Most users don’t care about sources much of the time; they reach for whatever is at hand. Like Google, Wikipedia, friends and family, maybe a chatbot. Librarians care about the source a lot. We want to show why the source matters and provide access to those sources which provide the best, most relevant information. Users care more about the topic though, the information, the surprise, the finding out.
That’s why I was surprised to learn that first-year students at OSU working on their first research paper often skipped selecting a topic entirely (Deltering & Rempel, 2017). Instead, they chose a topic they already knew well. The decision is a strategic one: with their grade on the line and limited time, the risk in choosing the wrong topic is high. Between their perceived capacity and existing cognitive model of the subject, they choose the topic which minimizes research anxiety, but wind up with a topic for which their curiosity is actually lower.
This aligns with findings that 84% of students say getting started is the hardest part of research (PIL, n.d.). The easiest search is the one you already know how to do, but this reduces their motivation to explore new search strategies, thwarting efforts at information literacy instruction.
The challenge then is to create an environment in which users feel safe enough to explore a topic they are curious about but know very little. What is needed is a way to browse a wider range of high interest topics but with low stakes. The topics must be grounded in existing scholarly discourse so students have something to find. For this, OSU used press releases and news stories from sites like ScienceDaily. They also emphasized framing the exercise as exploring a topic over finding sources per se (Deltering & Rempel, 2017).
This helps students get a sense of what the literature might contain before they formulate a query. This is the paradox of search: you need to know what the index contains and how it is structured before you can effectively query it. Like many complex tasks, you learn along the way what you needed to know at the beginning.
There is a parallel in Matthews essay (2017) on how the organizational structure of academic libraries affects their ability to respond to change. The core argument is that libraries miss important opportunities because they are run too much like factories. If staff had more autonomy and fewer silos, they could better adapt and seize these opportunities.
Though it is hard to quantify, the opportunity cost is potentially quite large. The sense is that new tech-enabled modes of collaboration are such powerful multipliers that a nascent, globally distributed, cross-functional team is out there just waiting to invent the iPod or Taurus sedan of library services. (Are they hiring?)
The problem is the design space is simply enormous. In other words, academic libraries have a similar problem as students doing research; we don’t know what we don’t know, we don’t know which processes are repeatable. The best we can do is experimentation. Perhaps the solution here is similar: a way to explore a wider range of topics but with lower stakes, like allowing staff the (company) time to experiment. This way they can take risks, like first-year students, with less anxiety. Both would benefit from better ways to reward this exploratory research.
References
Deitering, A. & Rempel, H. G. (2017, February 27). Sparking curiosity: Librarians’ role in encouraging exploration. In the Library with the Lead Pipe…. https://www.inthelibrarywiththeleadpipe.org/2017/sparking-curiosity/
Mathews, B. (2017). Cultivating complexity: How I stopped driving the innovation train and started planting seeds in the community garden. http://hdl.handle.net/10919/78886
Project Information Literacy (PIL) (n.d.), A National Study About College Students Research Habits [Infographic], Project Information Literacy Research Institute, https://projectinfolit.org/publications/retrospective#infographics
Image Credits
NASA. 1980s Visualization [image].
NASA. GRAPH3D [image].
Koppitch, A., & Schilling, H. W. (2025, July 23). GVIS lab at NASA Glenn research center history. NASA. https://www.nasa.gov/centers-and-facilities/glenn/gvis-history-glenn/
I love the many thoughts and ideas you bring to this, Rob. As humans, we are wired to follow the path of least resistance. This means, unless we are taught otherwise, we are going to grab the first answer we get. This isn’t always the correct answer. It is interesting how similar I have found AI to be as well. For an assignment last semester, I had to use ChatGPT to see what answers it would give me. I already had the correct answers ahead of time. I do not remember the exact question, but when asked, it gave me the wrong answer. I told it so, and it gave me the corrected answer. It did not have sources for this information and was going off of related information it did have. It lacked sources for the information it gave. It also “assumed” I was giving the correct answer when I told it the answer was wrong. I think there is much that needs to be explored in AI, as it has many amazing features, and still has room for growth. All of this to say, it is important for information professionals to teach others that the fastest answer isn’t always the best or correct choice.