Getting a Community of Practice Off the Ground
Students are already using AI on their own, which may be good news. “With guidance, structured use of AI can lead to actual improvement in student learning and deeper engagement,” Martinsen says. But to be effective as instructors, teachers need to know how these tools operate and what they can do.
To that end, Jennifer Garner, a biology professor at Ventura College and president of the academic senate, attended a statewide training session in spring 2025 and returned with the idea of ramping up CoPs at Ventura. To get that up and running, leadership from the academic center helped create a program to train the trainers.
“We put out a call for a leadership team developer, which ended up being Jennifer because she had just done the training,” Martinsen says. Then a call went out for five faculty who were interested in leading AI-focused CoPs.
Those faculty members focused on different areas of AI adoption. Martinsen, for instance, already uses a Family Educational Rights and Privacy Act–compliant AI assistant, “and the focus of my community of practice was, how do we use a tool like this to engage with students or maybe do our own work?” he says.
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Bringing the Community of Practice to Life
The five trainers spent the fall semester meeting a few times a week, preparing themselves and developing their training materials. Then the CoPs were opened to participants.
To generate buy-in, the school offered financial incentives. Faculty were offered a $1,250 stipend to take part in the CoPs. Each trainer would take on a cohort of 10; the planning team received about 80 applications for 50 available slots.
The actual format for the CoPs varied, with some meeting in person and others on Zoom. “Some of the trainers ran theirs a little like a seminar class, where everyone has a point of view,” Martinsen says. “Others were a more leader-directed.”
Technology was essential to making these learning sessions effective. Trainers used platforms such as Canvas and Google Docs to post resources and facilitate conversations among the participants.
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It was also important to establish deliverables to demonstrate the impact of the effort. Each trainer established outcomes that could be measured at the end of the training.
Within each CoP, “there was some expectation that some work would be completed,” Martinsen says. In his case, he asked faculty to make practical use of AI platforms to develop bots or apps, and others did likewise within their CoPs.
Lessons Learned From Developing Communities of Practice
Other colleges and universities can take away some key lessons from Ventura’s experience. First, this kind of effort requires strong leadership. In Ventura’s case, senior leaders had a shared vision and a commitment to making it work, Martinsen says.
Persistence pays off as well. “We actually cycled through multiple vice presidents for academic affairs as this was being set up, and I give Jennifer a lot of credit for managing all those transitions. She was able to say: ‘Your predecessor approved this, here’s where we are in the process, we need to do the next step.’ And that iterated several times,” Martinsen says.
The IT team can play a key role in delivering the infrastructure that supports an AI-focused CoP.
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“We definitely relied heavily on Zoom and other collaborative platforms,” Martinsen says. And then there are the AI tools themselves, with their respective licenses. IT can support the availability of those tools, ensuring that the right licensing is in place and that faculty know how to access the platforms they need.
As the CoPs’ impact proliferates, IT can help by ensuring equity at the student level. “It’s a huge advantage for students who are struggling financially to be given free access or institutional access to a professional-level AI tool,” Martinsen says.
With trained faculty and the right tools in hand to support AI communities of practice, students can take the technology and run with it, in ways that are both effective and responsible.
