“One of the things we don’t want to do with this new technology is make things more ‘effortful’ for the scientist,” she says. “Hopefully, you know, the goal is that increasing the technical tools that they have for data visualization and scientific decision- making will make the job easier. But that’s not always going to be true. You’ll try some things, and sometimes, people will say, ‘Yeah, it’s a fancy new tool, but it just feels harder to get the information in there than how I’m used to doing it.’ So we’re looking at these important questions of what is happening in this multitasking environment.
“When we start introducing augmented reality, we ask whether it makes research more effortful. But the bigger question is: Does it change decision-making and make that decision-making better? So if it’s more effortful but your decisions are better, and you’re doing the science more cleanly, then maybe you do want to put in a little more effort?”
As technology continues to race forward, the strain can be particularly profoundly felt by “experts” in their fields, Braun notes. These are individuals who are accustomed to working a certain way, with certain tools. As the recent research bore out, this gives them advantages over less experienced researchers—at least in a traditional setting.
When new technologies are introduced, however, those advantages are diminished.
“We had a range of expertise for people in this experiment,” Braun says. “We had ‘experts’ all the way down to ‘novices,’ and we tested them in two situations—one of which was in the traditional situation that they were used to and one of which was a slightly modified version that goes more toward being remote, so that data that they would usually be looking at in a microscope, they were now looking at on a computer screen, which would be easier to transition to more remote environments, which is one of our goals. But there is some literature in the cognitive side that says, ‘Well, if you mess with something an expert is very used to, the expert is going to struggle with that new interface.”
In a sense, what the team found was that—at least initially—the introduction of new technology leveled the playing field, temporarily, between experts and novices in the field being studied.
“The expert outperformed everyone by miles in a traditional context—that’s what that person is very used to—but they also really struggled with this new context,” Braun says. “Whereas these newer people performed equally across the traditional and new contexts [but] they struggled overall. So this study reveals that, unlike for novices, experts will likely have to unlearn a lot of old habits when adapting to a new interface— this means we can’t evaluate how good a new interface is based on an expert’s initial performance, we need to take a bigger picture into account.”
The Science of Team Science
Arrington’s work is so respected on campus at Lehigh that she is now also extending her “research into research’ into a longstanding area of interest to the university community: team science.
With the support of $1 million National Science Foundation Predictive Intelligence for Pandemic Preparedness (PIPP) grant, and working in collaboration with Jagota, Arrington, in the fall of 2022, began work on another initiative that could help a team of Lehigh researchers learn to collaborate and communicate more effectively in the context of a broader effort to improve pandemic responsiveness—and specifically, in the context of Indigenous communities, which are typically more isolated than other communities and face a unique set of challenges during pandemics.
The questions Arrington is seeking to answer in this work cut across the most fundamental aspects of team science and could unlock new pathways to help researchers work more effectively both with individuals within their fields and those in other fields.
“One piece of what we are going to do in this space—and this moves beyond NHI—is research specifically looking at ‘the science of team science,’” she says. “For instance: How do a group of interdisciplinary researchers—maybe some who have collaborated before but probably who haven’t— effectively start to share knowledge about their disciplines?”
This initiative involves contributions from fields including psychology, bioengineering, materials science and computer science, among various others, and faculty from Lehigh’s innovative College of Health—13 faculty in all from eight different departments. Their work was to extend 18 months through the planning grant period, during which the team would then work together in hopes of securing an even larger grant.
To begin to better understand how the group worked together either effectively or ineffectively, and the challenges they would face, Arrington and her team began their investigation by recording their working meetings in both audio and video. The idea—similar to her work at NHI—is to capture language, conversations, mannerisms, gestures and anything else that might offer clues as to when the group is working in sync or when roadblocks are being put up. By gathering and decoding this data, Arrington hopes to create a base upon which greater collaboration might be built.
“So the question here is: ‘How do we share knowledge from members of the team with people who are not in our area?’ And one of the things I’m very interested in is whether the scientists, when speaking to their disciplinary team, are speaking differently than to those with whom they don’t typically work together. Do they gesture differently when there is assumed common knowledge about something within their thread, versus when you’ve got the whole group together and you’ve got people who are outside your discipline? Do you change the way you’re gesturing to support their knowledge?”
It’s a baseline study in team cognition, Arrington says. And its implications could spur innovation in team science across the campus. For a university such as Lehigh, which has so long valued interdisciplinary work, and whose size affords it the ability to leverage multiple fields of study within a tight-knit campus setting, this is no small consideration.
“We do hit the sweet spot in size for this sort of interdisciplinary research,” Arrington says. “It gives us the opportunity to have robust research programs with graduate students involved. But we are small enough that when you’re in faculty meetings, when you’re having lunch on or near campus, you’re talking with people from a lot of different disciplines, and I think that’s so valuable for researchers, no matter their field.”
Kate Arrington’s research interests focus on the cognitive control, attention and working memory processes engaged during volitional multitask behavior. She received her Ph.D. in psychology from Michigan State University. David Braun’s research investigates how people perceive and make choices around mental effort. He received his Ph.D. from Lehigh University.
Story by Tim Hyland
Interviews by Kelly Hochbein