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If you were to read a random sample of articles on generative AI’s potential impact on teaching & learning, you’d come away with a fairly bleak view on the state of classrooms. The prevailing thinking seems to be that teachers are inundated with thousands of short, often unrelated tasks. And that the most humane thing that we can do as developers is to take some of those off their plates; find a teacher's pain point and smash it. Repeat.

At CommonGood we have a very different view on teaching. We believe that most teachers are deeply interested in big ideas, ways those ideas connect to their students’ lives and planning learning experiences that will make them come alive. We think that given the option, teachers will dedicate a large portion of their attention to this process. Rather than casting teachers as the task mistress that barely keeps chaos at bay, could we behave as though teachers are called to deeply think and expertly plan as a fundamental part of their practice?

In a recent interview OpenAI CEO Sam Altman suggested that we will soon transition from using AI to solve small, five minute problems to solving more complex problems. “Someday they’ll do 10-minute tasks, and then they’ll do an hour-long task,” Altman said. “But you’ll still have to think about, ‘How is this all going to fit together? What do I want to build?’” That sounds more like it. At CommonGood, we don’t see supporting teachers’ core work as a five minute problem - and we have an opinion on how things fit together.

For around a decade, our founders have gathered educators in cohorts to deeply consider their students’ communities, the learning that will be most compelling to them, and flex our collective learning science muscles to design learning experiences that will lead to good outcomes. These processes are time consuming, intellectually rigorous and sometimes personally demanding. They often challenge our assumptions, shine new light on the communities we serve and stretch our capacities. Educators also love them - this work can build new mindsets and communities of practice. Some have even said that it reinvigorated their love of teaching.

That’s good stuff. Perhaps even better is what these approaches yield for students. In a recent paper, we lay out how similar approaches don’t suggest incremental improvements to student outcomes. They suggest that transformation is possible. 

But these approaches require expertise and dozens of hours of work for participants. Few communities have the bandwidth to take this on. Enter Collaborative AI. CommonGood Co-Founder Kyle Morton designed a workflow management platform, with AI-powered supports for each step in the design process. Like the cohort-based approach, teachers are presented with the underlying theory for each step, along with recommendations and ideas on how to execute it. The educative process both builds fluency with evidence-based learning design techniques and maintains the centrality of the teacher. 

Even maintaining healthy skepticism and high standards for outputs, the affordances of the technology showed promise early on. “I’m a self-described design snob” said Co-Founder Dr. Carly Muetterties. “I think that because the design processes are so well defined (leaning on peer-reviewed research and frameworks, lots of examples to reference) that the technology is very good at following those guidelines and making contextualized recommendations. The tools added value to my own design process very early on.”

Well-defined processes with lots of reference material is key to the shift being proposed. Using generative AI (or really any technology) to identify a small bug or teacher pain point and smash it doesn’t require much fluency with education theory or learning science. It presumes that when a product has been built to smash a bug, those involved will use the audience that they’ve built to find / smash bigger bugs. But it can be difficult to make the transition from peripheral to more core problems of practice. By starting with well-established evidence-based models, there is already a tremendous amount of information on what works, how pieces fit together and what good outputs look like. 

We tested and iterated on the design process over the course of years, working with and gathering feedback from lots of educators and across a variety of contexts. We’ve compiled a huge amount of data on how design steps fit together, how to coach people on them, and what predictably leads to usable outputs. We’ve done a lot of (peer reviewed) writing on these processes as well. An evidence-based approach is by its definition, well-defined.

And generative AI seems well suited to facilitate defined processes, particularly when there are lots of examples to reference. “When we set out on this build,” shared Dr. Carly Muetterties, “we’d hoped to make the process more efficient for ourselves and our clients. We have been successful there - in our use we realize a 70-85% efficiency gain. What we didn’t entirely expect is that we’re discovering that the platform can make these approaches even more effective. In my own practice, the platform generates well-reasoned recommendations for me to consider (which pushes my thinking), surfaces sources that I wouldn’t likely have found, etc.. It’s humbling sometimes, but the technology has made me a better designer.”

Suggesting that technology be used to facilitate established models has a few important implications. First, we should stop casting teachers as an ‘in over their heads’ class of quasi-professionals constantly combating burnout. Rather we should work on the assumption that they’re learning science practitioners, constantly using, testing and informing the evidence base on what works in classrooms. Second, we should build tools in close partnership with people who have practice applying that evidence base to core problems. We should expect to be able to see what experts, what models, what evidence are informing the technologies that are being developed for classrooms. 

Our platform is being tested by partners on curriculum teams at both school districts / operators and solutions providers. These partners are among the most discerning and demanding users we could find, most with decades at the forefront of evidence-based R&D. We are excited to share more about what we learn from these partners in the months to come.

In sum, we think that the best application of something as powerful as generative AI is to make proven models more accessible. Improving curriculum & instruction is not mysterious, just very difficult. Thankfully we have 100+ years of learning science that holds unrealized potential. Our use of generative AI so far is that it can make complex and difficult tasks less complex, and time consuming processes dramatically less so. We want to use this new technology to allow teachers to take on more - more inspiring, deeply impactful, even transformative work - not to do less. 

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We're excited to announce that the CommonGood team is growing in an important direction! Earlier this year, Kyle Morton joined us as a co-founder, bringing his expertise in tech and product development. With a solid background in building SaaS companies and a deep understanding of search, AI, and educational technologies, Kyle will help CommonGood reach more educators with better products.

“The AI revolution is in full swing, and there are many solutions for students and teachers already—some good, some not so much. What drew me to CommonGood is our shared vision to keep humans at the heart of education while finding ways to save time and money without cutting corners. It’s the kind of challenging problem I love, and I’ve found great partners in Carly and Evan,” Kyle shares.

Kyle’s career highlights include founding HapYak Interactive Video, a leader in video-based training, which Newsela acquired in 2021. Before HapYak, he led product strategy at RAMP, launching the first scalable video search solution for media companies. He also co-developed one of the first mobile advertising solutions at Third Screen Media, later acquired by AOL.

“The co-design approach at CommonGood is exactly what we need right now—creating educational resources that are culturally sustaining, locally relevant and highly effective. The big challenge is scaling it. This is a unique moment where technology can really help solve this problem. I’m excited to lead our efforts to use Ethical, Collaborative AI to make life easier for curriculum developers, teachers, and students,” Kyle adds.

CommonGood focuses on co-designing curriculum resources with and for diverse communities. By bringing together educators, community leaders, experts, schools, and districts, we collaboratively envision and create curricula that are both better and more reflective of the students they serve.

“Collaborative AI is about applying AI to real problems in real contexts, combining what algorithms do well with what humans do best. I believe this approach to curriculum development and customization will drastically reduce costs, exactly when institutions need to save money, while radically increasing the number of students who benefit from high quality educational materials.”

Kyle will be working closely with the CommonGood team, educators, and curriculum designers to develop solutions that enhance and amplify their work. We’re looking forward to the innovative strides we’ll make together.

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Representation in education is not just about visibility; it's about authenticity, student empowerment, and the opportunity to see one's own experiences reflected in the broader narrative. The matter of representation is particularly important in connection to Queer Studies and LGBTQ+ history. 

The LGBTQ+ community continues to be virtually absent from formal curriculum, state standards, and textbooks. Instead, according to scholar JB Mayo, “[o]ften, students who identify as queer never encounter examples of other LGBTQ people in their school lessons. For many, in fact, only negative stereotypes are presented as part of their daily existence at school.” 

Learning social studies through the lens of gender and sexual orientation—central concepts to gender and LGBTQ+ studies—provides a valuable pathway for understanding citizenship, as well as justice and discrimination. Despite the opportunities for inclusion, the LGBTQ+ community remains generally absent in curricular resources, with the current politicization of diverse peoples being, likewise, a hindrance to authentic inclusion. 

To that end, our recent inquiry module on LGBTQ+ rights and marriage equality, designed for upper elementary students, demonstrates one pathway for bridging LGBTQ+ content into curriculum authentically and meaningfully. 

What makes “equality” equal?  Though a simply-worded question, it is rich with meaning—particularly for communities whose “equality” in the United States has regularly been denied. Created in a co-design process (with Cam Lloyd and scholar Michael Bronski), this question frames students’ exploration of the advocacy for, and public response to, marriage equality in the United States. By investigating the question, students problematize the concept of equality to consider a more nuanced definition that considers both legal equality (de jure equality) and social reality (de facto equality). 

Through this resource, we wanted to center the LGBTQ+ community in such a way that aligned with state and national frameworks, but also sought to normalize inclusion of these histories within larger national narratives. In other words, the impetus for this inquiry had much to do with normalizing the LGBTQ+ community’s experiences as being a part of civil rights movements. We believe this approach to centering is novel, but incredibly important in authentic representation. Rather than positioning LGBTQ+ voices as standalone or distinct, the community’s struggle for civil rights is framed as an example of the United States’ larger rights struggles. 

One of the key components of our approach was the intellectual preparation of teachers. We recognize that many educators feel ill-prepared to teach LGBTQ+ content, often due to a lack of professional learning opportunities and the politicization of the topic—the community’s very existence is often the heart of political controversy. 

To support teachers, we developed resources that provided foundational knowledge and analytical lenses to facilitate rich engagement with the content. We anchored our preparation on key suggestions from scholar Paula Greathouse (and colleagues) for incorporating LGBTQ+ topics into the curriculum. These suggestions included teachers acquiring a deep understanding of the content and its significance, knowledge of local policies, and creating a plan to defend curricular choices.

The current moment leaves teachers in the crosshairs of larger political culture wars. But the responsibility for inclusive learning is not on their shoulders alone! Much responsibility falls on curriculum providers to demonstrate authentic and meaningful ways to support inclusion and represent students’ diverse communities.

How do you incorporate LGBTQ+ voices? Let us know!  Contact us


Works Cited:

  • Paula Greathouse et al., “When Inclusion Meets Resistance: Resources for Facing a Challenge,” English Journal 110, no. 1 (September 1, 2020): 80–86,

  • Mayo, J. B. (2019). Engaging Two Spirit Knowledge as a Means to Deconstruct the Gender Binary. Social Studies Journal, (39)1 (2019): 7.

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