5 Findings to Know about Your Gen Z Patrons’ Tech Habits

From social media to information literacy to AI and more!

Posted on March 12, 2025 in Blog Posts

I admit I’m usually skeptical that generational analysis is anything more than the narcissism of small differences. The skinny jeans–baggy jeans divide between millennials and zoomers is real, sure, but significant? Maybe not.

But I’m willing to grant that generational differences do, at times, capture specific patterns of technological use and engagement—or at least serve as a convenient shorthand for describing changing behaviors. My go-to example is a university writing instructor who told me that she has some students who write full-length essays on their phones because they can type faster on their phones than on their computer keyboards. For me, writing an essay will always be “a laptop activity,” to cite a much-discussed tweet, but I’m not surprised that younger generations are extending their phone-first practices to essay writing. 

Below, I have highlighted a few recent studies that shed light on the technology practices and attitudes of Generation Z students (“zoomers”), angled toward how they might be applied in a library context. I touch on social media, misinformation, AI, and tech skepticism. Some of these findings might well be generalizable beyond this cohort and help us rethink how we conceive of user behavior within our current technological environment. 

🐦‍⬛ Nobody’s on Twitter (or probably Bluesky) 

Academics and university staff face an unfortunate problem with social media. Most tend to create professional accounts on platforms such as Twitter/X, Bluesky, and LinkedIn, which allow them to communicate and participate in the discourse via text—a familiar mode for engaging in scholarly and professional discussion.

Unfortunately, most young people don’t use these platforms regularly and get information from platforms that don’t have as many professionals shaping and contributing to the conversation. Despite its inflated role in the media, Pew Research’s 2024 report found that only 17 percent of teens use Twitter, down from 23 percent in 2022. (Note: I covered the 2023 report on LTI.) Instagram, YouTube, and TikTok remain the most popular platforms.

This disjuncture has two separate implications. For one, libraries and other cultural institutions understandably are inclined toward text-dominant platforms such as Twitter and Facebook to conduct student outreach and share their programs and offerings, but these platforms have a much shorter reach than a platform that’s more popular with students, though also harder to design for, like Instagram. (As for the merits of using TikTok, I defer to Beth Carpenter’s excellent piece.)

Secondly, this disjuncture limits attempts to remedy mis/disinformation through professional intervention because the latter is mostly occurring on platforms that are less used for professional reasons. We need to reconsider what information literacy means within the specific context and architecture of the platforms students are actually using. On that point…

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💬 Fact-checking occurs in the comment section 

Information professionals have long taught “lateral reading” as a strategy for evaluating information. In short, students are encouraged to check multiple sources on the same story so they won’t be locked into a single author’s or publication’s bias, interpretation, and narrative. However, lateral reading seems like a vestige of the laptop era of accessing the internet. Indeed, “lateral” seems to derive from the multiple tabs a user might open to flip from article to article to compare the results. This practice is much more cumbersome on a phone. Equally important, a lot of information users encounter on the internet may simply not rise to the threshold where they feel the need to fact-check or interrogate it. Particularly if they’re hearing it from a trusted source or influencer, they might defer to the influencer’s judgment over their own. 

Researchers at Google found that zoomers tend to use the comments as a fact-checking service and read the top comments to see how others have responded. This practice makes sense in the context of the social media apps they are using—for instance, Instagram and TikTok, which have the comments section easily available, just one tap away. Users tend to place a lot of trust that the most liked comment provides the most important corrective or interpretation of the information presented in the video. Truth, in essence, is primarily a crowdsourced phenomenon—not a process of research and discernment. 

I don’t think information professionals should abandon lateral reading as a vetting tool, given the nature of academic research and the skills we want students to develop to that end. However, we do need to think about the information environments students are likely to occupy and how those environments shape their information-seeking behaviors and sense of truth. The most important bias they encounter may not be a specific news site or talking head but their own instinct to trust the most liked comment. 

📈 AI use rates are increasing but are hardly universal 

There’s this funny survey from YouGov that I often think about. Respondents were asked to estimate what percentage of Americans fell into various demographic groups, and YouGov compared the estimates with the actual demographic numbers. Not surprisingly, respondents’ estimates were way off. (For instance, respondents, on average, estimated that 30 percent of Americans are vegetarians; in actuality, it’s closer to 5.) The point is that our perception of prevalence is often out of step with the actual numbers. 

Similarly, from all the chatter about students’ use of generative AI in education, you’d be forgiven for thinking that almost every student is using AI for their homework. While a new Pew Research report found that the share of teens using AI for schoolwork doubled between 2023 and 2024, you may be surprised to learn that amounts to only 26 percent of students. Granted, respondents in this survey were teens aged 13–17, not college students, but these numbers should ask us to question the op-ed assumption that students have ceded their entire educations to AI. 

🧠 Young people want AI education 

In her account of ITHAKA’s Next Wave event earlier this week, Fatima Mohie-Eldin cited a Cengage survey that is worth pausing on. Cengage found that 70 percent of graduates believe that generative AI training should be integrated into coursework. For better or worse, graduates’ valuation of their own degrees is tied to their ability to help them transition into the workforce, and, increasingly, that means training them to use AI.  

While educators might take issue with these assumptions about the value and purpose of a college education, I think this finding should come as mild relief. So much of the concern about AI in higher ed pertains to its supposed role in facilitating cheating. This finding would suggest that there’s another way to approach the issue of AI and students’ motivations for using it, which might be far more sincere or even fear-driven than lazy or malicious. Perhaps this new understanding might offer a better way of thinking about the place of AI in educational instruction. 

🤷 Not everyone’s a tech enthusiast 

This isn’t a vetted finding, but I wanted to end this piece by returning to my opening point about the fallacy of generational analysis. Our cultural understanding of what it means to be a zoomer seems to assume a specific—indeed, totalizing—relationship to technology. But even as some studies show that the majority of Generation Z deems technology “essential” to their lives, we also need to acknowledge that circulating within this cohort is a sense of wariness too—whether that’s career anxiety related to AI, the effect of social media use on psychological integrity or intellectual development (so-called “brain rot”), the desire to separate good uses of technology from bad ones, or simply nostalgia about videos of young people partying before phones became omnipresent.

Too often, we treat technology as something independent from human values and emotions, or we see it, equally problematically, as coextensive with human aspiration. We can’t treat generations as monoliths, and we also can’t treat an individual’s attitudes toward technology as characterizable by a single emotion. The library has always served as a space for honoring human complexity, and an understanding of that complexity has to shine through in our approaches to students’ uses of and feelings toward technology.

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