For the two of us—educators born almost 60 years apart—it’s a marvel to see what generative artificial intelligence (AI) can do. One of us, Professor Edmund W. Gordon, was born in 1921 and has served many roles throughout an 80-plus-year career: from psychologist and minister to civil rights leader and public servant. The other, Eric Tucker, born in 1980, is a parent of school-age children, a special educator, a former superintendent, and a technologist. Despite our different perspectives, this new reality of AI leaves us pondering: If AI can produce something that takes the typical student years, even decades, to master, what does it mean to be educated? 

As the launch of ChatGPT marks its first anniversary, we’re not the only ones asking these questions. Tumult at OpenAI, the non-profit AI research and deployment shop and publisher of ChatGPT whose mission is “to ensure that artificial general intelligence—AI systems that are generally smarter than humans—benefits all of humanity” creates something of an Overton window to consider what broadly distributed benefits for AI might look like in the field of education. 

A Biden administration executive order and report highlights how educators and schools might navigate the rapid expansion of AI, arguably one of the most significant transformations since the War on Poverty, of which Dr. Gordon was a key architect during the Johnson administration.

Dr. Gordon’s scholarship has considered what it means to be human and how technologies amplify learning and development over a career that included contributions to numerous presidential administrations, including Kennedy’s desegregation efforts, Johnson’s creation of Head Start, and Obama’s Promise Neighborhoods. To paraphrase Gordon: Being a learner for life is not about filling a pail but lighting a fire.

In the wake of the public debut of ChatGPT, Claude, and Bard, it’s clear that AI’s influence is here to stay. So while it’s worth understanding the risks—including the potential for AI to disrupt human jobs, metastasize bias, reproduce mistakes, undermine privacy, and cause unintended consequences—it’s also important to understand AI’s possibilities for enhancing human potential and informing educational processes. 

As educators, we’re interested in how these technologies could help students learn in a manner that honors learner variability. How can educators and caregivers orient our work regarding these tools to ensure all children thrive in an uncertain future? While the technology is different, educators have considered these types of questions before. We’ve gone from encyclopedia sets to Google workspaces, from one-room schoolhouses to Zoom seminars. As the storm of AI-fueled transformation makes landfall, we believe educators should understand the emergence of AI as an opportunity to take stock of what matters most for learners in the period ahead. 

What It Means to Educated for the Future

In the face of emerging technological advances, Carl Bereiter and Marlene Scardamalia (2013) considered human competencies that matter in an uncertain world. They elevate the ability to create knowledge, find real-world applications for abstract ideas, understand and operate within complex systems, sustain focus amid multiplying distractions, and engage in collective work.

Similarly, the XQ Institute has identified research-backed goals, or learner outcomes, that students must develop to be successful in the future. These include agility in their ways of thinking and making sense of the world, building collaborative capacities such as self-awareness and social awareness, and cultivating curiosity to become lifelong learners.

Studies show too many U.S. high school graduates need remedial courses in college and don’t master the skills employers increasingly prioritize. XQ is working to change that by redesigning the high school experience. XQ’s Learner Outcomes help educators identify how to engage students deeply in their learning to master the knowledge and skills necessary to meet the challenges—and opportunities—they’ll need for college, career, and any other future success. Within these outcomes are numerous competencies aimed at developing skills such as critical thinking, social awareness, and self-management.

For example, when Eric Tucker co-founded the Edmund W. Gordon Brooklyn Laboratory High School in 2017, the curriculum emphasized the practice and presentation of applied research. For each year of high school, students completed interdisciplinary year-long seminar courses sponsored by the College Board, investigating pressing issues of social concern in various disciplinary contexts, writing research-based essays, and designing and giving presentations as teams and individuals. Students completed research projects on topics they chose—from environmental justice to gun control, affirmative action, and economic mobility—gathering and combining information from various sources, viewing an issue from multiple perspectives, and crafting arguments based on evidence. 

Such competencies are human competencies—abilities that, at present, technology cannot fully replicate. In the face of AI, we, as educators, are the ones who must help all learners cultivate these competencies. We must shift education to focus on human potential, to develop students’ breadth and depth of knowledge, as well as their ability to navigate diverse ideas, people, and cultures. This is not a job a robot or algorithm can perform.

Focusing Education on Human Potential

Instead of practicing tasks that AI will increasingly perform (such as producing a first draft of an essay outline, generating initial lines of code, or preparing a range of preliminary visualizations of a statistical analysis), educators should shift our focus to enhancing uniquely human capabilities—amplifying human potential through technological advancements and beyond. Schools should embrace generative AI and similar tools to increase time spent honing competencies such as framing meaningful questions, contextualizing arguments, and evaluating multiple perspectives.

Dr. Gordon’s scholarly work explores two competencies that are particularly important for educators to focus on: 

Human agency. Agency is the ability to recognize and act in the best interest of yourself and others. Another way to think about it is the ability to hold onto a sense of efficacy and enact your values. Ana Mari Cauce and Gordon (2013) define human agency as the propensity to take action and to be goal-driven. 

Human agency is significant because it enables people to act for the collective good. As Viktor Frankl, the Holocaust survivor and psychologist, captures so beautifully in “Man’s Search for Meaning” (1954), fulfillment ensues “… as the unintended side-effect of one’s personal dedication to a course greater than oneself.” In an era of AI, we can amplify agency by using tools that enhance the ability to act meaningfully in the surrounding world. 

This is particularly true when confronted by complex existential threats like climate change. Educators focusing on student agency can work with students on how to use AI to address environmental challenges. Students might explore how AI can support campaigns to lower energy consumption and greenhouse gas emissions, monitor deforestation, or track carbon removal. The International Society for Technology in Education’s guide, for example, proposes students research and identify a local environmental or sustainability challenge, define the problem in detail, explore how an AI-powered solution might fit into the more extensive solution, and create and test a working prototype. In this example, an agentic learner can practice setting authentic goals and using AI to help solve a real-world problem.

Intellective competence and character. Dr. Gordon coined “intellective competence” (2013) to describe the ability to use knowledge, technique, and values to engage and solve novel problems. He uses the term “intellective character” to reflect that what we want learners to know and be able to do must be instrumental to achieving what we want learners to be and become. Intellectual character implies becoming a good citizen and creatively using imagination to address challenges and improve circumstances.

The ability to make sense of and address such problems sets humans apart from our ever-evolving technological counterparts. For example, Chris Terrill from Crosstown High highlights schools worldwide where students work together to address environmental challenges, big and small. Educators can strengthen intellective competence by engaging students using AI tools for sustainability challenges. Platforms such as Wildlife.ai, Restor, and Zooniverse suggest how AI might help provide insights into environmental challenges such as climate change, protecting ocean ecosystems and wildlife, water and plant conservation, or air quality. Intellective character orients a learner’s urgency, values, and commitments toward environmental justice.

Educators and students in classrooms around the country are exploring future-leaning approaches that resonate with Gordon’s notions of agency and intellective competence. Notably, XQ schools such as Latitude High School in Oakland, Iowa BIG in Cedar Rapids, and the Purdue Polytechnic High Schools in Indiana demonstrate how meaningful projects in which students have a voice in their learning and collaborate with community partners can nurture these competencies. 

As technological breakthroughs, analytic methods, and artificial intelligence (AI) rapidly redefine what it means to be educated, they correspondingly transform how we can measure and inform learning and development. At the Gordon Commission Study Group, we believe that now is the time to accelerate measurement and assessment system innovation to maximize learning and thriving for every learner. We are working to study the best of assessment, data, and AI practice, technology, and policy; consider future design needs and opportunities for educational systems; and generate recommendations to better meet the needs of students, families, educators, and society.

The emergence of generative AI signals a sea change for what it means to be educated. Our challenge to fellow educators is to join us in rethinking what it means to learn and thrive, given AI-powered tools. Our combined 100-plus years of experience as parents, educators, and applied researchers lends us confidence. We can embrace agency, encourage intellective character, and foster the abilities that shape us as individuals and help us create a healthy, just, and sustainable world.

The post What Educators and Families Should Prioritize in the Age of AI appeared first on Getting Smart.

And oftentimes, they were doing this work with little cognitive and emotional support.

Dr. Carmen Garcia, president of CCSS, Superintendent of Morgan Hill Unified School District and an incredibly thoughtful and kind leader, welcomed the group with one sentiment; “being a superintendent is lonely”. Because no matter how big your team is, the high-pressure, highly-public, and highly responsible role of superintendent has little room for mistakes. 

In the education world, we’ve seen ad nauseam the ways educators can use AI to produce lesson plans, quizzes, and report cards. But I would argue, the most important potential of AI isn’t to enhance human productivity. It’s to enhance and support human thinking. 

So at CCSS, I chose to prepare our Superintendents to use AI as the thought partner they’ve always wanted, in a world where leading is a lonely job. 

This 2-part article is about AI’s cognitive abilities as a thought partner.

In my last piece of this series, I mapped AI’s capabilities to Bloom’s taxonomy, differentiating the competencies of AI from humans. My hope is that readers will see what humans can double down on as their unique advantage, while also identifying a new standard for quality of thought.

The second part provides ideas for how leaders can train an AI thought partner to represent whoever they want – a critic, a twin, a mentor, a philosopher, or a guide. 

In my last piece of this series, I mapped AI’s capabilities to Bloom’s taxonomy where we learned that AI’s splotchy cognitive competencies can help us: 

• explain the human advantage over AI 
• depict AI as a cognitive partner
• identify ways learners might use AI and be duped by AI
• narrate how AI will elevate our standards in education for the production of content, ideas, and discourse

Now, we’ll identify how leaders can finally have the thought partner they’ve always wanted. 

Leaders are often faced with complex decision-making. It isn’t easy to expect others in their ecosystem to be able to provide a full evaluation of the situation or the final decision, because the leader often has more information. Collaborative decision making is always an excellent strategy to involve more stakeholders, but that can also fail if the stakeholders are uninformed or the decision needs to be made quickly. 

So in the moments when a leader needs to make a decision, help her collaborators make a decision, or evaluate a decision she made, who does she turn to?

Imagine if every leader had a personal coach who was critical when she needed feedback, a twin when she needed efficiency, and a philosopher when she needed inspiration. Imagine that this guide knew everything about the leader, her ecosystem, her stakeholders, and her problems.

During my keynote at CCSS, the thoughtful Dr. César Morales, Ventura County Superintendent, said he had a lightbulb moment at this point. Although he didn’t feel comfortable producing content on ChatGPT, he realized he could have it critique his work. And that completely changed his perspective on AI. 

Breaking Down Complex Decision Making

So how do we do this? There are ways to literally create a digital twin using AI. In fact, my friend Bodo built two with his kids using my friend Dima’s AI platform. But let’s consider ChatGPT as our main tool.

Let’s start by breaking down complex decision making. 

To make a difficult decision (or write a letter to the board, advocate for a staff member, produce a business report, etc. etc.), leaders have to gather and analyze the appropriate information from various sources first. We can equate this to the “empathy” stage of design thinking. Without analyzing information from all sides, it’s impossible to conceive a wise decision or prioritize the components of the decision. 

As leaders brainstorm a solution to their problem, they should explore alternative perspectives and generate scenarios that assess the risk, trade-offs, and predict the response. If leaders are not considering what could happen if this decision were made, they may run into bigger problems. 

These components work much like Bloom’s in that they’re more of a spiral that volley back and forth between each other. In sum, complex decision making is made up of gathering information, clarifying complex concepts, exploring alternative perspectives, facilitating brainstorming, analyzing data, and generating scenarios and predictions.

But the reality is that leaders don’t always have time or the skill to make these levels of assessments before they execute.

Enter, AI. 

In addition to asking AI to brainstorm the decision for us, we can ask AI to analyze the decision we may want to make. Remember that AI cannot make meaning so humans must always make their own judgments. Here are my go-to questions for complex decisions.

These questions allow teams to quickly iterate and adapt their decisions before executing. They allow us to simulate outcomes and consider alternatives we may never have thought of. And most importantly, they equip us with strategies to improve our thinking that we can potentially learn from for future decisions. 

This, of course, is my main thesis across these articles: AI can help us become better thinkers.

Context Setting 

To set up a cognitive friend on ChatGPT, we first need to set clear context for our ecosystem using the four Ps, before you even ask my go-to questions. 

Place: Tell AI what makes up your ecosystem from the size of the organization to the history it’s had. 

People: Describe who your stakeholders are and be as detailed as possible. Try introducing a few personas that your decision impacts.

Purpose: Identify the goals and objectives of your organization, your own professional goals in your leadership role, and any KPIs that might be relevant to the short or long term.

Problems: Explain the obstacles your organization has had over the last few years. Explain what your team has been struggling with. 

By asking ChatGPT to remember these things, every new piece of information will build upon the last. 

To set up a critic, add the prompt: “You are an expert in complex systems thinking, conflict-resolution, and design thinking. You are also my critical yet supportive thought partner who helps me see beyond my blindspots.” 

To set up a philosopher: “You are an expert in philosophy, regenerative ecosystems, and moral theory. You are also my critical yet supportive thought partner who helps me see beyond my blindspots.” 

…you get the idea. Following this, present your draft solution to AI and then ask the aforementioned go-to questions.

There are oodles of prompt engineering resources out there that will show you how to increase the reliability of responses. Our Ed3 DAO community member Brian Piper recently identified prompts he’s used. Please choose your own adventure.

The main goal with setting up a cognitive thought partner is to improve your thinking, not just the production of content. If used correctly, leaders having a thought partner who knows them can be game changing. 

Grasping our Self-Governance

Technology will outpace our ability to keep up with it. Expanding datasets and neural links will likely help AI get “smarter”. But if we want to stand a chance against the machine, we must retain our self-governance, AKA our ability to own our decisions and data. We need to continually evolve our cognitive abilities and explicitly recognize the nuances only humans know, from politics to pedagogy.

I’m grateful to the folks at CCSS for inviting me to share my ideas with them and commend their continued leadership across their school districts, despite how lonely leading can be.

Check out my newsletter for more thoughts on AI + Web3 and my website, www.vritisaraf.com. Join our community at Ed3 DAO to continue the conversation and to access AI courses for educators. 

The post AI is the Cognitive Friend We’ve Always Wanted appeared first on Getting Smart.

AI Integration Framework

Their AI Integration Framework breaks the progression of adoption into three distinct stages, investigating, implementing and innovation. 

Progression Stages:

• Investigating involves initial exploration and understanding, with limited AI applications.
• Implementing sees schools actively integrating AI, with a focus on ethical considerations, targeted learning activities, and foundational AI infrastructure.
• Innovating signifies a mature AI adoption, with advanced applications, comprehensive policies, and holistic assessments using AI. The innovating column also emphasizes how AI can support bolstering student ownership.

The framework then applies these stages across a variety of fields: Leadership & Vision, Policy Considerations, Instructional Framework, Learning Assessments, Professional Learning, Student Use of AI, Business & Technology Operations, and Outreach. Each is a great opportunity for innovating in new ways. 

Planning Guide for AI

Supplementing the framework, they have released a planning guide for AI which starts off with four distinct directives for school leaders to responsibly engage with AI: engage in planning, make it local, dedicate a team and address potential concerns. Throughout, they make the case for using AI as an augmentation tool, not a replacement tool, and suggest that it can support “uniquely human tasks,” “promoting student agency” and developing “new learning models.” We also appreciate the call for helping students to both understand and utilize the technology. Each section is then followed by a suite of potential risks of adoption and integration, which seeks to anticipate some of the potential pitfalls and roadblocks of the coming transition. 

Additionally, the team has announced a series of workshops, courses and trainings to support school leaders in their adoption, their understanding and their ability to form their own strategies for embracing the new learning landscape.

All of these contributions add to the great information emerging from orgs like TeachAI and AI for Education.

A Statewide Culture of Innovation

This is not the first time Michigan Virtual has led the charge toward innovation. For 25 years, the statewide virtual school has partnered with school districts. They sponsored The Future of Learning Council (FLC), a cohort of 40 unique school districts and learning organizations.

“The Council members are thought leaders who represent a powerful ‘coalition of the willing’ who embrace change and recognize the value of flexible, personalized, and competency-based learning systems that are high-touch and high-tech. We are excited to provide the administrative backbone and meeting facilities to support the Council’s functions,” said Jamey Fitzpatrick, President of Michigan Virtual.

For more on the transformational change happening in Michigan:

The post One State’s Approach to AI Integration and Rapid Reskilling appeared first on Getting Smart.

School systems across the nation face a common problem – how to use the vast amount of data available to them from various edtech tools to make informed decisions and equip educators with that data promptly. According to a recent LearnPlatform report, school districts accessed an average of 2,591 district edtech tools last year and about 1,379 edtech tools each month. However, much of this data is siloed, making it difficult for educators to use it to drive decision-making. 

The solution to this challenge is data interoperability – the seamless, secure, and controlled exchange of data between applications. Data interoperability makes it easy to exchange data between systems and combine it to be easily analyzed and made available through data visualizations and reports. This makes it easier for educators to get a holistic picture of each student and can help drive better instructional decisions.

Implementing data interoperability can be a challenging, multi-year process for school systems and edtech service providers. For many districts, the journey continues while moving to more sophisticated interoperability systems and leading educators through professional development in online learning and data-informed decision-making.   

Every year, Project Unicorn administers the School System Data Survey to help the education sector better understand current K-12 school system capabilities and infrastructure for leveraging education data. Questions are grouped into six domains: Leadership and Vision, Governance, Technology and Infrastructure Landscape, Procurement, Implementation Fidelity, and Impact on Educational Environment. Project Unicorn then analyzes the data and publishes the results in the State of the Sector Report. 

The 2023 report evaluated the responses from school systems across the United States, providing valuable insights into the state of K-12 data interoperability and suggested action steps to move the work forward.

Some key findings include the following:

• Consistent with all three years, governance was identified as the most significant challenge for school systems among the six survey domains.
• Consistent with findings from last year, school systems that reported having data teams scored significantly higher across all domains, and the size of a district’s IT team did not have a significant relationship with the size of a district’s data team.
• Many school system leaders still need to familiarize themselves with education data standards and/or how they might be used to benefit students. Although knowledge in this area is slowly increasing year after year, the buy-in for interoperability is high.
• Larger and more urban school systems tended to score higher on the survey than smaller and more rural ones. This is likely because larger systems have more resources to invest in infrastructure, which ultimately leads to better outcomes.
• School systems continue to indicate prioritization of data-driven decision-making but need more capacity for robust implementation and face obstacles.
• Funding continues to be a challenge for implementing data system modernization, including interoperability and privacy, even with increased federal dollars.

The State of the Sector Report indicates that school systems need funding and support to leverage data interoperability and use their data best. Despite the abundance of edtech tools, school systems need more infrastructure and human capacity to leverage this data at scale.

Fortunately, Project Unicorn provides support and guidance to school systems that want to use their data better. By signing the Project Unicorn School Network Pledge, school systems receive complimentary technical assistance from Project Unicorn interoperability experts to help them move forward. No matter where school systems are on their interoperability journey, Project Unicorn and our partners can help them move this important work forward to benefit students, educators, administrators, and parents.

Recommended Resources

• The First Three Steps for K-12 IT Leaders
• The Privacy Jump Start Guide
• The Better Edtech Buying Guide
• The K-12 Digital Infrastructure Briefs – By The Office of Educational Technology

Chloe Sanducci is the Project Director for Project Unicorn, an initiative of the non-profit InnovateEDU. This initiative is a coalition of 17 external organizations focused on advancing and implementing data interoperability in K-12 schools.  Project Unicorn helps school technology leaders and edtech solution providers integrate data interoperability standards into their data ecosystems by providing free resources, webinars, scholarships for professional development, interoperability certifications, and reports. Additional 1:1 technical assistance is available for signatories of the Project Unicorn School Network Pledge and the Project Unicorn Edtech Vendor Pledge to help them move forward on their data interoperability journey.Project Unicorn has released its 2023 State of the Sector Report, featuring insights from the field into the status of data interoperability in K-12 schools nationwide.

The post Using the Insights of Project Unicorn’s 2023 State of The Sector Report appeared first on Getting Smart.

Often, they were doing this work with little cognitive and emotional support.

Dr. Carmen Garcia, president of CCSS, Superintendent of Morgan Hill Unified School District and an incredibly thoughtful and kind leader, welcomed the group with one sentiment; “being a superintendent is lonely.” No matter how big your team is, the high-pressure, highly-public, and highly responsible role of superintendent has little room for mistakes. 

In the education world, we’ve seen the ways educators can use AI to produce lesson plans, quizzes, and report cards. But I would argue the most important potential of AI isn’t to enhance human productivity. It’s to enhance and support human thinking. 

So at CCSS, I chose to prepare our Superintendents to use AI as the thought partner they’ve always wanted, in a world where leading is a lonely job. 

This 2-part article is about AI’s cognitive abilities as a thought partner.

The first part differentiates the competencies of AI from humans. It identifies what humans can double down on as their unique advantage, while also identifying a new standard for quality of thought using AI.

The second part (coming next week) provides ideas for how leaders can train an AI thought partner to represent whoever they want – a critic, a twin, a mentor, a philosopher, or a guide. 

The Cognitive Dance of AI

In the last year, we’ve seen a rapid improvement in the abilities of generative AI. It can take millions of pieces of data and reconfigure them into billions of pieces of content. However, shortcomings with data validity, misinformation, and algorithmic bias have deterred some educators from considering it a reliable tool.

When writing my keynote, I wondered if understanding AI’s cognitive abilities could help advocate for its utility. A familiar framework came to mind: Bloom’s Taxonomy. 

When I was a teacher, Bloom’s played an important role in lesson planning and assessing the competencies of my learners. Recent critics have appropriately recognized that these cognitive levels shouldn’t be stacked linearly, but should be more of a spiral that volleys between levels as learning is happening. Either way, it’s been the most accessible representation of learning in the last 70 years.

I thought that mapping AI’s abilities to Bloom’s Taxonomy would group at the top, bottom, or even perhaps swallow all of Bloom’s. In reality, it was much more spotty and varied, revealing a keen representation of human and robot capabilities.

Mapping AI to Bloom’s

Here’s my evaluation. Remember that the purpose was to set our superintendents up for understanding when and how AI is most powerful. As you read this, keep in mind how you’ve been thinking about AI.

Remembering: The Relentless Recaller 

• Bloom’s Level: Remembering
• AI’s abilities: Highly competent. 
• Key actions: Retrieving information such as facts, dates, definitions, or answers.

How well does AI recall data or information?

This first one is obvious. AI can simultaneously access millions of pieces of information across large databases. It will always be able to retrieve data more quickly, accurately, and with more abundance, than humans ever will. 

Understanding: The Illusionist 

• Bloom’s Level: Understanding 
• AI’s abilities: Not competent. 
• Key actions: Recognizing, discussing, or explaining the meaning behind information.

How well does AI make meaning of information? 

When I evaluated this level, I didn’t expect AI to fail so soon on Bloom’s. AI can recognize patterns, categorize data, and extract pattern-based meaning from large datasets, but it doesn’t truly “understand” in the human sense. Its comprehension is based on patterns and data, not on consciousness or intuition.

During my keynote at CCSS, the very thoughtful leader Dr. Tom McCoy, Superintendent at Oxnard Union HS District, chimed in with an incredible example. He explained how his son, when completing a homework assignment that asked him to write a goodbye letter to racism, used ChatGPT for ideas. ChatGPT replied with an opening line to the letter: “Dear Racism, We’ve had such great times in the past…”. AI used pattern recognition to identify how great letters hook the reader but didn’t make meaning of the purpose of the letter and the weight of racism. AI did not understand the assignment. 

AI possesses an uncanny ability to generate responses that, at face value, seem informed and profound. This is because it excels in pattern-matching, recognizing and mimicking structures, sequences, and commonalities within data. But it’s not making meaning.

Applying: The Patterned Practitioner

• Bloom’s Level: Applying 
• AI’s abilities: Somewhat competent.
• Key actions: Using information in new contexts to predict, interpret, solve for, execute, or implement. 

How well does AI use information in new situations? 

AI, especially machine learning models, excels in applying learned patterns to new data. At the heart of AI’s application skills is a concept called “transfer learning”, which enables an AI model trained on one task to be repurposed for a second related task without starting from scratch. This is akin to a human leveraging their knowledge of cycling to quickly learn motorcycle riding.

However, humans possess an innate ability to make intuitive leaps. If faced with an unfamiliar problem, we draw from our varied experiences, even if they seem unrelated, to find solutions. AI, on the other hand, relies heavily on patterns it has seen. It struggles in scenarios where data is sparse or where intuitive, out-of-the-box thinking is required.

So the effectiveness of AI at this bloom’s level is somewhat competent and really depends on the data it has along with the complexity of the problem.

Analyzing: The Connection King

• Bloom’s Level: Analyzing
• AI’s abilities: Highly competent.
• Key actions: Identifying trends, differentiating, comparing, relating, and questioning. 

How well does AI draw connections among ideas?

Traditionally, Bloom’s illustrates that if a student isn’t able to remember, understand or apply, they probably won’t be able to move up on the taxonomy. But seeing AI fail at the lower levels and excel at this one further helps to make the case for Bloom’s Taxonomy as a spiral construct, not a linear progression. 

AI can analyze vast and multidimensional datasets with superhuman speed, identifying subtle patterns and relationships. For instance, in genetics, AI tools can sift through enormous genomic data to spot potential markers or mutations linked to diseases. AI can predict potential future patterns based on historical data, which makes it highly competent at this level.

Evaluating: The Emotionless Evaluator

• Bloom’s Level: Evaluating
• AI’s abilities: Minimally competent
• Key actions: Making a judgment, critiquing, depending, or providing an informed opinion.

How well does AI make judgments?

The act of evaluation is not merely about decision-making based on data; it is a complex cognitive process that often demands judgment, ethics, and contextual understanding. AI falls apart at this level. It does not operate with ethical judgment, it does not have cultural nuance, and it certainly does not have emotions. It over-relies on quantifiable metrics and although this perspective is important and can be used to evaluate our own blindspots, it is not the full picture.

We know that the instinct-based decisions leaders need to make in difficult situations are sometimes the best decisions. Steve Jobs is famously known for using his instinct to launch the iPad when tablets were failing in the market. 

This level is where humans can shine and have a serious advantage over the machine. I gave this one a “minimally competent” because although AI cannot make judgments, it can provide us with the right information and recommendations so we can make judgments.

Creating: The Copy-Cat Composer

• Bloom’s Level: Creating 
• AI’s abilities: Somewhat competent
• Key actions: Producing, designing, assembling, constructing, formulating.

How well does AI produce new or original work?

AI can create new content by merging patterns it has observed, but it isn’t original. It doesn’t have original thoughts, emotions, or consciousness. Even when AI creates music, artwork, or narratives, it does so by identifying and combining patterns in its training data. The result may sound or look unique to our ears or eyes, especially when the AI blends seemingly disparate styles. But at its core, AI is not inventing; it’s remixing.

And because of this, AI’s creative capacity is tethered to data. It cannot make the cognitive leaps across variable experiences even if the sheer vastness of combinations it generates seems groundbreaking. The permutations are just regurgitations in many forms. 

Human creativity often springs from emotions, personal experiences, cultural contexts, and epiphanies. It’s organic, nuanced, risky, and sometimes serendipitous and unintuitive. These elements are currently beyond AI’s grasp. So although AI is highly competent at creating remixed content, it is not competent at creating original content. 

How Learning Blooms

Mapping AI on Bloom’s taxonomy opened several cognitive and presentation pathways for me. 

• It helped me explain the human advantage over AI 
• It depicted AI as a cognitive partner
• It identified the ways learners might use AI and be duped by AI
• It allowed me to narrate how AI will elevate our standards in education for the production of content, ideas, and discourse

This last point is particularly important. One of the superintendents mentioned that using AI feels like cheating. She didn’t want people to think her thoughts and her work were not her own. That made perfect sense to me and it was difficult to justify AI’s IP leaching algorithm. 

Instead, I shared that the calculator gave us the shortcuts we needed for quick and generic mathematics, but what we put in the calculator — how we used and contextualized the answer, and how we reasoned through the validity of the response — is what made the output our own. The use of the calculator also enabled educators to level up their expectations for students. Getting an answer was no longer the sole outcome. Now, students had to show their work and reason through more difficult questions. 

Although a simplistic analogy, AI will similarly create new standards of productivity for us. The more ubiquitous AI is, the more we will use it to produce higher-quality content. When everyone is using it, we’ll think of new ways to assess student competencies.

The next article in this two-part series will dive into how AI can be a cognitive partner to leaders. In the meantime, check out my newsletter for more thoughts on AI + Web3. Join our community at Ed3 DAO to continue the conversation and to access AI courses for educators.

The post What Bloom’s Taxonomy Can Teach Us About AI appeared first on Getting Smart.

We are a year into the new age of human-computer interaction and things are moving fast. Generative AI gets better every month at producing text, code, images, and even video. 

In an Impromptu dialog with GPT-4, LinkedIn founder Reid Hoffman suggested we should now think of ourselves as a new species, homo techne, “tool-makers and tool users, augmented and amplified beings capable of more than we ever thought possible.” 

Two breakthroughs define this new age of human-computer interaction, explained Satya Nadella in his annual letter, natural language as the interface (after generations of keyboards, mice, and touch screens) and powerful reasoning engines. “This generation of AI helps us interact with data in powerful new ways—from completing or summarizing text to detecting anomalies and recognizing images—to help us identify patterns and surface insights faster than ever.”

Hoffman’s AI startup Inflection offers Pi, a “personal intelligence” willing to serve as “coach, confidante, creative partner, sounding board and assistant.” The 2013 sci-fi movie Her is playing out with dozens of AI companions in app stores. 

A year ago, the script was “Focus on human skills because AI will never be creative or empathetic.” This fall AI apps promote idea generation, collaboration and creative content. 

AI apps are empathetic confidants, coaches, and pathway advisors. AI capabilities are moving fast causing a reconsideration of what young people can do and should know. 

At an AI demo at EdTech Week in NYC last month, there was a mixture of Hoffman’s optimism and a dose of concern. Some pragmatic optimists are busy automating 20th-century pedagogy–making it easier to produce worksheets and robo-tutoring hand calculations in math.  

Creative optimists are inviting learners into value creation. Warton professor Ethan Mollick invites students to view AI as a co-founder and creativity engine in entrepreneurship. Learners in DaVinci Schools in Los Angeles use Project Leo to construct community-connected projects. 

Educators use Playlab to construct project tools and chatbots. Reinvention Lab used Playlab to create FutureShock, a summer impact sprint.  

A new report from TeachAI summarizes the potential benefits of AI in education (below) leading with content development and (4th on the list) creative project-based work. To the personalized learning category, add smart career exploration and path guidance (see SchoolJoy for example).   

The most widespread concern is (what is currently considered) cheating and plagiarism–or the unauthorized and undisclosed use of gen AI in completing assignments. Use guidelines are important but there is also the opportunity to move to what Professor Sarah Elaine Eaton calls “the post-plagiarism age of hybrid writing” with higher expectations for quality while valuing attribution. 

The automation of bad pedagogy, as TeachAI notes, could lead to less agency and loss of critical thinking. The opposite is the goal– inviting learners into more challenging work yielding public products not previously possible. 

Getting Started With AI 

School visits this fall suggest that most schools are waiting for guidance. And, that direction is beginning to emerge. AI for Education offers useful guidance on laying a foundation, developing staff, and engaging students. 

Similarly, the new guidance from TeachAI suggests a three-step process of 1) creating/updating a use policy, 2) facilitating staff development, and 3) identifying areas for improvement and transformation. 

A few school districts are well down this path. St Vrain Valley Schools in Longmont Colorado has invited staff to explore AI with a bingo card of 25 learning experiences. Drop-in coaching sessions are hosted at the Innovation Center and weekly pop-up events at schools invite exploration (example below). AI Champions at each school support ongoing development and real-time exploration.  

St Vrain students won the 2022 World Artificial Intelligence Competition for Youth and they are hosting the competition this year. St Vrain has 220 robotics teams across the district and hosted the 2023 Underwater Robotics Championship. Innovation Center students on the AI Cyber Bus Team are converting two school buses into mobile labs following the lead of the Future Ready Innovation Lab.  

The Peninsula School District in Gig Harbor, Washington developed Artificial Intelligence Principles and Beliefs rooted in Universal Design for Learning. It concluded, “AI is a potent tool that can dramatically improve education by offering personalized, inclusive, and compelling learning experiences when used responsibly and ethically.” Teachers in an AI Action Research project developed Resources and FAQS. 

To get started, check out AI 101 for Teachers from Code.org. Also, see ISTE’s AI resources including Tips for School Leaders. For using AI to learn about teaching, request a demo of   

Stretch AI from ISTE, a chatbot that is trained on their libraries of vetted content. 

Communities Alive With Possibility

There are good reasons to be concerned about the proliferation of AI in work and learning. But if collective response is limited to risk mitigation, communities will miss the greatest impact opportunity in history. Gen Z (or as Reid Hoffman suggests, Generation AI) has the opportunity to do more than ever thought possible–to create, express, invent, heal, and teach. 

What I most appreciate about visiting St Vrain Valley Schools is the sense of possibility. They lean into opportunity, they turn it into an R&D agenda, they invite teachers and learners to explore new possibilities, and then they scale innovation for equity.   

With Colorado Education Initiative, St Vrain hosts the National Innovation and Leadership Institute where they share the formula for building a strong foundation and adding an innovation agenda. Assistant Superintendent for Innovation Joe McBreen challenged the last cohort, “Your district’s greatness in 2030 will be directly proportionate to how innovatively you dare to lead.” (And, he said it in three languages using an AI translation app.)It’s time for a community conversation about what’s possible, about lifting collective expectations of the kind of work young people can do. Like KEEN engineering schools, it’s time to invite learners to spot opportunity, design solutions, and deliver impact. Like Real World Learning schools in Kansas City, it’s time to invite learners into community-connected and entrepreneurial projects. Ethan Mollick said, “Given the inevitability of change, we need to figure out how to mitigate the negative, but also how to channel the change for good as much as possible.”

AI in Education

For the past decade, we’ve been covering advances in artificial intelligence and machine learning, sounding the alarm that it’s not if it’s when and it’s not when… it’s now. Over the last few years, the news cycle appears to be in full agreement with us. This publication highlights trends and developments in artificial intelligence that are shaping teaching and learning.

View Publication

The post One Year Into the AI Revolution….and Most Schools Are Still Seeking Direction appeared first on Getting Smart.

Level Up – Pathways in Schools

One size has never fit all; not in the free shirt you receive at a conference or in options for learning. 

Similarly, young people vary widely in interest and passion, and campuses often have to facilitate opportunities for students to connect and find their people. One option that not only provides connection, but also provides an environment for skill development, and prepares students for life beyond school is esports. While the world of esports was once considered ancillary to other programs, districts and campuses that have embraced this new pathway for students have found it to be vital.  

According to a student engagement survey, only 65% of students agreed with the statement, “I go to school because of what I learn in classes.” and 54% participate in 4 hours or more of school-sponsored activities. Esports is a great way for students to become engaged and connected during and after school. 

Stackable – Skills Development

No. Students aren’t just wasting their time gaming. 

As scholars put on their headsets, turn on their game, and spend countless hours rising through the ranks, they are forming teams, creating strategies, and persevering against some of the best players globally. Through gaming, students gain durable skills (as defined by America Succeeds) which are high demand skills that allow youth to demonstrate their knowledge and stretch their character. Esports (competitions, challenges, tournaments) allows participants to strengthen leadership, collaboration, critical thinking, and fortitude skills. Relying on teammates, developing strategy plans, and persevering against the odds are a few of the ways players develop transferable skills through gameplay and why esports teams are essential on any campus.

As with the competitive side of esports, operations are primarily fueled by technology. Esposure4All, a summer internship program,  trains high school students with limited incoming experience to run esports events focusing on the software incorporated into these experiences. Over the course of two months, students are introduced to the Adobe Suite, Obsidian, Blackmagic’s ATEM software, VMIX, and professional photography and videography skills. One intern said the experience “opened up new doors and opportunities that I wouldn’t have by learning to use these new software”. 

During the internship, students learned the importance of professional communication, proactively managing client scope, and event management and execution. Interns also learned the value of professional branding by creating their LinkedIn profiles, headshots, and portfolios as well as the elements of self-directed learning and critical thinking skills as they were provided access to the resources and were challenged to learn the necessary information to execute their goals. One intern stated the process forced him to “dig deep into [his] brain and find ways to solve the simplest tasks.”  If this progress occurred during two months of esports training, what level of impact would this provide over a school year or more?

Ready Player One – Future Career Options

Not a gamer, not a problem. 

While the obvious career option in esports may be professional gamer, that only accounts for a fraction of the jobs in the billion-dollar industry and provides an average salary of $60,000/year. A robust esports program can introduce young people to almost 200 careers in the esports industry according to Hitmarker, a job recruitment platform specifically for the video gaming world. From research to art design to event planning, the possibilities are abundant for those involved. As career exploration continues to expand and commence earlier than high school, the options in esports can’t be neglected. A recent study conducted by America Student Assistance showed over two-thirds of high school students would have benefited from career exploration: the time is now to view esports programs as an additional avenue to lucrative jobs before it’s game over. There are robust esports programs budding across the country on college universities and campuses like Full Sail that are fully committed to careers in the gaming industry. 

Additionally, there are paths to entrepreneurship that esports carves out as was the case for Ryan ‘Dayfri’ Conger who moved from college baseball player to gamer to professional gamer to esports intern to entrepreneur.  Conger once had his eyes on becoming a pro baseball player until his college career was sidetracked due to an injury. Once he shifted his focus to gaming and continued to learn about potential career opportunities he pivoted to gaming and, eventually, esports coaching. He is now the coach for the Dallas Mavericks esports team which also allowed him to support his parents’ pathway to entrepreneurship. 

Teamwork + Community = Belonging

Squad up!

Yes, most campuses have a football, basketball, band, cheerleading and dance team_, but is there a student demographic these organizations are missing? Perhaps, esports is the perfect solution to provide a community for a group of young people who may be overlooked by traditional sports programming. The world of esports is an accessible platform for students to gain recognition for their level of gameplay. The need to belong is ingrained in young people and is tied to student academic performance in school as well. Regardless of the console or video game, esports allows students to make connections, build community, feel seen and share experiences with other students with similar interests. A study from 2019 noted that while the majority of middle and high school students feel a sense of belonging, close to 30% are missing the vital aspect of belonging that could be solved through esports.  

As Epulze COO, Frank Sliwka stated, “With the rise of scholastic esports, educators now have a unique opportunity to validate their students’ interests, support their social-emotional learning, and connect them with future workforce aspirations.” It’s imperative that campuses and out-of-school opportunities expand offerings that include esports and the countless students who may find their crew through gaming.

Project-Based Learning 

Esports is the embodiment of project-based learning.

Through esports programs, students are finding and following their passions as Videographers, Photographers, Production Technicians, Production Managers, Light & AV Technicians, Discord Engineers, Stream Moderators, Graphic Designers, Animators, and many other roles. As students learn about different pathways, they are consistently facing challenges and troubleshooting to succeed in their job. 

As students take on their roles, they are learning how to “own” their positions and gain self-agency to grow within those roles. A simplified version of this is Esposure’s Esports Business Pitch Competition. Through this experience, Esposure works with schools physically or virtually to break students into teams of five and provides them with a mock budget to produce the best esports event out of their class. Each of the team members lead the divisions of Management, Marketing, Production, Technology, and Competition. These roles include the following responsibilities:

• Manager – Ensures the team is moving with a unified vision and within the given timeline 
• Marketer – Creates social media campaign and pages in addition to analyzing marketing spend
• Production – Creates reels from the stream of a simulated tournament
• Technology – Creates the company’s website
• Competition – Creates brackets and uses the budget to determine players to be selected for the mock draft.

Opportunities such as this give students the opportunity to learn independently while contributing to a larger group. This culminates in a “Shark-Tank” style pitch competition where teams are provided with 5 minutes to pitch their event, with the best one being crowned the winner.

This is just one example of how esports can bring students together. On a grander scale, esports programs can recruit from and contribute to a variety of other programs and clubs with the various soft and hard skills learned providing your campus with a student-run community of innovative leaders. 

As the education system embraces scholastic esports, it empowers educators to support students’ emotional growth, align their passions with their future aspirations, and facilitate project-based learning that mirrors real-world challenges. The story of esports in schools is a testament to the power of innovation, inclusion, and adaptable learning, shaping the next generation of agile, skilled, and self-assured leaders ready to excel in any field they choose to pursue.

The post Stop Playing: Your Campus Needs an Esports Program   appeared first on Getting Smart.

Artificial Intelligence is taking hold in our society. From Chat GPT to TikTok algorithms to Tesla Autopilot, we are seeing a much more public representation of what these systems are capable of. This is a pretty big deal to a high school student, who was just googling “How can I get my math homework done without having to do any actual math,” for fun when they realized, somebody actually invented it. Finally. It felt like the turning point my younger self had been waiting for, the day all the robots take over and I became the main character of a dystopian franchise. 

But, I was still in high school, and facing an even greater issue. I needed to brainstorm and draft a research project, complete with an annotated bibliography, a literature review, and a methodology analysis. 

My Global Impacts Microschool classmates and I were preparing these projects for when we took a 2-week-long research expedition to Kenya in February of 2023. We were traveling there to visit Lewa Wildlife Reserve and were expected to find a problem based on one of the UN Sustainable Development Goals. And then create a solution to that problem. It was overwhelming, I’ll admit it, but it was also the first time I was able to take a new interest I had, AI in conservation, and actually use my class time to research it. And what I found was that AI in Conservation could open up new pathways for Lewa – but, it was leading to a data trap globally that could push countries like Kenya further and further behind. How could AI in conservation be used to increase biodiversity in Lewa Wildlife Reserve in Kenya?

Many wildlife conservation reserves, such as Lewa Wildlife Conservancy, monitor animals through manual data collection and analysis. This requires individuals to go out, collect data, analyze it, and synthesize results in order to serve as a valuable conservation tool. Artificial intelligence (AI) provides a sharper edge to the conservation data collection and analysis tool.  Using AI sorting systems to analyze data from camera traps, audio recordings, and satellite images can decrease conservationists’ workload by a large amount. 

We visited the Rhino Monitoring and OPS rooms on Lewa, as well as a nearby research station called Natural State. These visits helped us familiarize ourselves with the systems Lewa uses to track its animals, such as satellite imaging, audio monitoring, and camera traps.

It soon became evident that these systems lacked an automatic sorting system or even an efficient way to move the images and audio clips from the actual cameras to the rooms where the research analysis took place. 

Lewa specialist Eunice Kamau noted that the problems stopping them from implementing these new systems were a lack of IT support and a reliable internet connection, as well as a community fear of job loss. Those at Natural State had begun to use and train AI sorting systems, but their issues stemmed more from the lack of a renewable energy source for their camera traps and audio mods, as they used battery-powered devices. All of these issues are taken into place when considering whether AI would be a good tool for Lewa to implement. 

My proposed solution for the AI in conservation question is a mock EarthRanger system, EarthRanger Jr., that is angled towards children 6+ in Lewa’s Digital Literacy Program. This would provide these children with the context they need to understand how large and bountiful the Lewa landscape is. It would also be a good way to encourage and measure interest in the conservation and computer science fields. 

This would be an open-world map game, have a downloadable format, and would be compatible with Android IOS. The game could have a variety of entities, especially the animals that live on Lewa. The game could also have a mock AI sorting system, where the students could begin to get a grasp on the AI world in conservation.

If the proposal went through to Lewa, they could bring it up to the EarthRanger and AI2’s teams when they meet with them, to see if this is a program they would be interested in. I have designed a proposal document, and that is the finalized product created from this research. This research answered many questions about the development of AI on Lewa, and it is exciting to be pushing for updates as the world of AI conservation blooms worldwide.

It was incredible to experience the challenges and opportunities given by the Global Impacts Microschool. Personally, I hadn’t felt this engaged during a lesson since I was young, getting to feel, build, and imagine things was transformative. I had never been out of the country before this trip, and the fact that my teachers were so dedicated to making this happen for us makes me extremely grateful. 

Writing the research paper made me feel like I was actually creating something meaningful for the first time in high school. It honestly, added some pressure to my school day, which was something I realized I NEEDED by the time I was done with this course. 

This course didn’t just affect my interest and excitement about school in one area, my grades in all my classes improved a ton. I needed a challenge during school, because of the way I learn, if I’m not being challenged or interested I immediately lose all my drive. This course gave me a push in many aspects of my life and allowed me to feel satisfied after completing work that actually mattered. This lets me see my own place in the world – which is an experience that all young people should be able to feel. I could check back in a few years and let y’all know, but, I guarantee it will continue to be life-changing for me. 

To learn more about microschool impact and opportunities, visit the Learning Innovation Fund.

Mary Margaret Perkins is a student at Notre Dame de Sion High School and served as a 2023 Getting Smart Summer Intern.

The post AI in Conservation: How Would this Change Our Interactions with Wildlife? appeared first on Getting Smart.

Accountability with AI is critical, especially in schools and especially right now. Many educators are skeptical of AI in general and in particular, generative AI (GenAI). They may even see firsthand the biases and inaccuracies inherent in chatbots and content creation tools. However, the push to use the tools in schools is real – and alarming. No matter how pressed for money schools may be, GenAI is not a substitute for any level of human contact. The idea that the tools will evolve and improve is not a valid argument because they do not always improve, and we do not know how they will change.  

Why, then, pay attention to Generative AI at all? Because, in the right context and with the right guardrails, it may bring productivity gains for teachers, and some level of personalized learning for students. It will give young learners new tools with which to express themselves and connect constructively. It will also be misused: in bullying, false identification, plagiarism, and many other ways. These tools reflect and amplify all the positive and negative qualities of the people who use them. Finally, they are going to be part of every student’s environment, and using them in schools will provide a safer way to learn them and some more thoughtful habits for using them. 

The U.S. Department of Education recently released its own principles for “AI and the Future of Teaching and Learning.” Based on those and on our own research for The AI Dilemma: 7 Principles for Responsible Technology — here are five points that school leaders can use to develop their approach to responsible AI. 

1. Emphasize humans in the loop. Above all, don’t delegate teaching to AI; don’t shut kids in with a chatbot as their primary teacher. AI provides a seductive illusion of control, but real education requires consistent human-to-human contact. Use the tools, and work with the tools, but always with human presence and awareness. 
2. Embrace “creative friction.” Digital technology is typically designed to reduce mental tedium, but that frictionlessness can backfire, especially in a school setting. Quality use of GenAI in education requires conscious attention to its practices. Bring together groups of people with diverse perspectives (ideally including students) to decide what you will and will not do. 
3. Prioritize trust – especially with data. In schools, this means learning how to verify that data is used in trustworthy ways. Digital systems for student evaluation are often mistrusted because they reflect long-standing biases. The “cold data” – quantitative statistics about student performance – can often place students from vulnerable groups into special ed paths which they don’t fit, and which short-change their future. “Warm data,” as Nora Bateson calls it, should be part of every decision. This might include stories and observations that can be used to truly see children and help them realize their potential. 
4. Open the closed box. Aim for AI projects to be explainable, so that other people can question and learn from them. Provide visibility into the logic of the algorithm and the model of any student data project, including why the data was collected, and how it could be safeguarded. Train students and teachers until explainability becomes second nature. It won’t always be easy, because machine learning, by its nature, doesn’t always track its sources or reasoning. Learn to recognize how different assumptions, reflected in the model, can lead to different outcomes. 
5. Hold stakeholders accountable. As we’ve seen with social media, digital technology can be used to bully others. Students (and sometimes teachers) can use AI to create deepfakes and false information; some will be tempted to plagiarize. Make it clear why boundaries are necessary. Point out that the same GenAI program used for a class assignment may deliver the same draft to others. Misusers of AI may not always be caught, but they should know that these are high-stakes tools, to be handled with at least as much care as a car. 
6. Reclaim data rights for students and parents. This will be difficult. Like all institutions and organizations, schools are used to collecting personal data and choosing how they use it – within legal guidelines. With GenAI tools, students will create and collect their own data: about who they are, where they go, who they spend time with, what they look up, and what they think and feel. They should have control over how this data is used and be conscious about how it is shared. 

In developing practices like these for GenAI in K-12 schools, educators are not just creating safeguards for particular applications. They are establishing risk awareness and safe innovation as a way of life for a generation of young people. 

Juliette Powell and Art Kleiner are co-authors of The AI Dilemma: 7 Principles for Responsible Technology.

Juliette Powell is an author, a television creator with 9,000 live shows under her belt, and a technologist and sociologist. She is also a commentator on Bloomberg TV/ Business News Networks and a speaker at conferences organized by the Economist and the International Finance Corporation.

Art Kleiner is a writer, editor and futurist. His books include The Age of Heretics, Who Really Matters, Privilege and Success, and The Wise. He was editor of strategy+business, the award-winning magazine published by PwC.

The post Six Steps to Build AI Accountability appeared first on Getting Smart.

When Horace Mann dreamed up the idea that eventually became the US public school system, the world was a different place.

Fast forward to 1940. By then, the one-room schoolhouse had morphed into something we’d recognize today. And then things got…a little stuck. For example, I went to the same high school as my mother. When I was in 10th grade, I read the same exact books in English class she’d read 23 years before. My baby sister, 20 years younger than I am, read the same ones, too. Since their founding, the job of K-12 schools has been to open up access and opportunity to all children, to prepare today’s youth for tomorrow’s adulthood, citizenship, and employment. But we’ve basically done that by sticking to what we’ve always done in the past. 

The recent hew and cry about ChatGPT in schools is a perfect example. If you google ‘ChatGPT and schools,’ almost every single link on the first page of Google includes the word “ban.” Search Facebook and you find posts like: “We’re blocking it for all faculty and staff,” “I’ll let you guys work out the kinks first,” and “If we just ignore it maybe it will go away?” But it’s not going away. 

The public school industrial complex cannot operate out of fear of the future as we prepare students to live and lead in the world that’s to come. As economist and author Daniel Pink has pointed out when speaking to an educator audience, “We need to prepare kids for their future, not our past.”

Schools may be stuck in the past, but teachers are early adopters of cool technology.

So it’s not surprising that alongside the calls to ban ChatGPT, we quickly started seeing teachers’ posts, and even books, about how to use it to plan lessons, assess student work, and compose messages to parents. New York State Master Teacher Mary Howard, author of Streamlining Your Teacher Life with AI, says, “As an educator, one thing that I can assert with respect to this new wave of artificial intelligence tools is that we need to adopt and accept the risk inherent in being early adopters.  AI tools will not go away. The internal combustion engine replaced the horse and the calculator replaced the abacus.” Each new technological advance makes space for new ways of teaching, and new ways of learning, solving, creating, and inventing. 

As school administrators start to individually embrace ChatGPT for its capability as an unpaid 24/7 personal assistant, the go-to spot for ideas is social media. Facebook chat groups show diversity and creativity of usage. For example:

• Creating a section on academic integrity and AI for the student handbook, written by ChatGPT
• Having ChatGPT analyze an annual school survey for trends and use that to develop goals for the year
• Using ChatGPT to generate an A/B block schedule

On X (Twitter), you can find Rebecca Bultsma, a school communications professional in Canada, tweeting ChatGPT prompts like: “I want you to act as a crisis communication specialist, crafting a checklist for handling a potential incident that could harm our school’s reputation. Detail your immediate response, key messages, and the process for updating stakeholders.” These prompts show that administrators (like teachers) are using ChatGPT to do their jobs more efficiently and effectively. 

They are thinking from the mindset of the role they occupy. 

But what if we used ChatGPT to “think differently”?

Apple’s focus on the user experience revolutionized how we use computers. This is something we don’t really think about in schools. For my Master’s program, I was assigned to shadow a 10th-grade student for a day. It was one of the most boring days of my life. Seriously. I barely made it through each class awake. If that’s what school feels like for students, we need to rethink the user experience (UX). That’s where ChatGPT can help.

The fear (and focus) when it comes to ChatGPT and students are cheating. We need to flip the lens on that. Graphing calculators helped usher in a new approach to problem-solving. Could ChatGPT usher in a new approach to teaching and learning? If we know that ChatGPT could write any number of essays on The Great Gatsby, or the causes of the Civil War, maybe those assignments aren’t actually encouraging students to be critical or original thinkers. If we have an advanced tool that can craft capable responses for students, it doesn’t mean we should shut it down quickly. It means we should change our methodology. 

What’s a prompt a teacher could give ChatGPT for this example? How about: “Write 5 sample classroom-based activities about The Great Gatsby that are culturally relevant, meet the needs of different kinds of learners, and don’t have Google-able responses.” That’s one way a teacher could use ChatGPT to:

• Do the job more efficiently
• Prevent students from cheating
• Address the needs of a wider diversity of students

But that only improves the UX partway.

ChatGPT can help us think from the POV of our students and parents.

We live to the limits of our own understanding, imagination, and experience. But ChatGPT is built with a lot more information than any of us could hold in our brains. So, in addition to asking ChatGPT to think like a school communications professional, a principal, or a teacher, what if we asked ChatGPT to think like the populations we’re serving, as a way of improving the education (or UX) we’re delivering? ChatGPT is a neural network that works very much like the human brain, which means we can use it to think like folks who are different from us. Who are not planning and leading in districts, buildings, and classrooms? Who may be new to the country, or the English language? Who may be chronically absent or have an IEP or be in the foster system? 

Here are prompts I could imagine asking:

1. As if you were a teenager, create the ideal school schedule for what my brain and body need. 
2. As if you were a struggling math student, write a lesson plan on factoring algebraic equations that would be easy to understand but that includes activities so kids who get it don’t get bored. 
3. Review this unit/communications plan/newsletter/classroom update/lesson plan/college counseling document/student handbook/welcome letter and show me how it could be improved for diversity, equity, and inclusion.
4. Write a culturally inclusive 8th Grade science curriculum that adheres to NGSS Standards.
5. As if you were a new immigrant parent in a public school, list the communications you need to see in your home language.
6. As if you were a chronically absent 10th-grade student, suggest what the school could do to help you feel like you want to be there.

In this way, ChatGPT becomes an equity tool to help educators reach and connect with more students and families. It gives insight into how to achieve a more inclusive school system. We can use it to foster school connectedness and trust, turning chronic absenteeism on its head. 

It’s time to let go of the rear-view mirror approach to schooling. The way to overcome the current challenges dominating k-12 is to think out of the box, from the mindset of our ‘users.’ And the way to overcome the challenges in our future is to model for our students how to embrace the new and unfamiliar with curiosity and confidence.

We can only do that by looking forwards.

Kara Stern, Ph.D. is an educational leader committed to equitable and inclusive k12 education & am a staunch advocate for the importance of home-school communications in building trust, reducing absenteeism, and creating more inclusive school communities.

The post Let’s Use ChatGPT to ‘Think Different’ About K-12 Schools appeared first on Getting Smart.