Giving ELA Lessons a Little Edtech Boost — from edutopia.org by Julia Torres Common activities in English language arts classes such as annotation and note-taking can be improved through technology.
6 ELA Practices That Can Be Enhanced by EdTech
Book clubs.
Collective note-taking.
Comprehension checks.
Video lessons.
..and more
Using Edtech Tools to Differentiate Learning— from edutopia.org by Katie Novak and Mary E. Pettit Teachers can use tech tools to make it easier to give students choice about their learning, increasing engagement.
The core problem, witnesses at the hearing said, is that teacher-preparation programs treat all teachers—and, by extension, students—the same, asking teachers to be “everything to everybody.”
“The current model of teaching where one teacher works individually with a group of learners in a classroom—or a small box inside of a larger box that we call school—promotes unrealistic expectations by assuming individual teachers working in isolation can meet the needs of all students,” said Greg Mendez, the principal of Skyline High School in Mesa, Ariz.
From DSC: I’ve long thought teacher education programs could and should evolve (that’s why I have a “student teacher/teacher education” category on this blog). For example, they should inform their future teachers about the science of learning and how to leverage edtech/emerging technologies into their teaching methods.
But regardless of what happens in our teacher prep programs, the issues about the current PreK-12 learning ecosystem remain — and THOSE things are what we need to address. Or we will continue to see teachers leave the profession.
Are we straight-jacketing our teachers and administrators by having them give so many standardized tests and then having to teach to those tests? (We should require our legislators to teach in a classroom before they can draft any kind of legislation.)
Do teachers have the joy they used to have? The flexibility they used to have? Do students?
Do students have choice and voice?
etc.
Also, I highlighted the above excerpt because we can’t expect a teacher to do it all. They can’t be everything to everybody. It’s a recipe for burnout and depression. There are too many agendas coming at them.
We need to empower our current teachers and listen very carefully to the changes that they recommend. We should also listen very carefully to what our STUDENTS are recommending as well!
The XQ Institute shares this mindset as part of our mission to reimagine the high school learning experience so it’s more relevant and engaging for today’s learners, while better preparing them for the future.We see AI as a tool with transformative potential for educators and makers to leverage — but only if it’s developed and implemented with ethics, transparency and equity at the forefront. That’s why we’re building partnerships between educators and AI developers to ensure that products are shaped by the real needs and challenges of students, teachers and schools. Here’s how we believe all stakeholders can embrace the Department’s recommendations through ongoing collaborations with tech leaders, educators and students alike.
…lead me to the XQ Institute, and I very much like what I’m initially seeing! Here are some excerpts from their website:
Transforming high school isn’t easy, but it is possible. ? Educator @nwallacecxh from XQ’s @CrosstownHigh shares real-world strategies to make learning relevant and meaningful. Ready to see how it’s done? ? https://t.co/xD8hkP33TH
People started discussing what they could do with Notebook LM after Google launched the audio overview, where you can listen to 2 hosts talking in-depth about the documents you upload. Here are what it can do:
Summarization: Automatically generate summaries of uploaded documents, highlighting key topics and suggesting relevant questions.
Question Answering: Users can ask NotebookLM questions about their uploaded documents, and answers will be provided based on the information contained within them.
Idea Generation: NotebookLM can assist with brainstorming and developing new ideas.
Source Grounding: A big plus against AI chatbot hallucination, NotebookLM allows users to ground the responses in specific documents they choose.
…plus several other items
The posting also lists several ideas to try with NotebookLM such as:
Idea 2: Study Companion
Upload all your course materials and ask NotebookLM to turn them into Question-and-Answer format, a glossary, or a study guide.
Get a breakdown of the course materials to understand them better.
“Google’s AI note-taking app NotebookLM can now explain complex topics to you out loud”
With more immersive text-to-video and audio products soon available and the rise of apps like Suno AI, how we “experience” Generative AI is also changing from a chatbot of 2 years ago, to a more multi-modal educational journey. The AI tools on the research and curation side are also starting to reflect these advancements.
1. Upload a variety of sources for NotebookLM to use.
You can use …
websites
PDF files
links to websites
any text you’ve copied
Google Docs and Slides
even Markdown
You can’t link it to YouTube videos, but you can copy/paste the transcript (and maybe type a little context about the YouTube video before pasting the transcript).
2. Ask it to create resources. 3. Create an audio summary. 4. Chat with your sources.
5. Save (almost) everything.
I finally tried out Google’s newly-announced NotebookLM generative AI application. It provides a set of LLM-powered tools to summarize documents. I fed it my dissertation, and am surprised at how useful the output would be.
The most impressive tool creates a podcast episode, complete with dual hosts in conversation about the document. First – these are AI-generated hosts. Synthetic voices, speaking for synthetic hosts. And holy moly is it effective. Second – although I’d initially thought the conversational summary would be a dumb gimmick, it is surprisingly powerful.
4 Tips for Designing AI-Resistant Assessments — from techlearning.com by Steve Baule and Erin Carter As AI continues to evolve, instructors must modify their approach by designing meaningful, rigorous assessments.
As instructors work through revising assessments to be resistant to generation by AI tools with little student input, they should consider the following principles:
Incorporate personal experiences and local content into assignments
Ask students for multi-modal deliverables
Assess the developmental benchmarks for assignments and transition assignments further up Bloom’s Taxonomy
He added that he wants to avoid a global “AI divide” and that Google is creating a $120 million Global AI Opportunity Fund through which it will “make AI education and training available in communities around the world” in partnership with local nonprofits and NGOs.
Google on Thursday announced new updates to its AI note-taking and research assistant, NotebookLM, allowing users to get summaries of YouTube videos and audio files and even create sharable AI-generated audio discussions…
As we navigate the rapidly evolving landscape of artificial intelligence in education, a troubling trend has emerged. What began as cautious skepticism has calcified into rigid opposition. The discourse surrounding AI in classrooms has shifted from empirical critique to categorical rejection, creating a chasm between the potential of AI and its practical implementation in education.
This hardening of attitudes comes at a significant cost. While educators and policymakers debate, students find themselves caught in the crossfire. They lack safe, guided access to AI tools that are increasingly ubiquitous in the world beyond school walls. In the absence of formal instruction, many are teaching themselves to use these tools, often in less than productive ways. Others live in a state of constant anxiety, fearing accusations of AI reliance in their work. These are just a few symptoms of an overarching educational culture that has become resistant to change, even as the world around it transforms at an unprecedented pace.
Yet, as this calcification sets in, I find myself in a curious position: the more I thoughtfully integrate AI into my teaching practice, the more I witness its potential to enhance and transform education
The urgency to integrate AI competencies into education is about preparing students not just to adapt to inevitable changes but to lead the charge in shaping an AI-augmented world. It’s about equipping them to ask the right questions, innovate responsibly, and navigate the ethical quandaries that come with such power.
AI in education should augment and complement their aptitude and expertise, to personalize and optimize the learning experience, and to support lifelong learning and development. AI in education should be a national priority and a collaborative effort among all stakeholders, to ensure that AI is designed and deployed in an ethical, equitable, and inclusive way that respects the diversity and dignity of all learners and educators and that promotes the common good and social justice. AI in education should be about the production of AI, not just the consumption of AI, meaning that learners and educators should have the opportunity to learn about AI, to participate in its creation and evaluation, and to shape its impact and direction.
3 Improvements, 3 Weeks In (I Think?) — from thebrokencopier.substack.com by Marcus Luther out at The Broken Copier What I think I’m doing better this year as a teacher—plus reasons why I might be…wrong?
So here we go: three ways I think I’ve improved so far this year as a teacher—along with three potential downsides for these shifts in my practice.
What this looks like: as I noted in my beginning-of-year goals, something I realized that I wanted to improve upon this year was consistently and intentionally protecting enough time at the end of each lesson to allow students to reflect on their learning. Along with creating a slide template I could consistently adapt from throughout the year, I knew this would mean creating and maintaining a system in our classroom of “closing with our takeaway”:
As an educator, you’re constantly adapting your teaching to meet the needs of your classroom, but it can be difficult to know everything necessary for effectively supporting your students, including those with learning disabilities.
We’re turning to you, our Edutopia community, to help us shape the content we create around this important topic. Where do you need more guidance in helping students with learning disabilities? Are there specific challenges you face, such as classroom accommodations, identifying learning disabilities early on, or navigating IEPs? Maybe you’re looking for help with differentiated instruction, inclusive teaching practices, or strategies for fostering social-emotional growth in these students.
.. More Guidance for Learning Disabilities Are you looking for resources that have already been published? We maintain a page dedicated entirely toSpecial Education. This resource is updated continuously with our latest articles and videos, offering practical tips and insights from educators like you.
Horizon Three Learning — from gettingsmart.com How might we build the nation’s new learning ecosystem together?
America’s education system was a groundbreaking effort to help a growing nation thrive in the 19th century. Now, 200 years later, the world has changed; the horizon looks drastically different. Collectively, we need to redesign our education system to enable all of our children — and, by extension, our nation — to thrive today and tomorrow.
“Horizon Three” or “H3” names the future-ready system we need, one that is grounded in equity serving learners’ individual strengths and needs as well as the common good. This series provides a glimpse of where H3 is already being designed and built. It also includes provocations about how we might fundamentally reimagine learning for the future ahead.
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:
…
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.
Using Video Projects to Reinforce Learning in Math — from edutopia.org by Alessandra King A collaborative project can help students deeply explore math concepts, explain problem-solving strategies, and demonstrate their learning.
To this end, I assign video projects to my students. In groups of two or three, they solve a set of problems on a topic and then choose one to illustrate, solve, and explain their favorite problem-solving strategy in detail, along with the reasons they chose it. The student-created videos are collected and stored on a Padlet even after I have evaluated them—kept as a reference, keepsake, and support. I have a library of student-created videos that benefit current and future students when they have some difficulties with a topic and associated problems.
AI can help educators focus more on human interaction and critical thinking by automating tasks that consume time but don’t require human empathy or creativity.
Encouraging students to use AI as a tool for learning and creativity can significantly boost their engagement and self-confidence, as seen in examples from student experiences shared in the discussion.
The speakers discuss various aspects of AI, including its potential to augment human intelligence and the need to focus on uniquely human competencies in the face of technological advancements. They also emphasize the significance of student agency, with examples of student-led initiatives and feedback sessions that reveal how young learners are already engaging with AI in innovative ways. The episode underscores the necessity for educators and administrators to stay informed and actively participate in the ongoing dialogue about AI to ensure its effective and equitable implementation in schools.
AI can be a powerful tool to break down language, interest, and accessibility barriers in the classroom, making learning more inclusive and engaging.
Incorporating AI tools in educational settings can help build essential skills that AI can’t replace, such as creativity and problem-solving, preparing students for future job markets.
Right now, high schoolers and college students around the country are experimenting with free smartphone apps that help complete their math homework using generative AI. One of the most popular options on campus right now is the Gauth app, with millions of downloads. It’s owned by ByteDance, which is also TikTok’s parent company.
The Gauth app first launched in 2019 with a primary focus on mathematics, but soon expanded to other subjects as well, like chemistry and physics. It’s grown in relevance, and neared the top of smartphone download lists earlier this year for the education category. Students seem to love it. With hundreds of thousands of primarily positive reviews, Gauth has a favorable 4.8 star rating in the Apple App Store and Google Play Store.
All students have to do after downloading the app is point their smartphone at a homework problem, printed or handwritten, and then make sure any relevant information is inside of the image crop. Then Gauth’s AI model generates a step-by-step guide, often with the correct answer.
From DSC: I do hesitate to post this though, as I’ve seen numerous posting re: the dubious quality of AI as it relates to giving correct answers to math-related problems – or whether using AI-based tools help or hurt the learning process. The situation seems to be getting better, but as I understand it, we still have some progress to make in this area of mathematics.
Educational leaders must reconsider the definition of creativity, taking into account how generative AI tools can be used to produce novel and impactful creative work, similar to how film editors compile various elements into a cohesive, creative whole.
Generative AI democratizes innovation by allowing all students to become creators, expanding access to creative processes that were previously limited and fostering a broader inclusion of diverse talents and ideas in education.
AI-Powered Instructional Design at ASU — from drphilippahardman.substack.com by Dr. Philippa Hardman How ASU’s Collaboration with OpenAI is Reshaping the Role of Instructional Designers
The developments and experiments at ASU provide a fascinating window into two things:
How the world is reimagining learning in the age of AI;
How the role of the instructional designer is changing in the age of AI.
In this week’s blog post, I’ll provide a summary of how faculty, staff and students at ASU are starting to reimagine education in the age of AI, and explore what this means for the instructions designers who work there.
India’s ed-tech unicorn PhysicsWallah is using OpenAI’s GPT-4o to make education accessible to millions of students in India. Recently, the company launched a suite of AI products to ensure that students in Tier 2 & 3 cities can access high-quality education without depending solely on their enrolled institutions, as 85% of their enrollment comes from these areas.
Last year, AIM broke the news of PhysicsWallah introducing ‘Alakh AI’, its suite of generative AI tools, which was eventually launched at the end of December 2023. It quickly gained traction, amassing over 1.5 million users within two months of its release.
What An Agent Is
Agents are computer programs that can autonomously perform tasks, make decisions and interact with humans or other computers. There are many different types of agents, and they are designed to achieve specific goals spanning our lives and nearly every industry, making them an integral and unstoppable part of our future.
Learning: AI agents will transform education by providing personalized learning experiences such as one-to-one tutoring. ChatGPT and other large language models (LLMs) are providing access to all digital knowledge now. An “agent” would act as a more personalized version of an LLM.
The hacking and control of an AI agent could lead to disastrous consequences, affecting privacy, security, the economy and societal stability. Proactive and comprehensive security strategies are essential to mitigate these risks in the future.
New Microschools for a New School Year — from the74million.org by Kerry McDonald As parent demand for more individualized education options grows, everyday entrepreneurs are stepping up to meet that demand by launching microschools
Microschools and similarly creative schooling options gained increased popularity in the wake of the pandemic, and they continue to gain momentum. Not only are new schools and spaces opening across the U.S. but existing ones are expanding.
New data from VELA, a philanthropic nonprofit organization and entrepreneur community, reveals that over 90 percent of the unconventional learning environments it surveyed had more learners last fall than they did at their launch date, and the median compound rate of growth for these programs was 25 percent a year.
86% of students globally are regularly using AI in their studies, with 54% of them using AI on a weekly basis, the recent Digital Education Council Global AI Student Survey found.
ChatGPT was found to be the most widely used AI tool, with 66% of students using it, and over 2 in 3 students reported using AI for information searching.
Despite their high rates of AI usage, 1 in 2 students do not feel AI ready. 58% reported that they do not feel that they had sufficient AI knowledge and skills, and 48% do not feel adequately prepared for an AI-enabled workplace.
The Post-AI Instructional Designer— from drphilippahardman.substack.com by Dr. Philippa Hardman How the ID role is changing, and what this means for your key skills, roles & responsibilities
Specifically, the study revealed that teachers who reported most productivity gains were those who used AI not just for creating outputs (like quizzes or worksheets) but also for seeking input on their ideas, decisions and strategies.
Those who engaged with AI as a thought partner throughout their workflow, using it to generate ideas, define problems, refine approaches, develop strategies and gain confidence in their decisions gained significantly more from their collaboration with AI than those who only delegated functional tasks to AI.
Leveraging Generative AI for Inclusive Excellence in Higher Education — from er.educause.edu by Lorna Gonzalez, Kristi O’Neil-Gonzalez, Megan Eberhardt-Alstot, Michael McGarry and Georgia Van Tyne Drawing from three lenses of inclusion, this article considers how to leverage generative AI as part of a constellation of mission-centered inclusive practices in higher education.
The hype and hesitation about generative artificial intelligence (AI) diffusion have led some colleges and universities to take a wait-and-see approach.Footnote1 However, AI integration does not need to be an either/or proposition where its use is either embraced or restricted or its adoption aimed at replacing or outright rejecting existing institutional functions and practices. Educators, educational leaders, and others considering academic applications for emerging technologies should consider ways in which generative AI can complement or augment mission-focused practices, such as those aimed at accessibility, diversity, equity, and inclusion. Drawing from three lenses of inclusion—accessibility, identity, and epistemology—this article offers practical suggestions and considerations that educators can deploy now. It also presents an imperative for higher education leaders to partner toward an infrastructure that enables inclusive practices in light of AI diffusion.
An example way to leverage AI:
How to Leverage AI for Identity Inclusion Educators can use the following strategies to intentionally design instructional content with identity inclusion in mind.
Provide a GPT or AI assistant with upcoming lesson content (e.g., lecture materials or assignment instructions) and ask it to provide feedback (e.g., troublesome vocabulary, difficult concepts, or complementary activities) from certain perspectives. Begin with a single perspective (e.g., first-time, first-year student), but layer in more to build complexity as you interact with the GPT output.
Gen AI’s next inflection point: From employee experimentation to organizational transformation — from mckinsey.com by Charlotte Relyea, Dana Maor, and Sandra Durth with Jan Bouly As many employees adopt generative AI at work, companies struggle to follow suit. To capture value from current momentum, businesses must transform their processes, structures, and approach to talent.
To harness employees’ enthusiasm and stay ahead, companies need a holistic approach to transforming how the whole organization works with gen AI; the technology alone won’t create value.
Our research shows that early adopters prioritize talent and the human side of gen AI more than other companies (Exhibit 3). Our survey shows that nearly two-thirds of them have a clear view of their talent gaps and a strategy to close them, compared with just 25 percent of the experimenters. Early adopters focus heavily on upskilling and reskilling as a critical part of their talent strategies, as hiring alone isn’t enough to close gaps and outsourcing can hinder strategic-skills development.Finally, 40 percent of early-adopter respondents say their organizations provide extensive support to encourage employee adoption, versus 9 percent of experimenter respondents.
Change blindness — from oneusefulthing.org by Ethan Mollick 21 months later
I don’t think anyone is completely certain about where AI is going, but we do know that things have changed very quickly, as the examples in this post have hopefully demonstrated. If this rate of change continues, the world will look very different in another 21 months. The only way to know is to live through it.
Over the subsequent weeks, I’ve made other adjustments, but that first one was the one I asked myself:
What are you doing?
Why are you doing it that way?
How could you change that workflow with AI?
Applying the AI to the workflow, then asking, “Is this what I was aiming for? How can I improve the prompt to get closer?”
Documenting what worked (or didn’t). Re-doing the work with AI to see what happened, and asking again, “Did this work?”
So, something that took me WEEKS of hard work, and in some cases I found impossible, was made easy. Like, instead of weeks, it takes 10 minutes. The hard part? Building the prompt to do what I want, fine-tuning it to get the result. But that doesn’t take as long now.
