Tag Archives: artificial intelligence

Can AI “ignite the mind and heart”? Stability & change in the education system in China (Part 3)

What challenges and opportunities can AI create for creating a more balanced education system? In the third post in this five-part series of reflections on his visits to innovative schools in China, Thomas Hatch describes what he learned from a visit to the Suzhou Experimental Primary School in December of 2025. This post summarizes what he took away from a forum where a group of teachers described the different ways they are using AI and the critical questions that it raises for them. The Suzhou Experimental Primary School is recognized as one of the best primary schools in China. In addition to famous graduates that include the architect I. M. Pei, that recognition builds on a long history that includes two visits from John Dewey during his visit to China that began in 1919. At the time, Dewey described the school as “the equal of first-class elementary schools in Europe and America” (“堪称与欧美一流小学并驾齐驱”). This post draws on an AI-generated transcription and translation of the conversation and benefitted from the comments of Zhenyang Yu and the support of Jianhua Ze and colleagues from the World Association for Creativity (WAFC) who arranged the visit.

The first post in this series described how some innovative schools in China are creating the time and space for more student-centered learning experiences, and the second post discussed how the Chinese education system has changed over the past 30 years. Future posts will discuss the growth of academic pressure as well as the technological and societal developments that may allow for the emergence of a more balanced education system. For previous IEN posts on educational change in China see “Boundless Learning in an Early Childhood Center in Shenzen, China;” ”Supporting healthy development of rural children in China: The Sunshine Kindergartens of the Beijing Western Sunshine Rural Development Foundation;” The Recent Development of Innovative Schools in China – An Interview with Zhe Zhang (Part 1& Part 2);” “The Desire for Innovation is Always There: A Conversation with Yong Zhao on the Evolution of the Chinese Education System (Part 1& Part 2);” “Beyond Fear: Yinuo Li On What It Takes To Create New Schools (Part 1);” “Everyone is a volcano: Yinuo Li On What It Takes To Create A New School (Part 2);” “Surprise, Controversy, and the “Double Reduction Policy” in China;” ”Launching a New School in China: An Interview with Wen Chen from Moonshot Academy;” and ”New Gaokao in Zhejiang China: Carrying on with Challenges.”


A warm welcome and an unexpected surprise awaited around every corner of my school visits in China. This past December, those surprises revealed what seemed to be a sudden explosion in the uses and discussions of AI in education. There was an elaborate AI lab at the Shanghai Shangde Experimental School (along with a drone arena and a robotics track); a showcase of sophisticated “kits” for incorporating AI into hands-on activities at the Nanjing PD Center; and a series of presentations at a conference on hands-on learning organized by the World Association for Creativity that highlighted the importance of the teachers’ role in AI. 

AI room from the Shangde Experimental School
AI room from the Shangde Experimental School
An AI kit for teachers from Nanjing’s PD Center
An AI kit for teachers from Nanjing’s PD Center

At the Suzhou Experimental Primary School, I was not thinking about AI at all when the leader from the school, Ge Daidan, and several English teachers, Zhao Hong, and Ye Qiujiao, took me on a tour of the school and led me through the school’s own museum. The many rooms and exhibitions of that museum chronicled John Dewey’s visits to the school in 1919 as well as the school’s growth and development since that time. But the surprise came when I went up the stairs and turned a corner, only to discover a small crowd of about thirty people waiting for me in a well-appointed meeting room. As soon as I was seated at the head of a conference table, six teachers, arranged in a semi-circle in front of a giant screen, launched into a set of carefully prepared and thought-provoking presentations about how they were working with and reflecting on their uses of AI throughout the school. Those presentations offered specific examples of how AI can already be put to work in a wide range of classes – including kindergarten, Chinese, English, Math, and Art – to help create more powerful, interactive, and student-centered learning opportunities in China and around the world. Yet at the same time, the teachers raised fundamental questions about the role of AI in education in general, the specific role of teachers in mediating AI use, and what distinguishes human contributions from those of AI.

Questions and Issues for AI in schools

The moderator, Huang Fei, began the forum by asking a question from a paper by Professor Wu Kangning of Nanjing Normal University – “What challenges does AI bring to education?” Faced with the waves of new developments, she asked “Should we embrace AI or wait and see? Should we lead or follow? How will the role of teachers, the form of the classroom, and the ecology of education be reshaped?”

Although it was impossible to capture all the issues that were raised throughout the rest of the forum, key questions included: 

  • Is it too early to be trying to incorporate AI into our work with students? 
  • Will AI provide assistance or will it become a crutch? 
  • How can AI save time, foster creativity, and support innovation, and strengthen teachers’ relationships with their students rather than weaken them?
  • Will AI help students and teachers to extend and develop their capacities rather than undermine them?
  • How can AI foster students and teacher’s creativity rather than stifle it? 
  • How can AI enhance teachers and students’ motivation rather than diminish it?
  • What is the teachers’ role when AI is being used?
  • Will AI lead to a focus on precision and efficiency that may interfere with the spiritual growth of students? 
  • How can we use AI to ignite the mind and heart?  
  • How can future education balance AI data-driven insights with humanistic judgment?  

As the moderator noted, these questions illustrate that “challenges and opportunities are often two sides of the same coin,” tensions that are unlikely to have a simple resolution, but that will require regular reflection. 

AI across subjects and classrooms

Following the opening remarks, the other five panelists offered a series of specific examples that demonstrated how the school is attempting to find a balance that enables students and teachers to use AI to extend their abilities without increasing the incentives and creating the conditions that discourage them from deepening their learning and exercising their agency and creativity. 

Kindergarten, Ms. Sheng: 

AI acts as a “good helper” in kindergarten by generating a growth record for each child, based on the teachers’ observations and other data. In turn, AI can use this data to generate lesson plans and personalize growth plans which can save teachers time and enable them to focus on developing their relationships with their students. 

As one example, they are using commercially produced software to help record students’ read-alouds,” and to use AI to track students’ growth in fluency, integrity, and accuracy. (For comparison to uses of AI in the US see “AI Tutors Are Now Common in Early Reading Instruction. Do They Actually Work?).  When they identify students who are hesitant and reluctant in reading and speaking aloud, they can also use AI to create interactive picture books that match each child’s interests and skill level. By reducing the demands of the interactive dialogues on pronunciation, ideally, they can increase a child’s willingness to speak and express themselves.

English oral reading results

Chinese, Ms. Huang: 

AI has helped teachers shift from answering questions to generating them. In the past, teachers assessed comprehension by asking students to answer questions about what they read about in historical, scientific and cultural texts. But now, they have shifted to inviting students to share their own questions, and teachers then use AI to analyze the students’ questions and to build their curriculum around them. As Ms. Huang put it: “Every good question is a seed of creation” and a window into the students’ interests, their observational abilities, and their logical reasoning. Reading a text about achievements in science, technology, and engineering, like the Zhaozhou Bridge, can lead to questions that help make visible the “germination of scientific thinking.” 

4 slides illustrating how AI has organized and categorized the students’ questions generated from their reading about the Zhaozhou Bridge

Art, Ms. Wang: 

AI has “injected a new vitality into our primary school art class,” Ms. Wang explained as she chronicled how the teachers are helping students to use AI to  expand their artworks and designs in a variety of ways, including: 

  • Making drawings on tablets that can then be printed on graduation t-shirts or turned into stop-motion animation.
Students in Art class with t-shirt designs
  • Using AI to explore what paintings of objects like their school campus might look like if they were painted by different artists or in different artistic periods as a way to develop students’ understanding of different artistic styles. 
Drawings based on the school.
Pictures of drawings based on the school.
  • Giving students opportunities to place themselves in ancient paintings to enhance  their historical and cultural understanding of art forms like Dunhuang Feitian dance
Students using AI with artwork.
  • Developing students’ designs and design abilities by using AI as an assistant to render their drawings in 3-D, enabling them to envision whether their design for an object like a chair would support someone’s weight or collapse to the ground.
Design and drawing of a chair.
  • Building a virtual exhibition hall where the students can display their paintings and sculptures, and parents and friends can view and comment on them. 

Yet, at the same time that Ms. Wang highlighted these artistic possibilities, she wondered: with the ease of generating finished products, will students become lazy? She concluded with a metaphor of hope: “I have always thought that AI is a museum that helps us find inspiration, not a print shop that gives you finished products directly.”

Math, Ms. Xu:

Teachers are using AI to help them create interactive and collaborative activities. For instance, to help students understand that the sum of the interior angles of a triangle is always 180 degrees – a fundamental geometric principle – the teachers are usingAI to produce a series of interactive demonstrations. Groups of students can manipulate the vertices of triangles of different shapes, discuss the results, and make comparisons. AI can record the conversations and help teachers identify key words and misconceptions that can inform their subsequent instruction. 

AI and data technology.
AI and data technology.
AI and data technology.

They envision as well using AI to increase the precision and effectiveness of their teaching. They can imagine assigning students exercises to complete on digital devices and developing AI agents that can identify mistakes and then link to corresponding explanation videos and examples to work on. 

Data-use, Ms. Hu: 

In addition to using different AI applications to collect subject-specific data within particular classes, the school also uses AI to help them look for trends and patterns in data across the school.  These analyses make it possible for them to quickly visualize growth trends and patterns in in five different areas including physical fitness, effort, ethics, and academics. 

Five Virtues Growth Chart

Teachers can also use AI to help them adjust their instruction to meet the needs of different classes. For instance, teachers can compare students’ English homework to see that one class may be struggling with pronunciation while another may be more be particularly advanced in vocabulary, leading a teacher to emphasize activities for sound discrimination for the first class and to introduce new content to the second.  Ms. Hu concluded by noting that “AI can give us a clear diagnostic map. But a prescription…is our teacher’s duty and wisdom.”

Hope and concerns for the future

Across these examples, I was particularly struck by the way teachers addressed the common concern that AI could transform teachers’ roles and the effect it might have on the teacher-student relationship. As Ms. Sheng articulated it, will the use of AI help to deepen teachers’ expertise and help to strengthen the relationships between teachers and students? Or will it interfere with teacher-child interactions and violate the essence of their child-centered educational approach? 

In response, the teachers emphasized that AI can’t replace the emotional links between people, and that teachers need to be able to pay attention to the more emotional aspects of children lives that may not be captured in the notes, observations, and other data that AI relies on. “AI can create beautiful paintings,” Ms. Wang, the art teacher noted, “but it can’t read the crooked little happiness in the sun painted by children. AI can’t replace the teacher who squats down to ask the child ‘Why are the clouds painted pink today?’” 

The presentations concluded with each teacher sharing, with hope and confidence, that they could find a balance that takes advantage of the potential of AI while enhancing the opportunities for teachers to draw on their emotional experience and humanity. As one put it, “I think as a teacher, the real wisdom lies in using the computing power of AI to liberate the teacher’s mind.”

The moderator added, that by following the development of the students and constantly adjusting teachers’ practice and cognition of teaching, “we will be able to gradually adapt to this educational change… It is really good to let AI be good at its skills and let the teacher keep his heart. Cultivate each child’s unique light with educational wisdom. Let’s guard the children’s unique light together.”

Posters.

What does education demand of AI and its developers? 

I don’t have any idea how many other educators in China are using AI in these ways, but I have no doubt that these are the kinds of questions we should all be asking: How can we find a balance that takes advantage of AI without succumbing to it? How can we enable students and teachers to use AI to extend their abilities without discouraging the from exercising their agency, deepening their learning, and developing their creativity? 

As Dewey suggested, education is not preparation for life; it is life itself. And in that spirit, we need to go beyond arguments about whether and how to stop children from using AI to ask, as these teachers are doing, how we can use AI powerfully, ethically, equitably? 

At the same time, even if we embrace Dewey’s philosophy and strive to engage students in real world activities, we do so with care and guidance. We can encourage students to explore the world beyond their classrooms, venture into the forest or cultivate a garden, but that does not mean that we leave them to play in a patch of poison ivy. Reflecting the concerns about the potential harms of AI use in schools, the Chinese government has already developed guidelines designed to support ethical and appropriate uses of generative AI and to address potential harms. According to these guidelines, “primary school students are not allowed to independently use open-ended AI content generators, which could allow them to use AI to do their assignments for them. Middle school students may explore the logical structure of AI-generated content, while high school students are permitted to engage in inquiry-based learning that involves understanding AI’s technical principles.” At the end of 2025, the Chinese Cyberspace Administration also released draft regulations that would restrict AI chatbots from influencing human emotions in ways to could contribute to self-harm. (In contrast, as Max Tegmark, MIT physicist and founder of the Future of Life Institute, points out that the US government has more regulations on sandwiches and food safety than on a technology that could sell AI girlfriends to 11-years olds and might develop a “superintelligence” capable of overthrowing the government itself.) 

Like the teachers at the Suzhou Experimental Primary School, we have to keep in mind both the possibilities for learning and the dangers that AI brings. It can analyze huge amounts of data and identify patterns on a large scale. It can provide greater precision and efficiency in some tasks, but it can also be addictive, misleading, and biased. It works, in a sense, on the past, on the data that has been generated and made accessible, but lacks – for now at least – as the teachers pointed out, human emotion and imagination. That means that the greatest benefits of AI may come when educators are a crucial part of children’s relationships with AI and other technologies; when we equip teachers with the tools of AI rather than relying on the ghost in the machine; when we use AI to help us imagine new and more equitable educational arrangements, new opportunities for learning and teaching that are not trapped in our past experience. As Cornelia Walther expressed it: “We must double down on the human element. The better we become at being human, at communicating, at reasoning, and at envisioning, the more the mirror of AI will reflect back greatness.”

The examples these teachers shared point to some of the many ways that AI and other technologies may open the doors to more interactive, student-centered activities in China and other parts of the world. But will they? In the end, I came back to the moderator’s initial questions that launched the entire forum: What is the role of teachers, students, and schools in artificial intelligence? Should we lead, or should we follow? These presentations taught me that teachers and students should be leading the way. To make that possible, rather than asking “what challenges does AI bring to education?” We need to bring the challenges of education to AI and demand a thoughtful and ethical response. 

Teachers and students should bring their questions and ideas to artificial intelligence. We need to tell the AI ​​designers and developers what education demands; what schools, educators and students need, and what problems they face. By truly challenging the designers and artificial intelligence itself, perhaps we can make AI a tool that expands our educational imagination. 

Next Week: Could concerns about the academic pressure on students in China lead to real changes in conventional schooling? Stability & change in the education system in China (Part 4)

Scanning the global headlines for recent news on AI, schools, and education: Rapid growth in uses, users, and concerns

A host of articles are chronicling the new developments — and the fears – in the uses of AI in K-12 education. To take stock of these developments, IEN pulls together links from a search for articles about and OECD’s Digital Education Outlook 2026 and a google news search for articles related to “AI schools education students learning” over the past month. Along with recent books like Artificial Intelligence and Education in the Global South and reports like Brookings’ A new direction for students in an AI world: Prosper, prepare, protect, these articles give a glimpse of what AI use looks like in different classroom contexts and highlight many of the concerns about those uses. These articles chronicle as well the efforts by many of the leading AI companies to cultivate new customers among students, teachers and schools. 

From OECD

OECD Digital Education Outlook 2026: Exploring effective uses of generative AI in education, OECD

OECD says generative AI reshapes education with mixed results, Cyber News

GenAI can turn students into passive consumers, OECD warns, Cyber News

AI gives a ‘mirage of false mastery’ The Australian

OECD: Many Flemish teachers feel overwhelmed by AI, Belgan News Agency

Generative AI reshapes education systems, Mexico Business News

Warning over uncritical AI use in education, RTE

Students trust AI over teachers on historical errors, The Chosun Daily

Digital idiots: University professors call for ban on use of AI in higher education, The Resident

Ban or Embrace? Portugal’s education system grapples with human cost of AI, Big News Network

AI around the world

Introducing OpenAI’s education for countries, OpenAI

Anthropic and teach for all launch global AI training initiative for educators, Antrhopic

AI and the digital divide in education, Frontiers

A conceptual framework on AI-related digital divides in education

AI in schools is harming learning, IFA

How AI is transforming education in Latin America and the Caribbean: Lessons from 193 solutions, IDB

BeConfident raises $16 million to expand AI tutoring platform beyond Latin America, Impact Alpha

Work 5.0, AI reshape education systems, Mexico Business News

The impact of digital learning in Mexico: Findings from an experimental study of the learning passport, Unicef

Critical success factors and major implementation barriers for digital learning

AI in education in Australia: Benefits, use cases & roadmap, Appenventiv

More math classes, AI, and new teachers: back to school brings new features in Paraná,

In China, AI is no longer optional for some kids. It’s part of the curriculum, NPR

 What can US schools learn about AI education from their Chinese counterparts?, K-12 Dive

Unsure how AI fits into education? One Prague school offers a practical, progressive model, Expats CZ

DepEd and Microsoft accelerate learning recovery and AI literacy for Filipinos, Microsoft

Schools from Berlin and Potsdam honored for AI ideas, Berlin

AI skills for life and work: Rapid evidence review, UK Government

Bloom’s taxonomy and AI literacy (Ng et al., 2021a).

Early introduction of AI in Ho Chi Minh’s schools proves effective, Asia News

AI Developments and Continuing Concerns

AI use in schools and classrooms is booming as educators grapple with guidelines, CBS News

The risks and rewards of AI in school: What to know, EdWeek

A new direction for students in an AI world: Prosper, prepare, protect, Brookings

Four takeaways from new report on AI’s risks in education, The74

Anthropic, Google and Microsoft fight to win teachers, Axios

Google’s work in schools aims to create a ‘pipeline of future users,’ internal documents say NBC News

OpenAI seeks to increase global AI use in everyday life, Reuters

Microsoft joins other companies in trying to fill ai training gap in schools, Education Week

Rising use of AI in schools comes with big downsides for students, Education Week

‘Dangerous, Manipulative Tendencies’: The risks of kid-friendly AI learning toys, Education Week

‘Grok’ Chatbot is bad for kids, review finds, Education Week

EU investigates Musk’s AI chatbot Grok over sexual deepfakes, PBS

Anthropic economic index: AI speeds up complex tasks, but deskills, StartupHub

Anthropic data shows AI boosts complex work fastest, with uneven impact across jobs and countries, ETIH

Artificial Intelligence mirrors natural intelligence: Can we move beyond human education years to hybrid intelligence?, Psychology Today 

‘What if I told you this school had no teachers?’: Is AI schooling the future of education — or a risky bet?, CNN

AI trailblazer Google doesn’t want schools to ‘Bypass the Human’, The74

1 in 3 Pre-K Teachers Uses Generative AI at School, EdSurge

How are K–12 school leaders managing the use of AI?, Education Next

How psychologists are using AI in schools, Psychology Today

Students turn to chatbots for college guidance, Smart Brief

AI assistive technology improves inclusion in K-12 environments, K-12 Dive

Short on resources, special educators are using AI – with little knowledge of the effects, The Conversation

How AI is helping NYC English teachers improve middle school reading and writing, The74

AI tutors are now common in early reading instruction. Do they actually work?, Education Week

Google DeepMind’s learnings in developing an AI Tutor, The74

Borrowing from the past productive friction in the age of AI, Getting Smart

I’m not worried AI helps my students cheat. I’m worried how it makes them feel, Education Week 

AI, Cellphones, Literacy, Students’ Mental Health, Political Turmoil and More: Scanning the Headlines for the Top Education Stories for 2025

IEN’s annual roundup of year-end reviews of top education stories and issues includes discussions of “tectonic” shifts in education related to AI and the actions of the current administration in the US as well as continuing concerns like the use of cellphones in schools, chronic absenteeism, learning loss, and students’ mental health. Here at IEN, major changes also include our exploration of ways to use AI to help us find and share articles related to educational policy, practice, and improvement around the world. Some of those results are included below. Next week’s post will focus on news and media stories discussing predictions and anticipated issues and trends for 2026. To see how education in 2025 compared to previous years, see the end-of-the-year scans for 202420232022202120202019 part 1, and 2019 part 2

Around the world 

The top 15 Education for All blogs of 2025, GPE

The ‘quiet’ revolution in schools: more and more countries are locking up phones – Part 1, World Education Blog

Are phone bans working? Part 2, World Education Blog 

Singapore: The top stories for education in 2025, Straits Times

End of UGC, two board exams and global campuses: How education in India changed in 2025, The Indian Express 

In 2025, Nigeria’s education sector experienced many reforms, challenges, Premium Times

Ghana: Education in Review: 2025 marks turning point, Ghana Web

Review of the year in England: Why we were all at sixes and sevens in 2025, School Management Plus

2025 review: A defining year for further education and skills in England, FE Week

In the US

2025 Research Roundup: 3 Pressing Themes Shaping Early Care and Education, The74

Looking back: What were the big events this year and how might they impact the field of comparative education? The FreshEdPodcast 

The top 10 education stories of 2025, Alexander Russo

California K-12 schools brace for another year of uncertainty: 2025 in review, CalMatters

Students in a classroom at Achieve Charter School of Paradise in Paradise on May 21, 2025. Photo by Miguel Gutierrez Jr.

Top higher ed campus safety stories from 2025: Hazing, Charlie Kirk, and Title IX, Campus Safety Magazine

2025 Year-in-Review: AI’s impact on campus security technology, Campus Safety Magazine

Fear, fatigue, gratitude: Students, parents and educators on the new Trump administration’s first year, Chalkbeat

Looking back at Colorado education in 2025,Chalkbeat Colorado

Year in review: Our top stories of 2025, District Administration

School boards: These topics were high priority in 2025, District Administration

5 education innovation trends to watch in 2025, eSchool News

The top 20 education next articles of 2025, Education Next

From classrooms to Sacramento: The education stories that defined 2025, EdSource

Revealing the top EdSurge K-12 stories of 2025, Rebecca Koenig, EdSurge

Most Popular EdSurge Early Education Stories of 2025, Lauren Coffey, EdSurge

The 10 most significant education studies of 2025, Edutopia

The top 10 EdWeek stories of 2025, Education Week

Trump’s Education Policies Spurred 71 Lawsuits in 2025. How Many Is He Winning? Education Week

The education-related policies that have attracted the highest numbers of lawsuits, Education Week

EdWeek’s Must-See videos of 2025, EdWeek

Here’s how AI is reinventing the end-of-year performance review, Forbes

How Trump 2.0 upended education research and statistics in one yearThe Hechinger Report

5 early ed highlights from 2025, The Hechinger Report

Philanthropy Awards 2025, Inside Philanthropy

The K-12 Dive Awards for 2025, K-12 Dive

Inside 2025: A year of urgency and the wins that mattered most New America 

2025 Year in Review: Year of change, tumult in public education, The North State Journal

The year in education: 25 of our top stories about schools, students and learning, The 74

Vax Rates, ESAs and Cell Phone Bans: 12 Charts That Defined Education in 2025, The 74

Why 2025 was a good year for education reform, Michael J. Petrilli, Thomas B. Fordham Institute

The 8 biggest education stories of 2025, Word in Black

National Education Association President Becky Pringle at a rally outside the U.S. Capitol

Teaching in the Age of Generative AI: Lead the Change Interview with Bernardo Feliciano

In October’s Lead the Change (LtC) interview Bernardo Feliciano’s discusses his work through the AITeach Co-design Lab at UMass Lowell; this work brings educators, researchers, and technologists together to co-create strategies and tools for teaching in this age of AI. The LtC series is produced by Elizabeth Zumpe and colleagues from the Educational Change Special Interest Group of the American Educational Research Association. A PDF of the fully formatted interview will be available on the LtC website.

Lead the Change (LtC): The 2026 AERA Annual Meeting theme is “Unforgetting Histories and Imagining Futures: Constructing a New Vision for Educational Research.” This theme calls us to consider how to leverage our diverse knowledge and experiences to engage in futuring for education and education research, involving looking back to remember our histories so that we can look forward to imagine better futures. What steps are you taking, or do you plan to take, to heed this call? 

Bernardo Feliciano (BF): Currently I am working with colleagues to build a co-design lab that brings together educators from very different contexts to develop approaches to teaching and learning in a world where generative AI is a reality. The lab is called the AITeach Co-design Lab @ UMass Lowell. (The hyperlink goes to one of many one-pagers we have been developing for partners representing different disciplines and sectors).

Bernardo A. Feliciano, Ph.D.

In the AITeach Co-design Lab, as collaborators we aim to create a structured space where we as a diverse group of educators, researchers, and technologists co-develop practical tools, strategies, and prototypes that respond to the reality of generative AI in education. The intention is not only to design usable products but also to study how to structure co-design itself to help schools navigate AI’s challenges and opportunities. In our co-design sessions, educators, researchers, and technology build spaces where we can address challenges in education and AI that are too complex for any one actor to solve (Snowden & Boone, 2007; Senge, 1990). The Lab functions as a structured environment where we can bring our problems of practice, iterate on small pilots, and use those cycles to build local capacity rather than waiting for top-down policy.

As an adjunct professor, I am also teaching a class on family and community engagement with schools. These roles constantly remind me that people bring distinct personal, professional, and institutional histories into every space. For me, futuring is less about projecting a single vision of “Education with a capital E” and more about the relational, actor-to-actor work of helping people shape their futures from the personal, professional, and institutional histories they inherit. That’s the direction my work is taking me.

The way I approach this is by convening diverse groups around developing tangible projects. The process matters as much as the specific product, whether it’s a research article, curriculum binder, a chatbot teaching/learning companion prototype, or a strategy for helping parents connect to schools. What is essential is how people can communicate their histories, connecting, adapting, negotiating, and reworking them to address problems in the present into a viable future. The varied personal and institutional histories participants bring are neither external resources to be tapped nor barriers to be overcome, but active materials in our negotiation of effective, situated teaching and learning. Innovation emerges as members work through these histories, adapting them in relation to one another to meet particular needs. I may not care whether my own work is labeled research, practice, or a mix of both, but as co-designers we must respect each other’s perspectives, even as those perspectives shift through negotiation. AI brings this into focus. At its core, AI is an immense bank or reservoir of the past, trained on and providing access to what is already known or has already been done. The future is not contained in the AI itself—nor can it be left to AI to imagine for us. The future comes from how we draw on that past to build something meaningful with and for the people in front of us. We explore generative AI as both a design partner and an object of study. Co-designers prototype tools like tutoring agents or parent communication bots, while also interrogating what it means to teach with, against, or around AI in everyday classrooms.

Of course, I have to use my own history, experience, and learning as a researcher, teacher, administrator, entrepreneur, and non-profit professional to leverage the network of histories that generative AI offers. But more than before, I can inform, contextualize, and connect the convening and teaching I do now with the work of so many more people and peoples (to some extent) who came before.

LtC: What are some key lessons that practitioners and scholars might take from your work to foster better educational systems for all students?

BF: One lesson is that teachers cannot be treated as passive implementers of someone else’s design. Too often, educational change is imagined as developing a curriculum or program in one place and distributing it everywhere. That assumes context does not matter and is peripheral rather than integral to learning and teaching. Our relationship to knowledge is always relational and always contextual.

Education has always lived in the complex space where cause and effect are only clear in hindsight (Snowden & Boone, 2007). Simon (1973) describes these as ill-structured domains existing in a state of dynamic heterogeneity in which diverse elements and relationships continually shift, preventing stable equilibrium and requiring ongoing adaptation (Pickett et al., 2017). Ill-structured problems cannot be solved by importing outside solutions but only by negotiation among those struggling with them. I do not believe that educational change—or improvement—comes from a fixed product or process delivered with fidelity. It is an ongoing process of learning through which people shape what they inherit—choosing what to keep, what to adapt, what to reject, and what to forget. It is a process I have found universally involves dynamics of local alliances, conflicts, and negotiations. The lesson I take from this is that if you want to improve schooling, you have to engage with the people who are doing the teaching and learning.

Working on my dissertation underscored this point. I wrote about using one-on-one meetings in a researcher-practitioner partnership to organize co-designing a computer science (CS) curriculum for middle schools. My experience brought home to me that there is no such thing as “shared understanding.” What emerges is never a single, final agreement but alignment good enough to act together, sustained through negotiation as perspectives shift. For example, teachers and researchers sometimes differed on how much detail a lesson plan should contain. Some wanted highly specified steps, others only broad outlines. Rather than force uniformity, we kept both versions and moved forward. That flexibility allowed the work to continue without pretending the difference had been resolved.

My work with different kinds of organizations has shown me how funding and infrastructure shape what is possible. This point is kind of obvious but still seems to bear repeating. Creativity and goodwill are not enough without sustainable and intentional support. For example, in the CS Pathways partnership, we shifted from MIT App Inventor to Code.org’s App Lab during remote learning. That solved one problem but created new ones around district procurement and accounts, showing how infrastructure shapes outcomes. In our recent Lab kickoff meeting, one participant noted that even when AI-enabled data tools existed, district procurement rules blocked their use — showing how funding and infrastructure filter what is possible.

At the same time, I saw that students’ and teachers’ own histories can be powerful resources for change, if we work out how to support them as they need to be supported.  In one part of the CS Pathways project, students framed their app design around civic issues in their community, such as neighborhood safety and access to resources. Their lived experiences pushed the curriculum beyond abstract coding skills into work that mattered locally. This reframed computer science as a civic as well as a technical practice and shaped how we sequenced and supported instruction in those classes. 

LtC: What do you see the field of Educational Change heading, and where do you find hope for this field for the future?

BF: In my experience, the field often moves toward building monoliths: “the system,” “the conceptual framework,” “the workforce,” “education technology.” Instead of these monoliths, we need to work with lesson plans and pacing decisions that make up “the system,” the overlapping frameworks that guide practice rather than a single “conceptual framework,” the varied teacher and student histories that constitute “the workforce,” and the specific tools and artifacts, from binders to chatbots, that become “education technology.” Monoliths can make things easier to talk about but also risk obscuring the negotiations and translations that are inseparable from those very systems. These relational dynamics are not add-ons. They are the system itself, as much as the actors are (Latour, 2005).  As in the earlier example of teachers’ differing preferences for lesson plan detail, the system took shape through the negotiation itself, not through a fixed agreement imposed from outside.

I would like to see the field shift toward paying closer attention to the actor-to-actor interactions and dimensions. That is where change takes shape: when people with different histories and contexts negotiate how to carry those histories forward. I see promising work moving in this direction: Playlab.ai’s participatory approach to AI tool-building, Victor Lee’s co-design of AI curricula with teachers, Penuel and Gallagher’s (2017) and Coburn et al.’s  (2021) and others’ emphasis on research–practice partnerships , and Bryk et al.’s (2015) improvement science cycles. The Cynefin co-design principles we are enacting in AITeach — probe, sense, respond — are themselves evidence of a field moving toward valuing negotiation and adaptation over fixed models (Snowden & Boone, 2007).

This is also where I find hope. In my dissertation research, I have seen how a small change in the structure of a meeting can reshape how colleagues relate to one another. Having a teacher go first in one-on-one meetings shifted the dynamic, allowing their concerns to set also frame a negotiation rather being a response to requirements. I have seen middle school students reframe ideas in ways that exceeded what I could have planned, such as attempting to build an app to help students and teachers share resources more effectively in school. Students translated apps they were familiar with into tools for their own purposes, which required reimagining instruction around their designs rather than trying to make pre-existing apps seem interesting. This approach may cause an instructional headache but least it provided an authentic motivation for learning an aspect of coding.

Some might call this the interest or work “micro-level,” but I avoid that term because it suggests hierarchies and fixed layers. I prefer to describe it as the translational dimension: the ongoing work of shaping futures from inherited histories by deciding what to keep, what to adapt, and what to let go.

Reimagining Coaching and Teachers’ Time: Scanning the News for Innovations in Teachers’ Professional Learning (Part 2)

This week, IEN’s managing editor Sarah Etzel continues a scan of recent news articles and research on post-pandemic developments in the teaching profession. In part two of the post, Etzel describes some of the initiatives to use technology to help to free-up time for teachers by reorganizing staffing and scheduling. Part one explored innovations in blended and remote teacher professional development models and the use of AI to provide feedback to teachers. 

What’s happened to teachers in the wake of the COVID-19 pandemic? On the one hand, in the US teacher vacancies appear to have grown substantially. One report released in the fall of 2023 showed 55,000 vacant teaching positions, an increase from 36,000 the previous year. On top of that, the report found that 270,000 teachers – almost 9% of the entire teaching force – are “underqualified,” either lacking full certification or teaching in a subject in which they are not certified. The National Center for Education Statistics also revealed that 86% of K-12 schools reported problems hiring new teachers in advance of the 2023-24 school year, and almost half of all public schools describing themselves as “understaffed.” On the other hand, the pandemic helped to stimulate experiments with new models for staffing and with virtual teachers that might help to address teacher shortages. 

Staffing Changes: Unconventional Teaching Roles

            Whether in-person or virtual, a small set of schools and organizations around the US are exploring what alternative teaching and staffing models for schools could look like. A report from FutureEd focusing on pandemic-inspired staffing strategies, for example, highlights the benefits of some co-teaching, team teaching, and mentor teaching models. Public Impact, working with a network of over 300 schools, has pioneered models designed to use teacher teams to enable teachers who have shown their effectiveness to reach more students. These “multi-classroom” leaders teach part-time and also lead small, collaborative teams of other teachers, paraprofessionals, and intern teachers in the same grade or subject. Cadence extends the reach of effective teachers by developing a national team of mentor teachers who deliver online lessons for a group of partner schools across the US. The teachers in the partner schools both learn from the mentor models and they can incorporate the lessons into the work with their own students. As Steven Wilson, a co-founder of Cadence, puts it: “It’s like being able to sit in the back of the room of the best teacher in the building for weeks at a time and see his or her moves and adapt them and make them your own.”

The FutureED report also emphasizes the potential of flexible class sizes, time blocks, and instructional cycles that allow for teachers to work with smaller groups of students outside of traditional grade-level and schedule constraints. As an example, the report highlights a particularly unusual approach from Kairos Academies in St. Louis that developed a seven-week schedule in which students attend school for five weeks, followed by two weeks off; staff have one week off, but use the other week to review data and plan for the next cycle. The report quotes, Gavin Schiffres, Kairos founder and CEO, describing what he sees as the advantages of the cycles; “With the cycle model, we operate in sprints, much like the technology industry. In a traditional calendar, you have kids in the building for such long stretches that as soon as there’s a break, everyone just wants to crash.” 

Drawing on interviews with a small group of leaders from six districts involved in staffing experiments, the Center on Reinventing Public Education issued a report on how unconventional teaching roles could help to make the profession more sustainable and increase teacher satisfaction in the process. Some of these roles include: 

  • Lead teacher: An individual who mentors a team of teachers (across content areas or grade levels) by developing curricula and co-teaching as necessary 
  • Empowered teacher: An individual who supports with school-level policies and sets learning targets 
  • Team teacher: An individual who teaches a large group of students (50-80) in collaboration with two to four other teachers 
  • Community learning guide: An individual who works with a group of educators and their students to create experiences grounded in students’ wider environment, community, or culture. 
  • Solo learning guide: An individual who independently teaches a small group students (5-15) in school or home contexts
  • Technical guide: An individual who leverages subject area expertise (e.g. robotics, architecture) to provide curriculum support and work with small groups of students 

According to the report, teachers in these roles shared that they experienced less stress and felt more motivated; working in diverse or team settings, teachers were able to share responsibilities, learn from each other, and feel connected to the purpose of teaching. Despite the potential, a review of the CRPE report from the National Education Policy Center cautions that it is too early to tell whether these kinds of staffing changes could be scaled effectively or whether they would have the desired impact. 

In order to address the shortage of teachers and support those that are in place, some schools in the US have also introduced models to support paraprofessionals to gain teaching credentials and become licensed teachers, while others have created pipelines for substitute teachers to gain teacher certifications. Beyond the US, organizations such as GPE KIX and UNICEF have been pioneering child-to-child teaching models, in which older students support the education of pre-primary learners, in areas where there are not enough teachers available (for past IEN coverage of peer-to-peer tutoring approaches, see: Education reform in MexicoAn interview with Dr. Santiago Rincón-Gallardo, and Bringing Effective Instructional Innovation to Scale through Social Movement in Mexico and Colombia).

Virtual teachers for in-person students

Along with developing new virtual and hybrid approaches for students to learn, during and after the pandemic, reports also note that some districts are spending millions of dollars on virtual teachers to fill-in when they can’t find the personnel they need in their local area. Among these, districts in Little Rock, ArkansasCharleston County, South CarolinaSan Jose, California, and Milwaukee Wisconsin have contracted with companies such as Elevate K-12Coursemojo, and Proximity Learning to address their teacher vacancies and to provide virtual instructors who zoom into their classes. These companies employ fully certified virtual teachers who provide “synchronized learning services” in a range of subjects. The virtual teachers interact with students completely through the online platforms, with, in some cases, in-person supervision provided by paraprofessionals or long-term substitute teachers. 

"live teaching" model

Elevate-K12’s model of “live teaching”, The 74

The benefits and drawbacks of these approaches are also being debated in the press. For some, these virtual options provide an alternative to other “quick fix” solutions that have been used to fill empty classrooms in the past, including hiring uncertified teachers, incentivizing military veterans to join the teaching force, or removing some degree requirementsAccording to the CEO of a San Jose charter school network that contracts with Coursemojo, this situation is not ideal, “but until we really, radically change the education profession here in the United States, we’re going to be looking at solutions like this.” Catherine Schumacher, Executive Director of Public Education Partners stated the importance of not shaming “districts for doing the absolute best they can do to get qualified teachers,” especially in a climate where “we have systematically underpaid…educators for years.”  

Other advocates argue that the subjects virtual teachers are teaching have historically been hard to fill, meaning many students did not have access to these educational opportunities, particularly in low-resource school districts. As the Milwaukee Public Schools talent management director put it: “when we talk equity and access, I want to ensure that if my students want to take pre-calc, if they want chemistry, if they want physics, that they have the opportunity to do so.” 

The cost-effectiveness of the virtual models also remains in question. For one school district in Milwaukee, Wisconsin, a contract with Elevate-K12 helped them fill 55 open positions at a cost of about $3.9 million, a savings from the $5 million it would have cost to hire that many in-person teachers. A district representative reported that they were able to save the $1.1 million because they did not have to provide benefits for Elevate K-12 teachers. In contrast, a school district in Charleston County, South Carolina that has used the virtual learning platform, Proximity found that these models were more expensive, as the schools needed to hire paraprofessionals to watch the students during the virtual classes. 

Critics point to the fact that there is not yet enough evidence to show that students are achieving positive learning outcomes under these models, but proponents such as Elevate K-12 founder Shaily Baranwal, argue that virtual teaching during Covid-19 took place under emergency circumstances and, with more time to prepare and focus on delivery methods, post-pandemic virtual teaching could be particularly effective. Critics also question whether students’ social experiences and sense of belonging will suffer when they have virtual teachers, and some wonder who will be held accountable for student learning under blended learning models (i.e. the paraprofessionals who are in class every day with the students, or the virtual teachers?). With all these uncertainties, many parents remain skeptical of this virtual  solution and question whether virtual teaching will be the best fit for their children. 

The bottom line? Freeing up time to teach? 

At the end of the day, the success of any of these “innovations” in professional learning depends on whether they can be put in place without adding to teachers already overloaded schedules and extensive set of responsibilities. Post-pandemic articles continue to highlight challenges like a lack of planning time for teachers and excessive time spent in staff meetings as well as hopes that AI may help address these issues by freeing up teachers’ teachers time from administrative tasks and helping teachers create differentiated assignmentsThrough a survey of 368 school-based employees across the U.S., AI-Equity found that 84% of those who used AI in the Daily/Weekly category reported they were “more excited about continuing education sector work because of AI,” compared to 52% of all respondents, while 94% of Daily/Weekly AI users shared that it made them more productive. According to research from MIT, AI can improve the performance of skilled workers in fields such as consulting by approximately 40%. A report from McKinsey and Co. estimates that teachers could free up 20-30% of their time by using AI and other technologies to support activities such as preparation, conducting evaluations and giving feedback, administrative duties, and professional development. The Christensen Institute argues that teachers may not use their reallocated time for increased student engagement without proper incentives, but freeing up teachers’ time could help to alleviate burnout and increase the attractiveness of the profession. 

How artificial intelligence will impact K-12 teachersMcKinsey

However, sources also caution that AI should not be viewed as a panacea for solving these issues, and in fact, may exacerbate some of the challenges that teachers face. As one teacher explained, the expectations developing lessons incorporating AI and other forms of technology “takes extreme planning, and that, we don’t have time for anymore.” Moreover, the increasing use of AI raises numerous questions about the potential impact on students’ learning and development. In particular, as Julia Freeland Fisher cautions, the education market doesn’t prioritize relationship building within its attainment metrics and so may fail to take into account AI’s impact on those relationships. Under those conditions, as Freeland Fisher put it, “the more commonplace that AI companions, coaches, and anthropomorphized bots in learning and support models are, the more fragile students’ social connectedness may become.”

The Threat & Promise of Advanced Technology in Education: Reflections from the Atlantic Rim Collaboratory 

This week IEN shares key ideas and resources from two meetings of the Atlantic Rim Collaboratory (ARC) that engaged policymakers and education leaders in exploring the potential of AI in education. The meetings included an ARC pre-Summit ThoughtMeet with A Focus on Democracy & AI Advanced Technology (like ChatGPT) in Schools, and the annual in-person Summit in Oslo, Norway that included a “Focus on AI and Education”. ARC co-founder and Learnlab CEO, Yngve Lindvig, offered some provocations as well as an opportunity to play with ChatGPT. 

ARC brings together members of education systems and organizations such as Ireland, Iceland, Scotland, Uruguay, Wales, and the Canadian provinces of Nova Scotia, and Saskatchewan, and the International Confederation of Principals (ICP). Summaries and materials from previous ThoughtMeets are available on the ARC Education Project website. This article was written by Mariana Domínguez González, Sarah McGinnis & Trista Hollweck.  

Ready or not, advanced technology (like ChatGPT) is part of the educational landscape, Yngve Lindvig declared. Even as the debate continues on the possibilities and consequences for schools and higher education, educational leaders must make policy decisions on artificial intelligence in their systems that take into account key questions like: 

• How can we make sure that pedagogy drives technology and not the opposite?

• How do we make AI generated data relevant for teachers and students to support learning?

• How can teachers and students be data generators and critical users?

• How can teachers be their own data managers and have access to effective tools for data informed feedback in real time?

• How do we know the data we use is ethical and complies with General Data Protection Regulations (GDPR)

In this context, Lindvig argued, ChatGTP and advanced technology should be embraced, rather than feared, but in a thoughtful and reflective way. Although many governments and system leaders are concerned about the speed of change and a lack of control over AI, banning its use in schools and higher education is not the answer, he continued. AI has the possibilityto disrupt established instruction and assessment practices tosupport student learning in new and powerful ways, but its threats must not be taken lightly, he warned.

Addressing both threats and opportunities, Lindvig described how data-informed learning can be a critical element of effectiveAI use in schools, where data are generated by the students andare used in the learning situation. Since the origin of content in most data management systems is unknown, however, a number of risks must be considered when using AI generated data in schools. These include lack of diversity in content, creating an echo chamber of self-reinforcing opinions and sources, and promoting content that may not be aligned with priorities in educational systems. The main problem is that when a student uses AI generated data, the output is not derived from the student’s critical thinking, reflection, ideas, or product, but it is outsourced to a machine that disconnects the student from the learning. On the other hand, Lindvig explained, if you are able to make an AI-empowered solution within your system, controlled by your system, linked to the curriculum, tagged with curriculum goals, incorporating student feedback based on the intentions in the curriculum, then we have a system that could actually change something.

For Lindvig, perhaps one of the most powerful changes that AI could bring to education is a shift from more traditional assessment practices (such as essay writing and tests) to production-based formats where students must demonstrate their learning in multiple ways using a variety of multi-modal formats. When AI is assessing multi-modal products aligned with the goals that the teacher sets for the learning experience, then the teacher also gets something in return for using advanced technology. Additionally, AI used for assessment can engagestudent learning and provide immediate feedback within the classroom. Of note, AI implementation guided by teachers’ goals ensures that the feedback provided to students is aligned with the educational system’s curriculum and not “big tech” controlled algorithms.  After testing this type of AI implementation in Scandinavian schools in May and June, Lindvig noted that teachers reported that the AI feedback on student work was aligned with the values in the curriculum and that it provided them with more time to communicate with their students.

So where do system leaders start in order to implement an AI-empowered solution that is pedagogically relevant? According to Lindvig, systems should:

• Own the login platform, even if a company runs it for the system. 

• Control the student catalog which contains the data.

• Implement very strong General Data Protection Regulations, and decide –at a federal, provincial and/or municipal level- which applications are allowed to be used.

• Own the curriculum by making sure that the applications filter the information so that it includes only the content that is relevant and pertinent to the national/provincial curriculum.

ARC Pre Summit March 2023 Yngve Lindvig

Yngve Lindvig´s ARC Talk on The Promise & Threat of Advanced Technology in Education

Previous IEN posts from ARC include A Focus on (Imperfect) Leadership: Snapshots from the 9th ARC Education ThoughtMeetWell-Being, Social Emotional Learning (SEL) and the COVID-19 Pandemic: Snapshots from the 8th ARC Education Thoughtmeet; and The ARC Education Project: Rethinking Secondary Examinations and Credentials. Previous IEN posts on AI include: ChatGPT on ChatGPT in education: Clear summaries and fake citations (The ChatGPT six month anniversary edition Part 1)Ban It or Use It? Scanning the Headlines: The Chat GPT six month anniversary edition Part 2Scanning the headlines for international perspectives on ChatGPT in schools: The Chat GPT six month anniversary edition Part 3and What difference will AI make in schools? Scanning the headlines on Chat GPT’s six-month anniversary (Part 4).