Tag Archives: Education

student blogs

blog 7

“An A.I. Translation Tool Can Help Save Dying Languages. But at What Cost?” was honestly one of the first AI-centered pieces in this class that didn’t leave me feeling scared, disgusted, hopeless. After Ebony and my’s pathfinding presentation, I felt pretty bleak regarding any sorta Ai reading/early literacy centered gadgets. So, I understandably felt quite hesitant before reading.

However, as I worked through this article, my demeanour shifted for the better. I have loved learning about different languages my entire life and value how it shows a group’s or culture’s story- past and future.

While this article largely focused on how the tech represented previously ignored and unrepresented certain Asian-centered languages, my mind drifted towards imagining how this application can breathe new life into Native American languages.

After reading Natalie Diaz’ I”f What I Mean Is Hummingbird, If What I Mean Is Fall Into My Mouth,” a few semesters back, I had feelings of both deep admiration and deep sadness for the layers upon layers of meaning n history embedded into indigenous people’s native tongues. After being colonized and forced to retreat such a beautiful form of communication, more n more Natives stopped speaking it, and were unable to keep such a priceless method of sharing n communicating as nursed n nurtured as it should be.

Inserting such indigenous languages into an app like this would be incredibly helpful. Descendants of native speakers can connecting to the language of their grandparents and parents in such connective ways. People can begin to promote such a connection and multilngualism in their small children. Even grown adults could learn, or relearn, the language through translated, accessible fairy tales HOWEVER………………….

Idk just seeing how our country has horribly treated indigenous people…. I feel nervy introducing such an idea. Ai and its environmental impact will likely hit these populations the very hardest. And…. all these things I am discussing n sharing can still be done with REAL people- not robots. Still.

Everything Ai is new n shiny. And cheap. At least this present doesn’t have a bomb (directly) strapped to it..

student blogs

When “Help” Starts to Feel Like Control

Reading Richard Sťahel’s article reminded me that AI is never just about convenience. It is not just about students finishing work faster or teachers saving time. It is about power. Who has it, who controls it, and who gets trained to depend on it.

That is what I found most striking in this piece. Sťahel argues that AI is not politically or environmentally neutral, and honestly, that feels obvious once you sit with it. These tools are built by corporations, not democratic communities. They are designed around growth, data, attention, and dependence, not around truth, equity, or education. Schools may use them, but schools did not shape their values.

As a teacher, I see a smaller version of that problem every day. Students already treat AI like an authority figure. If it gives them a polished answer, they trust it. If it sounds smart, they assume it is right. The issue is not just cheating. It is that AI can train students out of the habits real learning requires: questioning, struggling, revising, and thinking for themselves. I have read work that sounded brilliant on the page and completely collapsed the second I asked the student to explain one sentence out loud.

The article also pushes beyond the classroom and into something bigger. AI is sold as sleek and efficient, but it has real costs. Environmental costs, political costs, human costs. It depends on physical infrastructure, massive energy use, water, materials, and systems most ordinary people have no control over. So while society keeps marketing AI as the future, very few people are asking what that future is made of and who pays for it.

That is why this reading landed for me. It names something that gets buried under all the hype: AI does not just help people do things. It shapes habits. It shapes trust. It shapes dependence. And in a classroom, that matters. If students keep learning that every hard task should be outsourced, then we are not just changing how they work. We are changing how they think.

So no, I do not think the answer is panic. But I also do not think the answer is blind excitement. Students do not just need access to AI. They need literacy about it, boundaries around it, and enough confidence in their own minds to know that fast, polished, and confident are not the same thing as true.

That connects directly to the videos. Every single one shows what happens when systems meant to “help” start watching instead of trusting.

The first video, #tresdancing, hit the hardest for me. I understand the frustrations of at home testing. Not having the space to test effectively, people passing while I’m testing, having to show everything on camera. I have literally had to take my glasses off and show the camera that they were regular glasses and show them each piece or scrap paper I was using. And I have like the worst test taking anxiety known to man. One time I was having technical issues, reached out to the proctor, they took forever to get back to me, so the time lapsed and I could no longer take the test and I never got a refund. The test was 250. So I understand the lengths of what a person might go through to not experience that again. At some point, it stops being about fairness and just feels like punishment.

Blaxites hit in a different but just as real way. Don’t get me started on the medical field and their requirements for medication. I’ve had my share of constantly having to change medication multiple times because of insurance authorization, just to get what I need. I’ve even had to forfeit medication because companies were doing too much. Our health is just numbers and dollar signs instead of just helping. So the idea that your social media could determine your care does not even feel far off, which is the scary part.

A Model Employee really did piss me off. The job market in this day and age is so hard to get into. People are trying to meet or surpass expectations that barely pay a livable wage. And when we do everything in our power to get more money or move differently, then it’s a crime or a problem. Being tracked through wearable devices just adds another layer of pressure, like you are never off, never trusted, always being measured.

Then Frames kind of brings it all together. You have this all-knowing system that is supposed to understand everything, and it still fails to understand a person. That says a lot. You can collect all the data you want, but you still miss context, intention, and humanity.

Across both the reading and the films, the biggest thing I kept coming back to is this: all these measures put in place to help eventually harm. They start with good intentions or at least good marketing, but they end up creating systems where people feel watched, controlled, and misunderstood. And once that becomes normal, it is hard to question it, because it is everywhere.

So for me, this is not just about AI or surveillance as separate issues. It is about what happens when we replace trust with constant monitoring. And what that does to how people learn, work, and live.

student blogs

Until the end of time!

The screening surveillance videos show the literal reason why I don’t have a Ring doorbell or cameras inside the house.

I really liked the fact that Frames was a silent video; I think it gives a sense of disconnection between the humans. Even when receiving a $5k tip, the excitement is contained. As if controlled by the system. Artistically speaking, I think it’s a very creative choice. Starting, it just looked like what I think government cameras show, but shortly I started questioning who was actually the beneficiary of all the specific data and demographics. I imagine this would be an invention (or decision) of capitalism for capitalism. The companies maximize their profits as civilians lose control, privacy, and physical connection.

Based on the introductory text, this is a machine (AI) that “fails to understand the actions of a civilian,” but to me, the machine, at least this one in particular, doesn’t have to understand the data it collects and assigns to the people walking by, that’s the responsibility of a human in power or another machine that specific companies use to tailor their marketing plans. I think this could be a system implemented in the future to control and sell to the population; it would evolve until there’s just one person in with all the data and the world’s power (or the country, but you know what I mean).

“AI‑generated contradictions for environmental democracy” was a little hard for me to fully follow along because of the vocabulary, but what I think this text confirms is that not only are we killing the environment with our technological advances, but it is also illegal by the same rules we created for ourselves. Ironic and tragic. True.

Just today, I was talking to a different professor about Kean’s broad acceptance of AI usage, despite it holding a proud chest for its sustainability practices. How does replacing disposable to-go trays in the cafeteria with reusable plastic ones compare to most (since this class proves not all) of the student body uses AI every day for their assignments? Hell, even in classes where the topic is not AI or computer science or anything, the use of generative AI is expected. Not necessarily by the professor, even though some care little about whether an assignment is AI-generated or not, but by the students. “It’s okay, will put it on Chat, and it will give us the abstract.” No matter how much I tried for us to actually write it, the majority of the group chose AI slop.

The fact that people don’t even want to try anymore by themselves before using AI is tragic, but it’s even more tragic that the system that sustains our education doesn’t care for it either. Our problems are local, national, and global.

Maybe Nick Cave was right, the apocalypse is near.

student blogs

Writing (With)out AI

I’m currently in the thick of it with my students, somewhere between outlines, introductions, and the slow unraveling that happens when research papers become real. Eighty students. Eighty voices. Or at least, that’s the hope. Because this week, one of my students asked me, completely serious, “Can I use AI to find my sources?” I had to pause. Not because I didn’t have an answer, but because I had too many.

I chuckled. Out loud, just a little. But internally, I laughed harder than I should have, because just the day before, I had sat at my desk going through a student’s research resources, clicking link after link that led nowhere. Articles that sounded academic but didn’t exist. Authors that felt real but weren’t. It wasn’t even good AI use. It was just… empty. Fabricated. Efficient, maybe, but hollow.

And that’s when the question from the video stayed with me: What do we lose by making something efficient?

Because in that moment, it wasn’t just about fake sources. It was about recognition. Do I stop recognizing when a student is not using AI? Do I stop recognizing their voice, the slight awkward phrasing that actually signals effort, the sentence that almost lands but not quite? Or worse, do I stop recognizing them altogether? Their name attached to writing that could belong to anyone.

There’s something unsettling about that.

Dr. Zamora’s emphasis on intentionality really grounded me here. Not a rejection of AI, but a questioning of why we use it. That distinction matters. Because my student’s question wasn’t wrong. It was just incomplete. They weren’t asking how to think with AI, how to use it as a tool to deepen inquiry. They were asking how to bypass the very process that gives research its meaning.

And honestly, I get it. Writing a research paper is hard. Sitting in uncertainty is hard. Not knowing what your argument is yet, struggling through sources, revising a sentence ten times just to make it say what you actually mean—that’s not efficient. But it’s real.

The flowchart in the video was probably the most practical and necessary thing I’ve seen in a while. Not because it tells you what to do, but because it forces you to pause. To ask: What am I using this tool for? I keep thinking about how powerful it would be to bring that into my classroom. Because the truth is, my students are already using AI. The issue is not access. It’s awareness. They don’t know what they’re doing with it, or what it’s doing to their thinking.

And maybe that’s where I am right now as a teacher too.

I’m trying to hold space for both realities. The reality that AI is here, and the reality that writing still matters. That voice still matters. That the messy, inefficient process of figuring something out is not something to shortcut past, but something to move through.

Because when I think about those 80 papers I’m about to read, I don’t just want polished sentences. I want to hear them. I want to recognize who is writing.

And maybe that’s the real question I’m sitting with this week:

If AI can make writing easier, faster, cleaner—what do we lose if we stop listening for the human inside it?

student blogs

What are my students learning from A.I?

Listening to the Harvard EdCast conversation with Ying Xu felt a little like someone describing my classroom from the outside. Not the preschool part, obviously, but the bigger reality she names: AI is already part of how young people interact with the world. Whether it is asking SIRI a question, doomscrolling through the continuous YouTube recommendations, or opening ChatGPT/ CoPilot/ Gemini to “just check something,” students are already practicing relationships with AI. School did not start that relationship. We just walked in after it already began.

One thing Xu emphasizes is that learning is deeply social. Children develop language, understanding, and thinking through interactions with other people. Parents, teachers, peers. That point really stuck with me because as a teacher I see the difference immediately when students talk things through with another person. When they explain an idea out loud, challenge a classmate, or ask a follow-up question, the learning becomes visible. AI can simulate parts of that process. It can ask questions and offer hints. Xu even notes that some studies show children comprehend stories better when AI pauses to ask questions during reading.

But she also makes something clear that feels important for educators to hold onto. AI can support learning, but it does not replace the depth of human conversation. In her studies, children still talked more, asked more questions, and drove conversations further when speaking with a person instead of AI. That lines up with what I see with my own students. AI might get them started, but real understanding usually shows up when they have to defend an idea to someone else in the room.

Another part of the conversation that felt very familiar was the discussion about trust. Xu explains that children, like adults, often judge information based on whether a source has been correct before. If AI gave them a good answer once, they tend to trust it again. The problem is that generative AI blends information together in a way that hides where it came from. Unlike a Google search, there are no visible sources. It just presents a confident answer.

From a classroom perspective, that confidence is the real trick. Students see a clean paragraph and assume the thinking behind it must be just as solid. I have watched students bring in AI-generated essays, research questions, or thesis statements that sound polished but fall apart the moment you ask a follow-up question. The issue is not that they are trying to cheat every time. Sometimes they genuinely believe the tool “knows.”

Xu calls the skill needed to navigate this AI literacy, and that idea connects directly to conversations teachers are already having. Students need to know how these tools work, but they also need to know their limits. AI can remix information. It cannot understand context, intent, or truth the way a person can.

What I appreciated most about Xu’s perspective is that she does not frame AI as something schools should simply fear or ban. Instead she suggests something more realistic. AI should support learning, not replace human interaction. That distinction matters. Students might brainstorm with AI, check an idea, or explore a topic. But the deeper learning still happens when they wrestle with ideas themselves and discuss them with others.

There is still a bigger picture here; AI blurs boundaries. When something talks like a person, it becomes easy to forget that it is still just a program. Xu argues that helping children maintain that boundary is important. Students should know they are interacting with a tool, not a relationship.

That idea connects strongly to how I think about AI in school. Technology has always come with waves of excitement and panic. We saw it with television, smartphones, and social media. AI feels like the next version of that same cycle. The difference is that this technology interacts with students in ways that feel conversational and intelligent.

Because of that, simply telling students “don’t use it” is not going to work. They already are. The real question for schools is whether we help them understand it.

For me, that means teaching students to slow down and question what they see. Where might this information come from? Does it match what we already know? What might be missing? Those small pauses in thinking matter. Xu mentions research showing that even simple prompts encouraging students to reflect on credibility can help them evaluate information more critically.

In many ways, the goal is not to eliminate AI from learning but to make students more aware of how they are using it. AI can support curiosity, help students explore ideas, and sometimes provide scaffolding when they are stuck. But it cannot replace the messy process of thinking through a problem, discussing it with others, and arriving at an understanding that actually belongs to the student.

The conversation also reminded me of something teachers know well. Children do not develop in isolation. They exist within families, classrooms, and communities. Technology shapes their experiences, but the people around them shape how they interpret those experiences.

So the real challenge is not raising a generation that can simply use AI. It is raising a generation that can question it, understand it, and keep their human connections at the center of learning. AI might be everywhere now, but the most meaningful learning still happens when students talk, argue, laugh, and think together in a room.

student blogs

Our best and worst attribute

Well, chapter seven was a read.

This time, I can thank Aiden for saying that “no generational narrative is universal” (though that was probably said by someone more knowledgeable before); it felt as if all generations were sitting down at a table, and Aiden opened up the library.

All the talk on Baby Boomers made me think of the fact that we’ve been governed by them for so many decades with no sign of a change. Aiden’s read makes mention of Baby Boomers’ traits that explain why we are in a toxic 4-year-long (hopefully, not longer) relationship with a narcissistic prick. The privileged Boomers that have been governed did indeed “deep investments in the promises of progress and prosperity of modernity,” and it rewarded them “with opportunities to achieve, accumulate, and succeed.” Green by their power, it is natural that they don’t want to let it go. Obsessed with themselves, they seek glory and fame. As modernity collapses and their promises go to shreds, they taught a culture of “productivity, individualism, and external validation” to achieve the American Dream. To achieve success like theirs.

We wanted it, and we bought it.

The refusal, and lack of ability, to adapt to and at modernity’s speed, leaves us inside a middle floor of a crashing building. Of course, these kids are entitled; of course, they don’t care about authority. Those in authority positions have been making a fool of themselves and of their people for decades, and despite their “best” attempts, modern society suffers like no other. And I know that statistically speaking, we are living in better times than those of the past, but why does it feel so heavy then? Why is it almost impossible to deal with regular life struggles, and we crash out for the dumbest shit? All possible answers lead to a common ground in my head: technology. Global communication is our best and worst achievement. It allowed us to be more connected, but also a medium for segregation, discrimination, and global culture standards.

Reading about Gen A made me sad. I could see my little cousins, nephews, and nieces in almost all the traits Aiden used to define that generation, and most of those traits were directly influenced by technology and modernity’s speed. So, should we put a halt to it? Should we really deny the promise of possibility for current reality, and try to solve our current issues through different means?

I don’t know.

How am I supposed to know? How could anyone know?

The only things I see for certain are that we must learn and master what we currently have, so yes, we should be teaching from early education AI systems; we need a reform of local and global ethics; and we are in desperate need of real connection, not a virtual one, rather mental and physical. We need to be able to define our identity, beliefs, and goals by our own means, and we need to exchange physically, whether that is through the exchange of knowledge, non-verbal cues, feeling the blow of the wind, or poking a friend’s shoulder (not on Facebook -.-).

We cannot keep on depending on technology, and we can not stop existing because of it.

student blogs

AI and the classroom

Reading Empowering Learners for the Age of AI felt like two emotions at once: relief and teacher side-eye. Relief because somebody finally said it plainly. Students are already using AI in real life, and schools cannot keep acting like it is a future problem. Side-eye because whenever a framework says “shared responsibility,” I hear, “This is about to become one more thing teachers are expected to master between grades due at midnight and the copier being possessed.”

What I actually appreciate is that this draft does not treat AI literacy like “knowing what ChatGPT is.” It frames AI literacy as knowledge, skills, and attitudes students need to engage with AI, create with it, manage it, and even understand how it is designed, while also thinking about ethics. That matters because it shifts the conversation away from panic and toward agency. Not “ban everything,” not “let AI raise our children,” but “teach kids how to use it without losing their minds or their integrity.”

And yes, the draft basically confirms what every teacher already knows. Students trust confident-sounding information way too easily. If AI says it with enough vibes, it becomes “true.” The framework points out that young people are learning about AI mostly from social media, not educators, and a lot of them struggle to catch when AI invents facts. That tracks. I have seen students treat an AI paragraph like it is a sacred text, then look confused when I ask, “Okay, where did that come from?” Like I just asked them to name their great-grandparents.

The part that hit for me as an ELA teacher is how the draft weaves ethics into everything instead of making it a cute add-on. It calls out bias as baked into human choices about data and design. In other words, AI is not neutral, it is a mirror with a lot of fingerprints on it. That is actually a helpful way to teach it in English class. We already teach students that texts are shaped by perspective, audience, and omission. AI outputs are just texts with invisible authorship and questionable sourcing. So the core skill is the same old literacy question in a new outfit: Who benefits, who gets harmed, what is missing, and why should I trust this?

Where my teacher tiredness kicks in is implementation. I agree with the framework’s vibe, but I also know what happens next. Schools will say, “We support AI literacy,” and then hand teachers a PDF and a prayer. If we want this to be real, students need guided practice inside actual assignments, and teachers need time, training, and clear policies that match real classroom life. Because right now the integrity conversation is exhausting. Not because kids are evil. Because the system is not designed for a world where a tool can produce a decent essay in eight seconds and students think that means the learning happened.

So my takeaway is simple. AI literacy is not a new elective. It is the new air in the building. If we teach students how to question AI, verify claims, explain their process, and protect their own voice, we get learners who can think clearly while AI tries to think for them. If we do not, we get a generation that can produce polished paragraphs and cannot defend a single idea in them. And I do not have the energy to grade that future.

student blogs

Innovation is Human; Automation is Not

Reading Reid Hoffman’s piece about AI and techno-humanism left me more annoyed than inspired, and I think that reaction matters. The author frames technology, and specifically AI, as something that makes us “more human.” As someone who teaches writing every day and also identifies deeply as a writer, that claim feels overly confident and disconnected from how writing and learning actually work on the ground.

I do not reject AI outright. I use it. As a teacher, it can be genuinely helpful for lesson planning, generating accommodations, or thinking through differentiation for students. But none of that works unless I already know my students. I have to understand their needs, their reading levels, their writing habits, their anxieties, and their strengths first. AI does not replace that knowledge. It depends on it. Too often, people rely on AI without having the foundational understanding required to use it well, and then act surprised when the results feel hollow or off-base.

What really frustrates me about the techno-humanist argument is the way it collapses technology and innovation into the same idea. Innovation makes us human. The ability to struggle, to fail, to revise, to try again, to sit in uncertainty, and to learn through trial and error is deeply human. Technology, on the other hand, often removes that struggle or attempts to smooth it over. In writing, that struggle is not a flaw in the process. It is the process.

I saw this play out very clearly in my classroom when my district mandated the use of an AI-generated comic tool for a narrative assignment. The prompt asked students to create a story about a student posting something inappropriate online, how it goes viral, the consequences they face, and the lesson learned about social media. On paper, it sounded like a solid idea. In reality, the AI could not generate most of the content because it flagged the scenarios as inappropriate, even though that was the entire point of the assignment. Students became frustrated almost immediately. Some of them outright refused to use the tool and said they would rather fail the assignment than fight with the AI. Others tried to work around it and lost days to revisions that went nowhere. A few students chose to draw their comics by hand, which I appreciated, but even then, many could not finish within the four-day time frame.

What struck me most was that this tool, which was supposed to make the process easier, created chaos instead. The technology could not do what it was supposedly designed to do, and students were forced to bend their ideas to fit the limitations of the machine. That is not humanizing. That is constraining. And it directly contradicts the claim that technology inherently expands our creative capacity.

I have also noticed that when students rely too heavily on AI for writing, their voice disappears. Their work becomes more “academic” sounding, but less personal, less intentional, and less theirs. As a teacher, I care far more about students learning how to think through an idea than producing something polished on the first try. Sometimes that means putting the devices away, bringing out pen and paper, and reminding students that it is okay to not know what comes next right away.

If anything, AI has made me appreciate humanness more, not because it enhances it, but because it highlights what cannot be replicated. Writing is not just about getting words on the page. It is about intention, decision-making, and meaning. Those things come from lived experience, frustration, curiosity, and care. AI can assist in certain contexts, but it cannot replace the work of becoming a thinker or a writer.

So yes, AI is here, and it is not going anywhere. But I do not believe it makes us more human. What it does is remind us how human we already are, especially when it fails to do what we can only learn through effort, time, and struggle.