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Kate Arrington: Researching the Researchers

In her ‘Lab Lab’ at the heart of campus, Arrington studies colleagues as they pursue their cutting-edge science—and aims to help them do that science better.

Lehigh’s innovative Nano-Human Interface (NHI) initiative is one of the most ambitious and forward-looking projects that the university has ever launched—one that aims to fundamentally change the way that research is pursued, the way that breakthroughs are achieved and the way science is conducted.

Launched in 2016, the initiative has brought together researchers across numerous fields—including materials science, bioengineering, computer science and cognitive science—who share not only a belief in Lehigh’s strong interdisciplinary culture, but also a vision for what they call “the next revolution in the conduct of science.” It’s a lofty vision, for sure—but one that is backed by investigators of impressive backgrounds and unquestionable ambition.

In the years since its formal launch, the team involved with NHI has already notched numerous impressive achievements, and in April of 2022, cemented a $25 million partnership with Ohio State University and the U.S. Army Research Lab (ARL) to develop novel structural materials for high-strength applications. The first installment of funding, worth $3 million, has been authorized by Congress, and work is well underway.

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Image credit: Moonassi

Housed in Lehigh’s new Health, Science & Technology (HST) Building, the labs of NHI—including its cutting-edge Data Visualization Lab—are at any one time buzzing with the kind of activity reflective of the broad scope of the researchers and fields of study involved. A visitor to HST may see materials scientists engaged in microscopy, computer scientists developing new apps and programs in support of their materials science colleagues, and graduate and undergraduate students working across teams and disciplines toward the broader efforts of NHI.

What that same visitor may not see, however, is the work being done somewhat behind the scenes—by a team of visionary Lehigh cognitive psychologists—that may allow those very researchers to take their work to the next level, help them learn how to better utilize new and emerging technologies, and possibly revolutionize the very art of research itself.

Led by Kate Arrington, a professor in the psychology department and Cognitive Science program, the work is in many ways emblematic of the research ethos of Lehigh—a university that boasts a thriving culture of interdisciplinary research and team science. At the same time, Arrington’s research also recognizes that even in a thriving team science setting, there is always room to do better.

Through her “lab within a lab” at HST, Arrington is studying the way NHI researchers work, examining their habits, achievements and challenges—everything down to their eye movements, reaction time, conversations and even hand gestures—to ultimately find ways to create new efficiencies not only in a cutting-edge lab setting such as the Data Visualization Lab, but also in various team science environments across campus.

“One of the things we’re looking at in this work is how an individual human engages in the environment in which they’re working and how you can modify that environment to nudge people in behavioral directions that you would like to support,” Arrington says. “So one of the things we’re doing in this space is wanting to observe the scientist at work— and there are a lot of reasons for wanting to do that, including the fact that it gives us a large data set. We are manipulating environments, we are measuring behaviors, and we have hypotheses about how those behaviors are going to change in the different conditions in the experimental environment based on theories of cognition.”

Post-doctoral fellow David Braun, who has worked with Arrington, adds, “We are thinking about how we can design more optimal interfaces given what we know about how the human mind processes information. Can we make it more intuitive? Can we make things easier for collaboration? For problem-solving? So we want to design experiments that might give us insight into how scientists process information and then use those insights to optimize this lab environment.”

The work is somewhat unique in the world of cognitive psychology and presents a number of challenges both large and small. But, like their colleagues being studied in the NHI “Lab Lab,” Arrington shares a conviction with them that, with time, her team’s investigation and observation into every last nuance of how science is conducted at NHI will bear real dividends—not only for researchers at Lehigh, but elsewhere as well.

“We have the scientists watching the scientists,” Arrington says. “And that is a lot of fun to be able to do.”

We are thinking about how we can design more optimal interfaces given what we know about how the human mind processes information.

Post-doctoral fellow David Braun

“The NHI team is creating a new, exciting and highly visual way of interacting with instruments of scientific discovery,” Stephen P. DeWeerth, dean of the P.C. Rossin College of Engineering and Applied Science, said upon the announcement of the Ohio State/ARL partnership. “They are integrating materials science, data science and social science to extract deeper meaning from the physical world, and the tools they are developing will enable new ways of understanding and addressing research challenges. The continuation of long-term successful collaboration among Lehigh, ARL and Ohio State will amplify the team’s success. It is an inspired effort from a truly inspiring group of researchers.”

Arriving at the Right Time

Arrington was not on campus at Lehigh when NHI originally launched in 2016, as she was serving at the time as a program director of the National Science Foundation’s Perception, Action & and Cognition program.

But upon her return in 2017, she was approached by then-Lehigh College of Arts & Sciences associate dean for research and graduate studies Dominic Packer, a psychologist himself, who told her about the exciting work being done through the nascent NHI. The project, he explained, was about creating greater synergies and stronger efficiencies between human beings and the machines and technologies that are continually—and ever more rapidly—changing the way those humans conduct scientific discovery.

While pairing up a cognitive psychologist with a team of researchers working to build stronger superalloys, for instance, may have seemed counterintuitive, Arrington’s expertise, Packer believed, could play a key role in the project, nonetheless; NHI is led by Martin Harmer, the Alcoa Foundation Professor of Materials Science and Engineering, who is a longtime champion of team science and interdisciplinary exploration.

“Dominic said to me, ‘You should hook up with this team that is just getting this presidential initiative funded, and even though I wasn’t there at the outset, I came in kind of just as it was getting started,” Arrington says. “The idea behind the project was to harness both the artificial intelligence and computer science side of things, but also our understanding of human cognition and intelligence to design a better way of doing science—not only the materials science work that Martin and the folks in materials science were involved in, but also bioengineering work that was being led by Anand Jagota (vice provost for research and professor of bioengineering and chemical and biomolecular engineering).

“And so, my role as the cognitive science team leader is to look at ways in which our theories from cognitive science or methodologies from cognitive science research can be used to inform decisions that are made about how to create a workspace that will work with the sort of cognitive processes and limitations that scientists have, but also how can we enhance the scientific discovery process. So that was sort of the initial entry into the initiative, and since then, my involvement has really gone in a lot of different directions.”

They are integrating materials science, data science and social science to extract deeper meaning from the physical world, and the tools they are developing will enable new ways of understanding and addressing research challenges.

Stephen P. DeWeerth, dean, P.C. Rossin College of Engineering and Applied Science

Arrington’s work as an NHI researcher includes numerous projects that tackle the larger goal—helping researchers do science better—from various different angles. And in many ways, the nature of her work is also reflective of the shifting realities of research for scientists like herself and Harmer, Jagota and the myriad others involved in NHI’s work.

Take, for example, the ways that microscopy is being fundamentally changed by technological advances. Instead of a traditional lab setting—with a scientist sitting over some kind of microscope—the high-end technology on hand at HST allows materials scientists to engage in their work in a much more immersive way involving augmented reality support tools. This opens up tremendously exciting new possibilities, but, as Arrington notes, it also forces scientists to work outside their longstanding comfort zones. And this, of course, presents new challenges— ones that Arrington fundamentally understands based on her work on how the human brain works in different settings.

For years, she has pursued research exploring the cognitive control and attention processes related to multitasking, during which cognitive control on behalf of an individual is necessary to coordinate input of perceptual information, retrieve information from memory and direct behavior to competing tasks. As the level of multitasking in any particular environment becomes more complex, so, too, do the demands on the human brain.

“When I’m doing research with individuals in Chandler– Ullmann, we are doing it on a computer screen in a very small, very sparse room where the tasks are, for example, to first say whether a number is even or odd, and then, next, a letter appears and you have to say whether it’s a consonant or a vowel, and then, I measure down to the millisecond how quickly people are able to move between these tasks. And maybe you’re a 10th of a second slower [than you would be otherwise] if I am asking you to transition between those tasks,” she explains. “But at a space like the NHI Data Visualization Lab, it’s a true multitask environment—just much richer—and those same cognitive processes are at work in a more expansive way. And what we’re looking at is how a scientist is able to work in high-level, multitasking laboratory space.”

Challenges & Opportunities

Working in conjunction with Braun, Arrington is seeking to use what they’ve learned thus far—and have yet to learn—to help researchers work more effectively in a challenging environment such as that found at NHI.

Much of NHI’s work is focused on developing practical and useful augmented intelligence support for scientists, but despite the many benefits the technology provides, it also—on a strictly cognitive level—presents researchers’ brains with yet another level of multitasking. Ideally, Arrington would like to find a way to streamline and optimize technologies and processes in order to decrease the level of effort involved to access data and knowledge. By working with the scientists—and by studying their actions and behaviors while engaged in their immersive research—she believes she and her team can both identify and knock down research “bottlenecks.”

“We have audio-visual capture in the space where they’re working, as well as eye tracking,” she says. “So one of the things we have capabilities for is tracking where someone’s eyes are, and this is key because if you’re looking at a small screen, you can, of course, move very easily among the different elements of the display. But how does that ability to shift your gaze around change when you’re looking at a very large screen? We have the ability to capture these data and maybe identify some ways in which AI could be useful for them.”

At the same time, she acknowledges that efficiencies in the face of new technologies may not always be possible—and that, sometimes, new technologies
are just going to be inherently difficult to learn. In fact, she says, that may not necessarily be a bad thing.

Illustration for Researching the Researchers

Image credit: Moonassi

“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

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