Camille Faivre has spent years navigating the complexities of education management, particularly as institutions transitioned into the high-stakes landscape of the post-pandemic digital era. Her work focuses on the intersection of pedagogy and instructional technology, helping schools implement e-learning programs that prioritize student growth over mere automation. As a specialist in education management, she provides a vital perspective on how we can move past the initial fear of plagiarism toward a future where artificial intelligence serves as a sophisticated catalyst for literacy. In this conversation, we explore the evolving role of AI as a collaborative thought partner, the use of voice-to-text technology to empower diverse learners, and the urgent need for school leaders to provide educators with the space to experiment before setting rigid classroom policies.
Many students use AI like a traditional search engine, but it can also serve as a responsive partner for formulating complex arguments. How can educators design assignments where AI generates rebuttals for a debate, and what steps should students take to verify the credibility of the sources provided?
When we treat AI as a more robust version of a search engine, we barely scratch the surface of its potential to increase the rigor of our classroom assignments. Instead of asking a student to simply summarize a scientific argument, we can have them input their initial claims into a tool like Perplexity to generate three or four targeted justifications and rebuttals. This turns the writing process into a vibrant, back-and-forth exchange where the student has to defend their position against a tireless, researched opponent. The critical step here is the verification process; because Perplexity provides direct links to resources, students must spend time investigating those citations to determine if they are reputable or merely digital noise. This teaches a vital form of modern literacy where the student isn’t just a writer, but an investigator who must decide which pieces of evidence are strong enough to support their final rationale. It allows us to elevate the complexity of the lesson without burying the teacher in extra hours of prep work or lecture delivery.
Viewing AI as a digital editor can help students refine the clarity and consistency of their writing. How can teachers coach students to request structural critiques rather than just finished outputs, and what specific exercises help differentiate between shortcutting a task and using the tool as a linguistic calculator?
The most effective way to coach students is to shift the focus from the “finished product” to the “process of articulation,” treating AI as a linguistic calculator that helps solve for clarity. Just as a math student uses a calculator to handle complex computations so they can focus on high-level theorems, an English student can use AI to check for structural consistency in a long-form essay. Teachers should encourage students to upload their drafts and specifically prompt the AI to identify where their logic gaps exist or where their tone becomes inconsistent. For example, a student might arrive at a personal breakthrough in their narrative, but they may struggle to connect that insight back to their main thesis; the AI can point out that specific structural weakness without doing the thinking for them. By framing the tool as a coach that provides feedback on how well they are communicating, we help students avoid the trap of “cheating” and instead help them develop the professional skill of iterative editing.
Voice-to-text technology can lower barriers for learners with dyslexia or language differences by separating the thinking process from spelling or keyboarding. How can real-time feedback on pronunciation and vocabulary suggestions transform a student’s drafts, and what creative boundaries are removed during this process?
For many of our most diverse learners, the greatest obstacle to literacy isn’t a lack of brilliant ideas, but the physical and cognitive friction of getting those ideas onto a page. AI-powered transcription tools act as a powerful bridge, allowing a student with dyslexia to dictate a science procedure or a creative story without the paralyzing anxiety of spelling every word correctly in the moment. When these tools provide real-time feedback on pronunciation and offer synonyms that better match the intended tone, it creates a sense of empowerment that was previously out of reach for many. English Language Learners, for instance, can hear their own spoken words played back with clear, consistent pronunciation, which builds their confidence and fluency simultaneously. By removing the technical barriers of keyboarding and handwriting, we allow the student’s authentic voice to emerge, ensuring that their creative expression is no longer limited by their mechanical struggles.
Integrating AI into the classroom requires teachers to experiment with the technology before guiding their students. What specific frameworks should school leaders provide to give educators the time for this experimentation, and how do these internal pilots help determine where to draw the line on acceptable use?
School leaders must recognize that we are in a moment of rapid transition, and the first step is to officially grant teachers the “permission to play” with these tools before they are expected to implement them. This means creating internal pilot groups where educators can test various AI platforms to see which ones actually enhance their specific curriculum and which ones lead to undesirable shortcuts. By giving teachers dedicated professional development time to engage with the technology as learners themselves, they can identify the specific moments in a lesson where AI adds value—such as helping a student brainstorm a list of themes—and where it might cross the line into doing the core work. These pilots serve as the foundation for school-wide policies, ensuring that our rules are based on practical classroom experience rather than just fear of the unknown. We have to act fast to intervene and coach students, but that coaching is only effective if the teacher has already mastered the tool’s nuances.
What is your forecast for AI’s role in shaping literacy instruction over the next decade?
Over the next ten years, I anticipate that AI will become an invisible but essential infrastructure in every literacy classroom, moving away from being a “novelty” and toward being a standard partner in the cognitive process. Literacy will no longer be defined solely by the ability to spell or format a document, but by the ability to curate, critique, and refine ideas that are generated in collaboration with intelligent systems. We will likely see a massive shift in how we assess student work, moving toward “oral defense” models or “process-based” grading where the evolution of an idea matters as much as the final text. I believe this will actually lead to a Renaissance in human-centric writing, as the “mechanical” parts of communication become automated, leaving more room for students to focus on deep reflection, empathy, and complex reasoning. Ultimately, the goal is to use these tools to amplify the human voice, making sure that every student, regardless of their learning differences, has the power to be heard clearly by their intended audience.
