summer on all the work and thinking you are doing with the program, how might you develop and use an intentional reflective practice to document your work this summer? If you are not in the program think about how developing and implementing an intentional reflective practice might help you over the next couple of months.
How might you use the habits you form through reflective practice in these coming months to influence your teaching going forward? How might it help you in your next annual review or other reporting points, or how it might generally help you to become a better teacher, researcher, etc?
Remember that changing and developing habits is HARD WORK. You likely won’t develop a lasting practice overnight or in a short amount of time, a slow and steady pace is a great way to develop these habits that will last a long time.
Reflective practice is personal—the challenge is to figure out what works for you and supports your learning. Take some time to try out different things, see what works/doesn’t and what you connect with. Ask colleagues who are doing this work and learn from them.
Some ideas to get started and/or support your practice:
This workshop was recorded on May 25, 2023 as part of the MSU COLA Fellows workshop series.
The positive benefits of youth interacting with technology are often ignored while the negatives are emphasized. It’s time for that to change. In a commitment to this effort, the Connected Learning Alliance, along with the Connected Learning Lab at the University of California, Irvine, are excited to share the new Connected Wellbeing Initiative with the... Read more »
The post The Connected Wellbeing Initiative: Building Understanding and Action Regarding Teens’ Technology Use and Their Mental Health appeared first on Connected Learning Alliance.
Imagine we’re all surfers. The ocean we’re in is the educational system, and we’re all trying to ride the wave of knowledge to the shore of understanding. Some of us have master surfers as guides – personal tutors who are right there with us, helping us manoeuvre the currents and ride high on the knowledge wave. They know our strengths, they know our fears, and they ensure we don’t wipe out. These fortunate few reach the shore faster, more smoothly and often with a lot more fun.
Then there are the rest of us. We’re in a giant surf class. There’s one instructor and dozens of us learners. The instructor is doing their best, but they can’t give us all the personalised attention we need. Some of us catch the wave, some of us don’t. This is Bloom’s Two Sigma Problem.
Brought to the fore by educational psychologist Benjamin Bloom in the 1980s, the Two Sigma Problem highlights a gap in education. Personal tutoring can propel students’ performance by two standard deviations – like moving from the middle of a class right to the top 2%. The problem is, we can’t give everyone a personal tutor. It’s just not feasible. So, the question is, how do we give each student the benefits of one-on-one instruction, at scale?
Enter Artificial Intelligence (AI) and, in particular, Large Language Models (LLMs) such as ChatGPT. I’ve been experimenting with using ChatGPT as a tutor for my son during the revision period for his exams. It’s great at coming up with questions, marking them, and suggesting how to improve. This kind of feedback is absolutely crucial to learning. It’s also great at exploring the world and allowing curiosity to take you in new directions.
So, if we revisit the Two Sigma Problem based on what’s possible with LLMs, it looks like there’s a possible solution with multiple advantages:
No technology is a silver bullet. As an educator, I know that while curiosity and feedback is really important, there’s nothing like another human providing emotional input — including motivation. AI is here to support, not replace, our human guides.
Even though it’s early days, we’re already seeing some really interesting developments in the application of LLMs in education. I’m no fan of Microsoft, but I will acknowledge that a feature they have in development called ‘passage generation’ looks interesting. This tool reviews data to create personalised reading passages based on the words or phonics rules a student finds most challenging. Educators can customise the passage, selecting suggested practice words and generating options, then publish the passage as a new reading assignment. I find this kind of thing really useful in Duolingo for learning Spanish. Context matters.
As a former teacher, I know how important prioritisation can be for the limited amount of time you have with each student. And as a parent, I’m a big believer in the power of deliberate practice for getting better at all kinds of things. Freeing up teachers to be more like coaches than instructors has been the dream ever since someone came up with the pithy phrase “guide on the side, not sage on the stage”.
One of the main concerns I think a lot people have with AI in general is that it will “steal our jobs”. I’d point out here that the main problem here isn’t AI, it’s capitalism. Any tool or system be used for good or for ill. If you’re not sure how we can approach this post-scarcity world, I’d recommend reading Fully Automated Luxury Communism by Aaron Bastani. Of course, regulation is and should be an issue, too.
The main issue I see with this is centralised LLMs run by companies running opaque models and beholden to shareholders. That’s why I envisage educational institutions running local LLMs, or at least within a network that only connects to the internet when it needs to. Just as Google Desktop used to allow you to search through your local machine and the web, I can imagine us all having an AI assistant that has full context, while preserving our privacy.
So the way to approach any new tool or service is to ask critical questions such as “who benefits?” but also to fully explore what’s possible with all of this. I’m hugely hopeful that AI won’t lead us into a sci-fi dystopia, but rather help to even out the playing field when it comes to human learning and flourishing.
What do you think? I’d love to hear in the comments!
Image remixed from an original on the SkillUp blog. Text written with the help of ChatGPT (it’s particularly good at coming up with metaphors, I’ve found!)
The post Using AI to help solve Bloom’s Two Sigma Problem first appeared on Open Thinkering.Image: Portland State University, Oregon MESA InventTeams In 2019 I stumbled upon the field of invention education when I joined a Lemelson-MIT (LMIT) research project examining how high school teams were using computer science to create technological solutions that would improve the lives of others. As part of the research, I attended EurekaFest, where I... Read more »
The post When Learning is Irresistible: An Invitation to Foster Inventive Mindsets appeared first on Connected Learning Alliance.
“When we change the input into our minds, we change the output into our lives.” — Zig Ziglar
Even the best jobs are complicated and stressful in various ways. Outside forces are nearly always there and it often feels like many of them are out to get us. And by get us, I mean they are looking to interrupt our work, relationships, leadership, vision, and in many cases, our sanity. We often don’t recognize moments where the outside forces appear to be negative, but In reality, if looked at differently, offers a chance to do a course correct. With that said, sometimes those outside forces are truly out to derail us, but we have more power than we often think.
I recently had a health related incident that knocked me out of action for a period of time. Now that I am back and feel great, I am practicing a different mindset about who I am and how I choose to react to those outside forces. When I heard that quote this morning it really made me reflect on my 25 years of work in higher education and how I have given these forces too much power. At each stop of the way there have been forces that have pushed me to do great work and those that have actively worked against the progress our institutions need to face. Using the mindset above I am learning that we have more control over how we process these signals on the way in and how to convert them into an energy on the way out that allows us to do great work (sanely) and how to treat the people in our lives that are important.
“As a child that’s one thing that my parents really instilled in us as children is to know who you are and identify with what is most connected to you…We are Black people. We are of African descent. That is the culture. That’s how I was raised. That’s what I know. That’s who I am.... Read more »
The post Timbuk2 – Anchored in a Historical Legacy of Care and Spirituality appeared first on Connected Learning Alliance.
On behalf of the Connected Learning Summit Conference Committee, we are pleased to announce the publication of the Proceedings of the 2022 Connected Learning Summit. It is our honor to share with you a proceedings that celebrates participatory, playful, and transformative learning. In 2021, the Connected Learning Summit became a fully online event, supporting inclusive,... Read more »
The post Proceedings of the 2022 Connected Learning Summit Released appeared first on Connected Learning Alliance.
File this under “designing board games is a lot like teaching”…
I was recently reading the new issue of Senet magazine, a publication whose tagline is “board games are beautiful.” The issue featured an interview with Matt Leacock, designer of the popular cooperative board game Pandemic. In a cooperative board game, all the players work together to defeat the game. There’s no single winner; either everyone wins or the game wins. What happens when one player starts telling all the other players what they should do? That’s called the alpha player problem, and it can really take the fun out of a cooperative game.
Leacock was asked about the alpha player problem and what a game designer can do about it. “The designer… has a responsibility to create mechanisms where everyone can shine and one player can’t dominate.” What are some mechanisms that can prevent or at least minimize the alpha player problem? Leacock identified three strategies:
As I was reading the Leacock interview, I couldn’t help but think of analogies to the college classroom. When integrating group work in a class session, there’s a risk that some groups will have an “alpha student,” that is, a group member who takes charge in an unhelpful way. Not only can this make for some uncomfortable social situations, it can also deprive other group members of opportunities to learn.
How can teachers try to prevent or minimize the alpha student problem? Leacock’s three game design strategies transfer very well to educational settings!
How do you go about structuring group work to avoid “alpha students”? Do your methods map onto any of these three strategies?
For more on the intersection of games and teaching, see my “Learning at Play” blog posts or my Leading Lines podcast interviews with Patrick Rael, Max Seidman, and Kimberly Rogers.
If you can remember the web of 30 years ago(!), you can remember a time when all it took to make a website was a little knowledge of HTML and a tilde account on the university VAXcluster (e.g., /~wiley6/). While it’s still possible to make a simple website today with just HTML, making modern websites requires a dizzying array of technical skills, including HTML, CSS, JavaScript frameworks, databases and SQL, cloud devops, and others. While these websites require far more technical expertise to build, they are also far more feature-rich and functional then their ancestors of 30 years ago. (Imagine trying to code each of the millions of pages on Wikipedia.org or Amazon.com completely by hand with notepad!)
This is what large language models (LLMs) like ChatGPT are doing to OER. Next generation OER will not be open textbooks that were created faster or more efficiently because LLMs wrote first drafts in minutes. That’s current generation OER simply made more efficiently. The next generation of OER will be the embeddings (from a 5R perspective, these are revised versions of an OER) that are part of the process of feeding domain knowledge into LLMs so that they can answer questions correctly and give you accurate explanations and examples. Creating embeddings and injecting this additional context into an LLM just-in-time as part of a prompt engineering strategy requires significantly more technical skill than typing words into Pressbooks does. But it will also give us OER that are far more feature-rich and functional than their open ancestors of 25 years ago.
Here’s a video tutorial of how to integrate a specific set of domain knowledge into GPT3 so that it can dialog with a user based on that specific domain knowledge. This domain knowledge could come from chapters in an open textbook, but in the example in the video it’s coming from software documentation. Granted, this video is almost two months old, which feels more than two years old at the rate AI is changing right now. So this isn’t the exact way we’ll end up doing it, but the video will give you the idea.
Rather than fine tuning an LLM, where the entire model training process has to be repeated, embeddings allow us to find just the right little pieces of OER to provide to the LLM as additional context when we submit a prompt. This is orders of magnitude faster and less expensive than retraining the entire model, and still gives the model access to the domain specific information we want it to have during our conversation / tutoring session / etc. And by “orders of magnitude faster and less expensive” I mean this is a legitimate option for a normal person with some technical skill, unlike retraining a model which can easily cost over $1M in compute alone.
Every day feels like a year for those of us trying to keep up with what’s happening with AI right now. It would be the understatement of the century to say lots more will happen in this space – we’re literally just scratching the surface. Our collective lack of imagination is the only thing holding us back. What an incredible time to be a learner! What an incredible time to be a teacher! What an incredible time to be working and researching in edtech!
They’re coming to us, without any work experience because of discrimination and lack of opportunities. Or with having had some work experience, but having struggled to successfully retain the job because of hostile employment settings. Or having experienced racism on the job and negotiating professional standards that are unwritten but expected. – Maddie Deegan Davenport,... Read more »
The post Responding to Race in Youth Career Development Practice appeared first on Connected Learning Alliance.
Enlarge / An AI-generated image from an #aicinema still series called "Vinyl Vengeance" by Julie Wieland, created using Midjourney. (credit: Julie Wieland / Midjourney)
Since last year, a group of artists have been using an AI image generator called Midjourney to create still photos of films that don't exist. They call the trend "AI cinema." We spoke to one of its practitioners, Julie Wieland, and asked her about her technique, which she calls "synthography," for synthetic photography.
Last year, image synthesis models like DALL-E 2, Stable Diffusion, and Midjourney began allowing anyone with a text description (called a "prompt") to generate a still image in many different styles. The technique has been controversial among some artists, but other artists have embraced the new tools and run with them.
While anyone with a prompt can make an AI-generated image, it soon became clear that some people possessed a special talent for finessing these new AI tools to produce better content. As with painting or photography, the human creative spark is still necessary to produce notable results consistently.
On online learning and alternative academic careers.
Seven ingredients for gathering well.
At the crossroads of education, social justice, and personal development stands critical pedagogy, a concept associated with the Brazilian educator and philosopher Paolo Freire. His conviction was that education should be egalitarian, democratic, and transformative; his work has had an outsize impact on my educational philosophy. Critical pedagogy emphasises the significance of dialogue, critical thinking, and active participation. The further I delve into the world of of Open Recognition, the clearer the links with Freire, both in essence and practice.
In Pedagogy of the Oppressed, Freire states that:
Education either functions as an instrument which is used to facilitate integration of the younger generation into the logic of the present system and bring about conformity or it becomes the practice of freedom, the means by which men and women deal critically and creatively with reality and discover how to participate in the transformation of their world.
Open Recognition, like critical pedagogy, is about empowering individuals to take ownership of their personal and professional development. The approach not only foregrounds knowledge, skills, and understanding, but also behaviours, relationships, and experiences.
Freire believed that through open and honest conversations, individuals could challenge existing power structures, question assumptions, and engage in transformative learning experiences. Similarly, Open Recognition offers a way for individuals to engage in meaningful conversations about their skills, experiences, and aspirations — using language and approaches that make sense to them.
In facilitating dialogue over power dynamics, Open Recognition nurtures a sense of community and belonging. It empowers individuals to share their stories and learn from one another, and this exchange of ideas and experiences not only contributes to personal growth but also fosters a sense of collective responsibility and solidarity
Critical pedagogy is grounded in the belief that education should be a vehicle for social change and empowerment. Open Recognition aligns with this vision by providing ways for individuals make meaningful contributions to their communities, challenge the status quo, and actively participate in shaping their own futures.
So it’s fair to say that Open Recognition and critical pedagogy share a common goal: the empowerment and transformation of individuals through dialogue, inclusion, and active participation. By explicitly embracing the principles of critical pedagogy, it’s my belief that Open Recognition can help create a more inclusive and equitable world.
If you’re interested in Open Recognition, critical pedagogy, and doing something different than the status quo, I’d highly suggest joining badges.community!
The post Open Recognition + Critical Pedagogy = empowerment, dialogue, and inclusion first appeared on Open Thinkering.Imagine a formidable fortress standing tall. Long the bastion of formal education, it’s built upon the pillars of ‘standards’ and ‘rigour’. It has provided structure and stability to the learning landscape. These days, it’s being reinforced with smaller building blocks (‘microcredentials’) but the shape and size of the fortress largely remains the same.
However, as the winds of change begin to blow, a new force emerges from the horizon: Open Recognition. Far from seeking to topple the fortress, this powerful idea aims to harmonise with its foundations, creating a more inclusive and adaptive stronghold for learning.
Open Recognition is a movement that values diverse learning experiences and self-directed pathways. So, at first, it may appear to be in direct opposition to the fortress’s rigidity. However, upon closer inspection, rather than seeking to tear down the walls of standards and rigour, Open Recognition seeks to expand and reimagine them. This ensures that the fortress is inclusive: remaining relevant and accessible to all learners.
To create harmony between these seemingly conflicting forces, it’s important to first acknowledge that the fortress of standards and rigour does have its merits. It provides a solid framework for education, ensuring consistency and quality across the board. However, this approach can also be limiting, imposing barriers that prevent many learners from fully realising their potential.
Open Recognition brings flexibility and personalisation to the fortress. By validating the skills and competencies acquired through non-formal and informal learning experiences, Open Recognition allows the fortress to accommodate different sizes and shape of ‘room’, allowing the unique talents and aspirations of each individual to flourish
The key to harmonising these two forces lies in recognising their complementary nature. Open Recognition strengthens the fortress by expanding its boundaries, while standards and rigour provide the structural integrity that ensures the quality and credibility of the learning experiences within.
Educators and employers, as the guardians of the fortress, play a crucial role in fostering this harmony. By embracing Open Recognition, they can cultivate a more inclusive and dynamic learning ecosystem that values and supports diverse pathways to success. In doing so, they not only uphold the principles of standards and rigour but also enrich the fortress with the wealth of experiences and perspectives that Open Recognition brings.
As the fortress of standards and rigour harmonises with Open Recognition, it becomes a thriving stronghold of lifelong learning, identity, and opportunity. Far from crumbling under the weight of change, the fortress is invigorated by the union of these two powerful forces, ensuring its continued relevance and resilience in an ever-evolving world.
The post Reinventing the Fortress: using Open Recognition to enhance ‘standards’ and ‘rigour’ first appeared on Open Thinkering.
Enlarge (credit: Aurich Lawson | Getty Images)
On Thursday, OpenAI announced a plugin system for its ChatGPT AI assistant. The plugins give ChatGPT the ability to interact with the wider world through the Internet, including booking flights, ordering groceries, browsing the web, and more. Plugins are bits of code that tell ChatGPT how to use an external resource on the Internet.
Basically, if a developer wants to give ChatGPT the ability to access any network service (for example: "looking up current stock prices") or perform any task controlled by a network service (for example: "ordering pizza through the Internet"), it is now possible, provided it doesn't go against OpenAI's rules.
Conventionally, most large language models (LLM) like ChatGPT have been constrained in a bubble, so to speak, only able to interact with the world through text conversations with a user. As OpenAI writes in its introductory blog post on ChatGPT plugins, "The only thing language models can do out-of-the-box is emit text."
FreshRSS 
