We emerged with two guiding principles. First, we had learned that certain environments—in particular, those that cause sensory distraction—can more significantly impact neurodivergent users. Therefore, our design should diminish distractions by mitigating, when possible, noise, visual contrast, reflective surfaces and crowds. Second, we understood that we needed a design that gave neurodivergent users the agency of choice.
The importance of those two factors—a dearth of distraction and an abundance of choice—was bolstered in early workshops with the classroom committee and other stakeholders, which occurred at the same time we were conducting our research. Some things didn’t come up in our research but were made quite clear in our conversations with faculty members, students from the neurodivergent community and other stakeholders. That feedback greatly influenced the design of the Young Classroom.
We ended up blending the two concepts. The main academic space utilizes traditional tables and chairs, albeit in a variety of heights and sizes, while the peripheral classroom spaces use an array of less traditional seating and table configurations, similar to the radical approach.
This post summarises a fascinating webinar I had with Rachel Higginson discussing the elements of building belonging in our settings.
We know that belonging is important and one of the ways to make this explicit in our settings is to consider what it takes to cultivate an inclusive environment where each individual feels valued and understood.
Rachel has spent several years working with young people, particularly those on the periphery of education to help them back into mainstream education and participating in class, along with their peers.
Rachel’s work helping young people to integrate back into education resulted in schools requesting support and resources to embed inclusion within their settings. As a result, Finding My Voice has evolved into a broader curriculum development framework.
This week, as I kick off the 20th cohort of my AI-Learning Design bootcamp, I decided to do some analysis of the work habits of the hundreds of amazing AI-embracing instructional designers who I’ve worked with over the last year or so.
My goal was to answer the question: which AI tools do we use most in the instructional design process, and how do we use them?
Here’s where we are in September, 2024:
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Developing Your Approach to Generative AI — from scholarlyteacher.com by Caitlin K. Kirby, Min Zhuang, Imari Cheyne Tetu, & Stephen Thomas (Michigan State University)
As generative AI becomes integrated into workplaces, scholarly work, and students’ workflows, we have the opportunity to take a broad view of the role of generative AI in higher education classrooms. Our guiding questions are meant to serve as a starting point to consider, from each educator’s initial reaction and preferences around generative AI, how their discipline, course design, and assessments may be impacted, and to have a broad view of the ethics of generative AI use.
AI technology tools hold remarkable promise for providing more accessible, equitable, and inclusive learning experiences for students with disabilities.
In a busy classroom, it can be daunting to meet the varied learning needs of all your students. Knowing you’re also responsible for implementing instructional accommodations and modifications in students’ IEPs and 504 plans can make it feel even more challenging. But with the right information, you can provide these important supports to help all students thrive.
Here are key concepts to keep in mind and steps you can take to implement accommodations and modifications for your students.
BALTIMORE — What if your child didn’t go to school?
Believe it or not, some parents don’t send their children to school five days a week, and it’s called unschooling.
It is a growing and sometimes controversial approach to homeschooling.
Rather than using a defined curriculum, unschooling parents trust their kids to learn organically. Unschoolers are focused more on the experimental process of learning and becoming educated, rather than with “doing or going to school.”
Public schools are particularly vulnerable to pressure, Cuban said on a call with EdSurge. That’s because national problems tend to become school ones, Cuban says. Schools have to walk a “tightrope,” striking a balance that is both stable for students and able to adapt to changes in the broader society, he says.
Pressure on schools to respond to new issues often ends up altering curricula or introducing new courses, because that’s the easiest part of the public education system to change, Cuban argues. But classrooms are isolated from the superintendent’s office, the school board and other “policy elites” who push change, he says.
Every teacher at her school, the Health Sciences High and Middle College, in San Diego, shares in the responsibility of teaching students literacy skills, regardless of the subject they teach. That’s because so many students, even incoming ninth graders, arrive at the school without basic reading skills, according to Douglas Fisher, an administrator at the school. While some students also receive one-on-one remediation, Fisher said that research shows those interventions aren’t enough to close the gap.
“We have kids that on our benchmark knowledge assessments are scoring what is the equivalent of second grade, first grade, fourth grade,” said Fisher, who is also a professor and chair of educational leadership at San Diego State University. Yet, by the time students graduate, he said, the goal at the secondary school is that they have “reading levels ready for college.”
The landscape of education is on the brink of a profound transformation, driven by rapid advancements in artificial intelligence. This shift was highlighted recently by Andrej Karpathy’s announcement of Eureka Labs, a venture aimed at creating an “AI-native” school. As we look ahead, it’s clear that the integration of AI in education will reshape how we learn, teach, and think about schooling altogether.
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Traditional textbooks will begin to be replaced by interactive, AI-powered learning materials that adapt in real-time to a student’s progress.
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As we approach 2029, the line between physical and virtual learning environments will blur significantly.
Curriculum design will become more flexible and personalized, with AI systems suggesting learning pathways based on each student’s interests, strengths, and career aspirations. … The boundaries between formal education and professional development will blur, creating a continuous learning ecosystem.
Picking the right projector for school can be a tough decision as the types and prices range pretty widely. From affordable options to professional grade pricing, there are many choices. The problem is that the performance is also hugely varied. This guide aims to be the solution by offering all you need to know about buying the right projector for school where you are.
Luke covers a variety of topics including:
Types of projectors
Screen quality
Light type
Connectivity
Pricing
From DSC: I posted this because Luke covered a variety of topics — and if you’re set on going with a projector, this is a solid article. But I hesitated to post this, as I’m not sure of the place that projectors will have in the future of our learning spaces. With voice-enabled apps and appliances continuing to be more prevalent — along with the presence of AI-based human-computer interactions and intelligent systems — will projectors be the way to go? Will enhanced interactive whiteboards be the way to go? Will there be new types of displays? I’m not sure. Time will tell.
Since AI in education has been moving at the speed of light, we built this AI Tools in Education database to keep track of the most recent AI tools in education and the changes that are happening every day. This database is intended to be a community resource for educators, researchers, students, and other edtech specialists looking to stay up to date. This is a living document, so be sure to come back for regular updates.
The day started out with a short talk about AI (slides). Some of it is my usual schtick where I do a bit of Q&A with folks around myths and misunderstandings of generative AI in order to establish some common ground. These are often useful both in setting the tone and giving folks a sense of how I come to explore generative AI: with a mixture of humor, concern, curiosity, and of course, cat pics.
From there, we launched into a series of mini-workshops where folks had time to first play around with some previously created prompts around teaching and learning before moving onto prompts for administrative work. The prompts and other support materials are in this Workshop Resource Document. The goal was to just get them into using one or more AI tools with some useful prompts so they can learn more about its capabilities.
The Edtech Insiders Rundown of ASU+GSV 2024 — from edtechinsiders.substack.com by by Sarah Morin, Alex Sarlin, and Ben Kornell And more on Edtech Insiders+, upcoming events, Gauth, AI Reading Tutors, The Artificial Intelligence Interdisciplinary Institute, and TeachAI Policy Resources
Alex Sarlin
4. Everyone is Edtech Now This year, in addition to investors, entrepreneurs, educators, school leaders, university admins, non-profits, publishers, and operators from countless edtech startups and incumbents, there were some serious big tech companies in attendance like Meta, Google, OpenAI, Microsoft, Amazon, Tiktok, and Canva. Additionally, a horde of management consultancies, workforce organizations, mental health orgs, and filmmakers were in attendance.
Edtech continues to expand as an industry category and everyone is getting involved.
It was such a delight to chat with Ana. She’s brilliant and passionate, a talented educator, and an advocate for better ways of learning for children and adults. We cover ways to transform schools so that students get real-world skills, learn resilience and how to embrace challenges, and are prepared for an unpredictable future. And we go hard on why we must keep learning no matter our age, become generalists, and leverage technology in order to adapt to the fast-changing world.
The Texas Tribune reports an “automated scoring engine” that utilizes natural language processing — the technology that enables chatbots like OpenAI’s ChatGPT to understand and communicate with users — is being rolled out by the Texas Education Agency (TEA) to grade open-ended questions on the State of Texas Assessments of Academic Readiness (STAAR) exams. The agency is expecting the system to save $15–20 million per year by reducing the need for temporary human scorers, with plans to hire under 2,000 graders this year compared to the 6,000 required in 2023.
Debating About AI: An Easy Path to AI Awareness and Basic Literacy — from stefanbauschard.substack.com by Stefan Bauschard If you are an organization committed to AI literacy, consider sponsoring some debate topics and/or debates next year and expose thousands of students to AI literacy.
Resolved: Teachers should integrate generative AI in their teaching and learning.
The topic is simple but raises an issue that students can connect with.
While helping my students prepare and judging debates, I saw students demonstrate an understanding of many key issues and controversies.
These included—
*AI writing assessment/grading
*Bias
*Bullying
*Cognitive load
*Costs of AI systems
*Declining test scores
*Deep fakes
*Differentiation
*Energy consumption
*Hallucinations
*Human-to-human connection
*Inequality and inequity in access
*Neurodiversity
*Personalized learning
*Privacy
*Regulation (lack thereof)
*The future of work and unemployment
*Saving teachers time
*Soft skills
*Standardized testing
*Student engagement
*Teacher awareness and AI training; training resource trade-offs
*Teacher crowd-out
*Transparency and explainability
*Writing detectors (students had an exaggerated sense of the workability of these tools).
How Early Adopters of Gen AI Are Gaining Efficiencies — from knowledge.wharton.upenn.edu by Prasanna (Sonny) Tambe and Scott A. Snyder; via Ray Schroeder on LinkedIn Enterprises are seeing gains from generative AI in productivity and strategic planning, according to speakers at a recent Wharton conference.
Its unique strengths in translation, summation, and content generation are especially useful in processing unstructured data. Some 80% of all new data in enterprises is unstructured, he noted, citing research firm Gartner. Very little of that unstructured data that resides in places like emails “is used effectively at the point of decision making,” he noted. “[With gen AI], we have a real opportunity” to garner new insights from all the information that resides in emails, team communication platforms like Slack, and agile project management tools like Jira, he said.
Here are 6 YouTube channels I watch to stay up to date with AI. This list will be useful whether you’re a casual AI enthusiast or an experienced programmer.
1. Matt Wolfe: AI for non-coders
This is a fast-growing YouTube channel focused on artificial intelligence for non-coders. On this channel, you’ll find videos about ChatGPT, Midjourney, and any AI tool that it’s gaining popularity.
#3 Photomath
Photomath is a comprehensive math help app that provides step-by-step explanations for a wide range of math problems, from elementary to college level. Photomath is only available as a mobile app. (link)
Features:
Get step-by-step solutions with multiple methods to choose from
Scan any math problem, including word problems, using the app’s camera
Access custom visual aids and extra “how” and “why” tips for deeper understanding
Google researchers have developed a new artificial intelligence system that can generate lifelike videos of people speaking, gesturing and moving — from just a single still photo. The technology, called VLOGGER, relies on advanced machine learning models to synthesize startlingly realistic footage, opening up a range of potential applications while also raising concerns around deepfakes and misinformation.
I’m fascinated by the potential of these tools to augment and enhance our work and creativity. There’s no denying the impressive capabilities we’re already seeing with text generation, image creation, coding assistance, and more. Used thoughtfully, AI can be a powerful productivity multiplier.
At the same time, I have significant concerns about the broader implications of this accelerating technology, especially for education and society at large. We’re traversing new ground at a breakneck pace, and it’s crucial that we don’t blindly embrace AI without considering the potential risks.
My worry is that by automating away too many tasks, even seemingly rote ones like creating slide decks, we risk losing something vital—humanity at the heart of knowledge work.
Nvidia has announced a partnership with Hippocratic AI to introduce AI “agents” aimed at replacing nurses in hospitals. These AI “nurses” come at a significantly low cost compared to human nurses and are purportedly intended to address staffing issues by handling “low-risk,” patient-facing tasks via video calls. However, concerns are raised regarding the ethical implications and effectiveness of replacing human nurses with AI, particularly given the complex nature of medical care.
A glimpse of the future of AI at work:
I got early access to Devin, the “AI developer” – it is slow & breaks often, but you can start to see what an AI agent can do.
It makes a plan and executes it autonomously, doing research, writing code & debugging, without you watching. pic.twitter.com/HHBQQDQZ9q
1,444
The number of students who were enrolled at Notre Dame College in fall 2022, down 37% from 2014. The Roman Catholic college recently said it would close after the spring term, citing declining enrollment, along with rising costs and significant debt.
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The number of academic programs that Valparaiso University may eliminate. Eric Johnson, the Indiana institution’s provost, said it offers too many majors, minors and graduate degrees in relation to its enrollment.
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A couple of other items re: higher education that caught my eye were:
University administrators see the need to implement education technology in their classrooms but are at a loss regarding how to do so, according to a new report.
The College Innovation Network released its first CIN Administrator EdTech survey today, which revealed that more than half (53 percent) of the 214 administrators surveyed do not feel extremely confident in choosing effective ed-tech products for their institutions.
“While administrators are excited about offering new ed-tech tools, they are lacking knowledge and data to help them make informed decisions that benefit students and faculty,” Omid Fotuhi, director of learning and innovation at WGU Labs, which funds the network, saidin a statement.
From DSC: I always appreciated our cross-disciplinary team at Calvin (then College). As we looked at enhancing our learning spaces, we had input from the Teaching & Learning Group, IT, A/V, the academic side of the house, and facilities. It was definitely a team-based approach. (As I think about it, it would have been helpful to have more channels for student feedback as well.)
Optionality. In my keynote, I pointed out that the academic calendar and credit hour in higher ed are like “shelf space” on the old television schedule that has been upended by streaming. In much the same way, we need similar optionality to meet the challenges of higher ed right now: in how students access learning (in-person, hybrid, online) to credentials (certificates, degrees) to how those experiences stack together for lifelong learning.
Culture in institutions. The common thread throughout the conference was how the culture of institutions (both universities and governments) need to change so our structures and practices can evolve. Too many people in higher ed right now are employing a scarcity mindset and seeing every change as a zero-sum game. If you’re not happy about the present, as many attendees suggested you’re not going to be excited about the future.
WASHINGTON, Feb. 6, 2024 /PRNewswire/ — While three-quarters of higher-education trustees (83%), faculty (81%) and administrators (76%) agree that generative artificial intelligence (GenAI) will noticeably change their institutions in the next five years, community college trustees are more optimistic than their community college counterparts, with (37%) saying their organization is prepared for the change coming compared to just 16% of faculty and 11% of administrator respondents.
Those findings are from the 2023-2024 Digital Learning Pulse Survey conducted by Cengage and Bay View Analytics with support from the Association of Community College Trustees (ACCT), the Association of College and University Educators (ACUE), College Pulse and the United States Distance Learning Association (USDLA) to understand the attitudes and concerns of higher education instructors and leadership.
From DSC: It takes time to understand what a given technology brings to the table…let alone a slew of emerging technologies under the artificial intelligence (AI) umbrella. It’s hard enough when the technology is fairly well established and not changing all the time. But its extremely difficult when significant change occurs almost daily.
The limited staff within the teaching & learning centers out there need time to research and learn about the relevant technologies and how to apply those techs to instructional design. The already stretched thin faculty members need time to learn about those techs as well — and if and how they want to apply them. It takes time and research and effort.
Provosts, deans, presidents, and such need time to learn things as well.
Bottom line: We need to have realistic expectations here.
AI Adoption in Corporate L&D — from drphilippahardman.substack.com by Dr. Philippa Hardman Where we are, and the importance of use cases in enabling change
The headline of the report is that we’ve never seen a technology adopted in enterprise as fast as generative AI. As of November 2023, two-thirds (67%) of survey respondents reported that their companies are using generative AI.
However, the vast majority of AI adopters in enterprise are still in the early stages; they’re experimenting at the edges, rather than making larger-scale, strategic decisions on how to leverage AI to accelerate our progress towards org goals and visions.
The single biggest hurdle to AI adoption in large corporates is a lack of appropriate use cases.
Wagner herself recently relied on the power of collegial conversations to probe the question: What’s on the minds of educators as they make ready for the growing influence of AI in higher education? CT asked her for some takeaways from the process.
We are in the very early days of seeing how AI is going to affect education. Some of us are going to need to stay focused on the basic research to test hypotheses. Others are going to dive into laboratory “sandboxes” to see if we can build some new applications and tools for ourselves. Still others will continue to scan newsletters like ProductHunt every day to see what kinds of things people are working on. It’s going to be hard to keep up, to filter out the noise on our own. That’s one reason why thinking with colleagues is so very important.
We are interested how K-12 education will change in terms of foundational learning. With in-class, active learning designs, will younger students do a lot more intensive building of foundational writing and critical thinking skills before they get to college?
The Human in the Loop: AI is built using math: think of applied statistics on steroids. Humans will be needed more than ever to manage, review and evaluate the validity and reliability of results. Curation will be essential.
We will need to generate ideas about how to address AI factors such as privacy, equity, bias, copyright, intellectual property, accessibility, and scalability.
Have other institutions experimented with AI detection and/or have held off on emerging tools related to this? We have just recently adjusted guidance and paused some tools related to this given the massive inaccuracies in detection (and related downstream issues in faculty-elevated conduct cases)
Even though we learn repeatedly that innovation has a lot to do with effective project management and a solid message that helps people understand what they can do to implement change, people really need innovation to be more exciting and visionary than that. This is the place where we all need to help each other stay the course of change.
I have been talking to a lot of people about Generative AI, from teachers to business executives to artists to people actually building LLMs. In these conversations, a few key questions and themes keep coming up over and over again. Many of those questions are more informed by viral news articles about AI than about the real thing, so I thought I would try to answer a few of the most common, to the best of my ability.
I can’t blame people for asking because, for whatever reason, the companies actually building and releasing Large Language Models often seem allergic to providing any sort of documentation or tutorial besides technical notes. I was given much better documentation for the generic garden hose I bought on Amazon than for the immensely powerful AI tools being released by the world’s largest companies. So, it is no surprise that rumor has been the way that people learn about AI capabilities.
Currently, there are only really three AIs to consider: (1) OpenAI’s GPT-4 (which you can get access to with a Plus subscription or via Microsoft Bing in creative mode, for free), (2) Google’s Bard (free), or (3) Anthropic’s Claude 2 (free, but paid mode gets you faster access). As of today, GPT-4 is the clear leader, Claude 2 is second best (but can handle longer documents), and Google trails, but that will likely change very soon when Google updates its model, which is rumored to be happening in the near future.
Scenario 1: Fully Digitalized Law School Scenario 2: Blended Law School Experience Scenario 3: Specialized Legal Education Scenario 4: Decentralized Legal Education
In the decentralized legal education scenario, the traditional model of law schools is disrupted by the emergence of alternative education platforms and micro-credentialing. The concept of a law degree is replaced by a more flexible and personalized approach to legal education. Students can choose from an array of legal courses offered by various providers, including universities, law firms, online platforms, and even government agencies.
A new planetarium project in the UK has the potential to revolutionise education and entertainment. Reece Webb reports.
Many integrators will work on a career defining project, and for Amir Khosh, a new, one-of-a-kind planetarium project nestled in the heart of Nottinghamshire, UK, has sat at the centre of his world.
A project more than five years in the making, ST Engineering Antycip will be part of the large-scale developmemt that is the Sherwood Observatory, which aims to drive education enrichment and visitor attraction in marginalised communities.
The majority of survey participants report increased student demand for online and hybrid learning juxtaposed with decreased demand for face-to-face courses and programs. Most participants also say that their institutions are aligning or working to align their strategic priorities to meet this demand. Notable findings from the 50+-page report include:
Face-to-Face enrollment is stagnant or declining.
Online and hybrid enrollment is growing.
Institutions are quickly aligning their strategic priorities to meet online/hybrid student demand.
The Homework Apocalypse — from oneusefulthing.org by Ethan Mollick Fall is going to be very different this year. Educators need to be ready.
Excerpt:
Students will cheat with AI. But they also will begin to integrate AI into everything they do, raising new questions for educators. Students will want to understand why they are doing assignments that seem obsolete thanks to AI. They will want to use AI as a learning companion, a co-author, or a teammate. They will want to accomplish more than they did before, and also want answers about what AI means for their future learning paths. Schools will need to decide how to respond to this flood of questions.
The challenge of AI in education can feel abstract, so to understand a bit more about what is going to happen, I wanted to examine some common assignment types.
From DSC: The Bible talks about listening quite frequently. The authors ask people to listen to what is being communicated.
Proverbs 16:20
Whoever gives heed to instruction prospers,
and blessed is the one who trusts in the Lord.
Unfortunately, it often involves people NOT listening to the LORD and/or to others and, instead, going their/our own way. In my own life, things don’t go so well when I do that. I think the same is true on a more general/corporate level as well.
For example, Israel in ancient days thought and behaved this way too. Read 1 Kings and 2 Kings to see what I mean. They didn’t listen to the LORD. They didn’t listen to instruction. They thought they knew it all. They didn’t give credit to Whom credit was due. They made up their own gods and worshipped the things that they created.
The LORD wanted to bless them — and us. But they didn’t — and we still don’t — want to listen and submit to His will at times (even though His will is meant to BLESS US).
I used to see the LORD looking down from heaven, with a stern or disappointed look on His face. He was tapping His foot, and had His arms folded. I imagined Him saying, “Daniel, get your stuff together!!!” I didn’t see Him as being on my team.
Through the years He has shown me that He IS on my team and that He is active in my heart, mind, and life. He is full of grace, truth, patience, forgiveness, vulnerable love, and wisdom. He’s awesome. I love Him and His ways — but that’s taken me decades to be able to say that.
He wants what is best for us. He gave us gifts and wants us to use those gifts to serve others.