Mary Beth Hertz, a high school teacher, leverages AI to educate her students about the nuances and biases inherent in artificial intelligence. She encourages her students to interact with ChatGPT, fostering a deeper understanding of AI’s strengths and limitations. In her entrepreneurship class, ChatGPT is used as a tool to refine mission statements and business pitch language.
Paul Wilkinson, a teacher of secondary English and social studies, employs AI to devise learning challenges for his students and provide them with comprehensive feedback. He uses AI to create curriculum-based content, formulate rubrics, and offer personalized feedback to each student. He also designed a reflection assignment to enhance students’ metacognitive skills.
Mick McMurray, a teacher specializing in marketing and entrepreneurship, uses ChatGPT as an assistant for student assignments. He crafted a series of ChatGPT prompts for a high school marketing class project, leading to an engaging “choose your own adventure” reading experience for the students.
Of course, the article underscores that while the use of generative AI in K-12 settings is still emerging, it holds the potential to boost student creativity, enhance writing skills, and provide students with a clear understanding of AI’s limitations. The educators involved believe that when used wisely, AI tools can serve as valuable partners in the learning journey.
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In a world increasingly reliant on AI tools, a recent study by the University of Copenhagen reveals a significant cultural bias in the language model ChatGPT. The AI chatbot, which has permeated various sectors globally, from article writing to legal rulings, has been found to predominantly reflect American norms and values, even when queried about other cultures.
For instance, when asked about the importance of interesting work for an average Chinese individual, ChatGPT’s response in English indicated it as “very important” or “of utmost importance”, reflecting American individualistic values rather than the actual Chinese norms. However, when the same question was asked in Chinese, the response was more in line with Chinese values, suggesting that the language used to query the AI significantly influences the response.
This cultural bias in AI tools like ChatGPT has serious implications. As these tools are used globally, the expectation is for a uniform user experience. However, the current situation promotes American values, potentially distorting messages and decisions made based on the AI’s responses. This could lead to decisions that not only misalign with users’ values but may even oppose them.
The researchers attribute this bias to the fact that ChatGPT is primarily trained on data scraped from the internet, where English is the dominant language. They suggest improving the data used to train AI models, incorporating more balanced data without a strong cultural bias.
In the context of education, this study underscores the importance of students and educators identifying biases in generative AI tools. Recognizing these biases is crucial as it can significantly impact their work when using AI tools. For instance, if students use AI tools to research or generate content, cultural bias could skew their understanding or representation of certain topics. Similarly, educators must be aware of these biases to guide students appropriately and ensure a comprehensive and unbiased learning experience.
Moreover, the study serves as a reminder that AI tools are not infallible and should not be used uncritically. It encourages the development of local language models that can provide a more culturally diverse AI landscape. This could lead to more accurate and culturally sensitive responses, enhancing the effectiveness and reliability of AI tools in various fields, including education.
In conclusion, while AI tools like ChatGPT offer numerous benefits, it’s crucial to be aware of their limitations and biases. As we continue to integrate AI into our work and learning environments, we must strive for tools that respect and reflect the diversity of our global community.
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The world of education, specifically K-12, is on the brink of a significant transformation. The catalyst? Generative AI tools. These tools, such as Large Language Models (LLMs) and ChatGPT, are heralding a new era of automation, promising to reshape how we approach administrative and teaching tasks in schools.
Generative AI tools are a generational leap in what we can automate with software. They are not just about replacing human effort but also about creating entirely new kinds of automation. The potential impact on jobs and people is profound, and the pace of change is rapid. For instance, ChatGPT has already amassed over 100 million users in just six months.
The world of education is no stranger to automation. Over the past two centuries, we’ve seen waves of automation that have eliminated certain jobs while creating new ones. This process, while sometimes disruptive, has ultimately led to increased prosperity and efficiency.
For school administrators and teachers, generative AI tools could automate many tasks, freeing up time for more strategic and student-focused activities. For example, these tools could automate administrative tasks such as scheduling, record-keeping, and communication with parents. They could also assist teachers with tasks such as grading, lesson planning, and even providing personalized learning support for students.
However, the adoption of these tools is not without challenges. The tools that people use to do their jobs are complicated and very specialized, embodying a lot of work and institutional knowledge. Replacing or automating any of these tools and tasks is not trivial. There’s a huge difference between an amazing demo of a transformative technology and something that a big complicated organization can use.
Moreover, while generative AI tools can answer ‘anything’, the answer might be wrong. They are not databases but pattern matchers. They can produce answers that fit the pattern of the question but may not be factually correct. This means that while they can automate many tasks, their outputs still need to be checked.
Despite these challenges, the potential benefits of generative AI tools in K-12 education are immense. They could lead to more efficient administration, more personalized learning, and ultimately, better educational outcomes for students. However, it’s important to remember that these tools are not a magic bullet. They are just another wave of automation, and their successful implementation will require careful planning, training, and adjustment.
In conclusion, generative AI tools hold great promise for automating tasks in K-12 education. However, their adoption will require careful planning and a clear understanding of their capabilities and limitations. As with any new technology, the key to success will be in how well we integrate these tools into our existing systems and processes, and how well we adapt to the new ways of working they enable.
FAQ
What is generative AI? Generative AI, including Large Language Models (LLMs) and ChatGPT, represents a significant change in what we can automate with software. It’s not just about replacing human effort but also about creating entirely new kinds of automation.
How fast is the adoption of generative AI tools like ChatGPT? The adoption is happening very rapidly. For instance, ChatGPT has amassed over 100 million users in just six months.
What is the potential impact of generative AI on jobs? Generative AI tools have the potential to automate many tasks, which could lead to job displacement. However, similar to previous waves of automation, they could also create new types of jobs.
What challenges are associated with the adoption of generative AI tools? The tools people use to do their jobs are complicated and very specialized, embodying much work and institutional knowledge. Replacing or automating any of these tools and tasks is not trivial. Additionally, while generative AI tools can answer ‘anything,’ the answer might be wrong as they are not databases but pattern matchers.
What is the potential of generative AI tools in the education sector? In the education sector, generative AI tools could automate many administrative tasks and assist teachers with tasks such as grading, lesson planning, and even providing personalized learning support for students.
What is the future of generative AI tools? The future of generative AI tools is likely to involve more automation, but also more integration with existing systems and processes. Their successful implementation will require careful planning, training, and adjustment.
What is the ‘Lump of Labour’ fallacy? The ‘Lump of Labour’ fallacy is the misconception that there is a fixed amount of work to be done and that if a machine takes some work, there will be less work for people. However, if it becomes cheaper to use a machine to make, say, a pair of shoes, then the shoes are cheaper, more people can buy shoes, and they have more money to spend on other things besides, and we discover new things we need or want, and new jobs.
What is the Jevons Paradox? The Jevons Paradox suggests that as technological progress increases the efficiency with which a resource is used, the total consumption of that resource may increase rather than decrease. This paradox has been applied to white-collar work for 150 years.
What is AGI (Artificial General Intelligence)? AGI refers to a type of artificial intelligence that is as capable as a human at any intellectual task. If we had AGI, it could potentially change everything, including overriding all the complexity of real people, real companies, and the real economy. However, as of now, we do not have AGI, and without that, we have only another wave of automation.
How can generative AI tools help in personalized learning? Generative AI tools can provide personalized learning support for students by adapting to each student’s learning style and pace. They can provide additional explanations, practice problems, and feedback, making learning more effective and engaging.
Can generative AI tools replace teachers? While generative AI tools can assist with tasks such as grading and lesson planning, they are not a replacement for teachers. Teachers play a crucial role in motivating students, managing the classroom, and providing emotional support, among other things. These are aspects that cannot be automated.
What is the role of generative AI tools in administrative tasks? Generative AI tools can automate administrative tasks such as scheduling, record-keeping, and communication with parents. This can free up time for school administrators to focus on more strategic tasks.
What is the difference between a database and a pattern matcher in the context of generative AI tools? While databases store and retrieve factual information, pattern matchers, like generative AI tools, generate responses based on patterns they’ve learned from data. This means they can produce answers that fit the pattern of the question but may not be factually correct.
What is the importance of careful planning and training in adopting generative AI tools? The successful implementation of generative AI tools requires careful planning and training. This is because these tools must be integrated into existing systems and processes, and users need to understand their capabilities and limitations.
What does it mean that generative AI tools are not a magic bullet? This means that while generative AI tools hold great promise, they are not a solution to all problems. Their successful implementation will require careful planning, training, and adjustment. They are just another wave of automation, and their impact will depend on how well we adapt to the new ways of working they enable.
What is the potential impact of generative AI tools on educational outcomes? By automating administrative tasks and assisting with teaching tasks, generative AI tools could lead to more efficient administration, more personalized learning, and, ultimately, better educational outcomes for students.
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Heading into the second half of 2023, I thought I’d take a minute and review some of my accomplishments thus far. This is mostly for my own benefit as I continue to curate a digital commonplace book.
Also, it scratches my itch to curate all the things. So here we go…
Reading
Yearly Books Goal: 150 books
Pages Read Goal: 50K
Current book count: 59 books
Current page count: 22k
Writing
Blog posts this year: 94
Class papers: Who the hell knows, but it was a lot
Professional Development
Four full-day PD sessions
Two mini-sessions
Numerous one-on-one meetings with teachers
Music
I curate a Spotify playlist every year of great songs I find or rediscover over the course of the year. Here is the 2023 playlist, so far:
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I finished up the Licanius Trilogy this week. What a complex, mind-bending journey into a new realm of fantasy and magic. I came away with a couple of favorite characters and a new way of thinking about how to write epic fantasy.
If you’re on Goodreads or Storygraph, let’s connect and see where our reading journeys take us.
Thanks for taking the time to read this post. If you’ve enjoyed the insights and stories, consider showing your support by subscribing to my weekly newsletter. It’s a great way to stay updated and dive deeper into my content. Alternatively, if you love audiobooks or want to try them, click here to start your free trial with Audible. Your support in any form means the world to me and helps keep this blog thriving. Looking forward to connecting with you more!
In the world of skateboarding, Rodney Mullen is a legend. Known as the godfather of modern street skating, Mullen’s journey from a farm boy in Florida to a world-renowned skateboarder is a testament to the power of creativity, resilience, and individuality. As we navigate a transitional era in education, moving towards more student agency and authentic work, Mullen’s story offers valuable insights.
Growing up, Mullen felt like an outsider until he discovered skateboarding. The sport offered him a sense of freedom and individuality that resonated deeply with him. There were no coaches, no direct opponents – just him and his board. This is a powerful reminder of the importance of student agency in education. Like Mullen, students should have the freedom to explore their interests and passions, learn and grow at their own pace, and express their individuality through their work.
Mullen’s journey was not without challenges. As the sport of skateboarding evolved, he found himself struggling to adapt. However, this setback was also liberating. Freed from the pressure of maintaining his champion status, Mullen was able to explore and create new tricks. This resilience and adaptability are crucial skills for students in today’s rapidly changing world. As educators, we must create learning environments that encourage students to take risks, learn from their mistakes, and continually strive for improvement.
One of the most significant lessons from Mullen’s story is the power of creating something for the sake of creating it. Mullen found joy in innovating and creating new tricks, not for the accolades or fame, but for the sheer love of creation. This is a powerful message for students. In a world that often values grades and test scores above all else, it’s important to remind students that the process of creation and learning is valuable in and of itself.
Mullen’s story also highlights the importance of community and collaboration. In both the skateboarding and hacker communities, respect is earned by taking what others have done, improving upon it, and sharing it back with the community. This ethos of continuous innovation and growth is one that we should strive to foster in our classrooms. By encouraging students to collaborate, share their work, and build upon the ideas of others, we can create a culture of learning that is dynamic, inclusive, and empowering.
As we navigate this transitional era in education, let’s take a page from Rodney Mullen’s book. Let’s create learning environments that value creativity, resilience, individuality, and community. Let’s encourage our students to create for the sake of creating and to find joy in the process of learning. And most importantly, let’s remind them that, like Mullen, they have the power to shape their own learning journeys and to make a meaningful impact on the world around them.
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In a world where information is increasingly digital and accessible, a new law in Mississippi is causing a stir. The law, Mississippi Code 39-3-25, part of House Bill 1315, has effectively banned anyone under the age of 18 from accessing digital materials made available through public and school libraries without explicit parental or guardian permission. This move has sparked a debate about the morality of censorship and the right to access information.
The law, which went into effect on July 1, 2023, has left libraries across the state scrambling to comply. It mandates that vendors providing digital resources must verify that all their materials comply with the state’s definition of “obscenity.” This definition is broad and includes any material that contains representations or descriptions of various sexual acts, cruelty, violence, or anything deemed “likely to be injurious or harmful to a child.”
The implications of this law are far-reaching. Any vendor with materials in their system depicting sexual reproduction, queerness, or even images of nude female breasts – often part of sexual education, reproductive education, and biology and anatomy books for those under 18 – would be out of compliance with the law. As a result, platforms like Hoopla and Overdrive, which are not set up to change access based on age or varying laws by the municipality, may have to shut down access altogether.
This law has been seen by many as a step towards limiting public goods like libraries and creating systems where young people in some states have access to a world of knowledge and resources, while others are shut out entirely. It disproportionately affects those with the least privileges – those in unstable homes, those without regular internet access, and those without active parents or guardians in their lives.
The First Regional Public Library has already posted an announcement on its homepage regarding the changes, and the Vicksburg Public Library is still figuring out how the law will impact its patrons’ access to digital materials. For now, they’ve developed a new system of library card distribution, requiring those under 18 to have parental or guardian consent to access materials.
Mississippi is not the first state to limit access to materials and place the onus of compliance on the vendors. Texas is undergoing similar changes, and it’s likely that this will lead to similar, if not more dire, lockouts of material access for students statewide.
This move by Mississippi and other states highlights the ongoing battle over access to information and the role of libraries in our society. As we continue to navigate the digital age, the question remains: who gets to decide what information is accessible and to whom?
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In the rapidly evolving world of artificial intelligence (AI), we are constantly faced with new challenges and ethical dilemmas. One such issue has recently been brought to light by a study published in The Guardian. The study reveals a concerning bias in AI detection tools, particularly against non-native English speakers.
These AI detection tools are designed to identify whether a piece of text has been written by a human or generated by an AI. They are increasingly being used in academic and professional settings to prevent what some consider a new form of cheating – using AI to write essays or job applications. However, the study found that these tools often incorrectly flag work produced by non-native English speakers as AI-generated.
The researchers tested seven popular AI text detectors using 91 English essays written by non-native speakers. Over half of these essays, written for the Test of English as a Foreign Language (TOEFL), were incorrectly identified as AI-generated. In stark contrast, when essays written by native English-speaking eighth graders in the US were tested, over 90% were correctly identified as human-generated.
The bias seems to stem from how these detectors assess what is human and what is AI-generated. They use a measure called “text perplexity”, which gauges how “surprised” or “confused” a generative language model is when trying to predict the next word in a sentence. Large language models like ChatGPT are trained to produce low perplexity text, which means that if humans use a lot of common words in a familiar pattern in their writing, their work is at risk of being mistaken for AI-generated text. This risk is greater with non-native English speakers, who are more likely to adopt simpler word choices.
The implications of these findings are serious. AI detectors could falsely flag college and job applications as AI-generated, and marginalize non-native English speakers on the internet, as search engines such as Google downgrade what is assessed to be AI-generated content. In education, non-native students bear more risks of false accusations of cheating, which can be detrimental to a student’s academic career and psychological well-being.
In light of these findings, Jahna Otterbacher at the Cyprus Center for Algorithmic Transparency at the Open University of Cyprus suggests a different approach. Instead of fighting AI with more AI, we should develop an academic culture that promotes the use of generative AI in a creative, ethical manner. She warns that AI models like ChatGPT, which are constantly learning from public data, will eventually learn to outsmart any detector.
This study serves as a reminder that as we continue to integrate AI into our lives, we must remain vigilant about its potential unintended consequences. It’s crucial that we continue to question and scrutinize the tools we use, especially when they have the potential to discriminate or cause harm. As we move forward, let’s ensure that our use of AI in education and other sectors is not only innovative but also fair and ethical.
For more details, you can read the full article here.
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Do your students enjoy interacting with AI chatbots? Are they fascinated by the idea of AI-generated content, such as articles, poems, or even code? Do you want to help your students learn how to discern the difference between human and AI-generated content? If you answered yes to any of these questions, consider integrating AI literacy education into your lessons.
AI literacy expands traditional literacy to include new forms of reading, writing, and communicating. It involves understanding how AI systems work, how they generate content, and how to critically evaluate the information they produce. AI literacy empowers people to be critical thinkers and makers, effective communicators, and active citizens in an increasingly digital world.
Think of it this way: Students learn print literacy — how to read and write. But they should also learn AI literacy — how to “read and write” AI-generated messages in different forms, whether it’s a text, an article, a poem, or anything else. The most powerful way for students to put these skills into practice is through both critiquing the AI-generated content they consume and analyzing the AI-generated content they create.
So, how should students learn to critique and analyze AI-generated content? Most leaders in the AI literacy community use some version of the five key questions:
Who created this AI model? Help your students understand that all AI models have creators and underlying objectives. The AI models we interact with were constructed by someone with a particular vision, background, and agenda. Help students understand how they should question both the messages they see, as well the platforms on which messages are shared.
What data was used to train this AI model? Different AI models are trained on different datasets, which can greatly influence their output. Help students recognize how this often comes in the form of new and innovative techniques to capture our attention – sometimes without us even realizing it.
How might different people interpret this AI-generated content? This question helps students consider how all of us bring our own individual backgrounds, values, and beliefs to how we interpret AI-generated messages. For any piece of AI-generated content, there are often as many interpretations as there are viewers.
Which lifestyles, values, and points of view are represented — or missing? Just as we all bring our own backgrounds and values to how we interpret what we see, AI-generated messages themselves are embedded with values and points of view. Help students question and consider how certain perspectives or voices might be missing from a particular AI-generated message.
Why is this AI-generated content being produced? With this question, have students explore the purpose of the AI-generated content. Is it to inform, entertain, or persuade, or could it be some combination of these? Also, have students explore possible motives behind why certain AI-generated content has been produced.
As teachers, we can think about how to weave these five questions into our instruction, helping our students to think critically about AI-generated content. A few scenarios could include lessons where students interact with AI chatbots or any time we ask students to create AI-generated projects. Eventually, as we model this type of critical thinking for students, asking these questions themselves will become second nature to them.
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As the landscape of education continues to evolve in response to global disruptions and digital advancements, blended learning models have surged in popularity. Among these is the flipped classroom model, a strategy that leverages video instruction to mitigate potential obstacles that make it challenging for students to access information presented live. However, I often hear the question, “Can I use the flipped classroom if I don’t assign homework?”
Catlin Tucker explores the evolution of the flipped classroom model and discusses its potential beyond traditional homework assignments. The author reflects on how the concept has transformed over the years and provides valuable insights into its current state.
Tucker emphasizes that the flipped classroom is no longer limited to a mere reversal of in-class and at-home activities. Instead, it has evolved into a more dynamic and interactive learning experience. The traditional model involved students watching video lectures at home and completing practice exercises in the classroom. However, Tucker suggests that educators can now take advantage of various digital tools and instructional strategies to enhance the flipped classroom approach.
One key takeaway from the post is the importance of leveraging technology to make flipped learning more engaging and personalized. Tucker suggests incorporating interactive videos, online discussions, and collaborative projects to foster deeper student engagement. By diversifying the resources and activities, educators can create a more inclusive and interactive learning environment.
Another significant point highlighted by Tucker is the need for intentional planning and scaffolding in a flipped classroom. Educators should design clear guidelines and structures to support students in their independent learning endeavors. This involves providing explicit instructions, organizing content in manageable chunks, and offering continuous guidance throughout the process.
Tucker also explores the concept of differentiation within the flipped classroom. She suggests tailoring instructional materials and activities to meet the diverse needs of students. By providing a range of resources, teachers can support students with different learning styles and abilities, promoting an inclusive and equitable learning environment.
In conclusion, Catlin Tucker’s blog post emphasizes the evolution of the flipped classroom beyond its original concept of homework flipping. By embracing technology, intentional planning, and differentiation, educators can create a more engaging and student-centered learning experience. The flipped classroom has the potential to transform traditional teaching practices and foster deeper understanding and collaboration among students.
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