Cognitive Science Alumni

Our Department isn't defined by the physical space we occupy on the campus of UCSD - it is defined, rather, by the remarkable individuals who make up our community. The lifeblood of any community is its people, and this is especially true of a community that relies on ideas and innovations. In recognition of this, the Department of Cognitive Science at UCSD presents our new "Alumnus/Alumna of the Month" feature.

The goal of the Alumnus of the Month program is to celebrate some of our outstanding Alumni, while giving all students - past, present, and future - an opportunity to meet some of our graduates, and to see some of the amazing things that people from our community have accomplished - in the field of Cognitive Science and beyond.

The hope is that it will both put a more 'human' face on Cognitive Science, as well as be a testimony to the wide range of interesting things that one can do with a Cognitive Science background. In addition, of course, it's a means for CogSci alumni to see what other alumni are up to.

Alumnus of the Month: Victor Lee, 2001

Victor Lee

Victor R. Lee received his B.S. in Cognitive Science with a specialization in Human-Computer Interaction in 2001 along with a B.A. in Mathematics/Applied Science. While an undergraduate, he spent one summer teaching elementary students for SummerBridge San Diego and one summer interning at Microsoft. In 2008, he completed a doctorate in Learning Sciences at Northwestern University. Since then, he has worked as an Assistant Professor of Instructional Technology and Learning Sciences at Utah State University. He recently received a prestigious NSF CAREER award, the foundation's "most prestigious award" for early career scholars. Victor's research interests include: exploring the use of physical activity data technologies for use in mathematics and science education, studying student knowledge as elicited in interviews and small group interactions, and understanding how external representations are used in science teaching and learning. He currently serves as Chair of the American Educational Research Association’s Special Interest Group for Advanced Technologies for Learning.

An Interview with Victor Lee

by Tristan Davenport

You're a professor of learning sciences - a discipline that may be unfamiliar to most people. Can you tell us about it?

Learning Sciences is an interdisciplinary field of scholarship that centralizes learning as the object of study and considers what sorts of environments or conditions can support learning. It has an interventionist character in that many people in Learning Sciences do not simply want to understand learning -- rather they want to create or change environments or systems to better foster it. New media and technologies are often seen as key levers to use for improvement. So the kinds of things you might see someone from Learning Sciences do could include any of the following: conducting an experiment to determine how perceived virtual social presence in an online world or the use of physical manipulatives vs simulated virtual ones influences understanding of newly-learned content; collecting video records of learning as it takes place at school, in museums, or at home and analyzing discourse and interactions to localize how learning is involving multiple individuals, artifacts, and cultural practices; designing a new curriculum and activities organized around a project that incorporate cutting-edge simulation tools, data representation technologies, or distributed networks of learners and analyzing the implementation of that curriculum to figure out what features of the design matched the intent, where and how improvements can be made, and whether our current understanding and prescriptions for learning environments make sense.

Stated simply, I'd say Learning Sciences involves (although not exclusively) people who have thought very carefully about the most recent research on cognition, design, and culture, and they want to really dedicate their energies to understanding and improving the phenomenon of learning. It typically finds its home in colleges of education, but distinguishes itself from some of the fields that are typically housed in such colleges. It started right around the beginning of the 90's, and twenty years later, the field is going strong and certainly growing. We've got conferences, a professional society, journals, and formal departments of Learning Sciences now.

Can you tell us about your own research?

Sure. I have a number of projects going on right now, but one that is getting a lot of my attention lately involves understanding the potential of a class of technologies that athletes typically use to track their activities and seeing how those can be repurposed and integrated into schools as a way for students to collect large amounts of personally relevant data. So for example, if you are familiar with heart rate monitors or accelerometers or bike computers - I try to design learning activities and environments that can use the data those devices produce and explore issues of learning  when students are given these technologies and can begin to pose questions about themselves and the data they collect about themselves. I have been thinking a lot about how this could be a vehicle for helping students to engage in data analysis in a way comparable to what scientists actually do - detecting patterns, considering what to do with outliers, characterizing trends, and the like. And that is not something that happens a lot in traditional schooling but, to me, represents a more powerful kind of learning and a set of skills that will be very useful for these kids as they get older. Right now, my team is interviewing students and giving them a variety of reasoning tasks involving data taken from physical activities to see what does and does not make intuitive sense and what sort of knowledge kids bring to bear when reasoning about data -- specifically, data that is tied to activities that they might already know a lot about. We have been working with elementary school teachers and implementing new instructional units with these technologies and then assessing what students know by throwing some tricky problems at them and seeing how they reason through them while a video recorder is running. We are thinking a lot about student cognition, embodiment and how it influences understanding, data representation, and how we can design instruction that can harness these technologies. The National Science Foundation has kindly agreed to support this research. (However, any findings or claims are mine alone and do not reflect those of the foundation.)

Other projects involve understanding how kids make sense of representations, understanding how educators use or embed representations into instruction or learning materials, studying in really fine detail the interactions that take place when researchers interview students about content they are learning, and how and why schools will or will not use innovative new learning technologies. Representations are something that fascinated me ever since I took COGS 10 as an undergrad with Ed Hutchins and has lingered in my research.

How did your cognitive science degree help you on the job market?

I graduated from UCSD back in 2001 which was a tough job market, although not as tough as the current one. I did an HCI specialization, which had just been established at that time. Cognitive Science certainly opened up some terrific internship and summer opportunities because it gave me a good breadth of knowledge to share and helped me communicate some of the complexities of how people and sociotechnical systems think and behave, and those things all added to my qualifications when I went to the job market. As someone who had strong leanings toward learning and education, it certainly helped me to know a range of relevant issues when I worked in the education sector. When I made the decision to go to graduate school, the cognitive science degree was a tremendous asset. Other universities definitely know the quality of training and the quality of student that comes out of UCSD's Cognitive Science Department. With that said, it was really striking to see how differently cognition was understood or approached at different institutions, and I think that I came in as a graduate student having an extra boost from having wrestled with certain issues already as an undergrad in with training in Cognitive Science from UCSD. I also really came to appreciate why it is that you are strongly discouraged from getting a PhD at the same place where you completed a Bachelors.

When I was finishing graduate school, the undergraduate degree in Cognitive Science still helped a lot too. I felt that the range of things I could talk about and think critically about was really solid. Even though I didn't do any work in the area, learning a year's worth of neuroscience as an undergraduate had been really helpful. When I interviewed for academic positions, sometimes I would get a question about what I thought about movements in education research to incorporate neuroscience and be more "brain-based". Having learned a decent amount about the brain, I felt I was able to handle those questions really well. And work by folks like Ed Hutchins and Jim Hollan (who were sort my de factor advisors as an undergraduate because of how many of their classes I took and the fact that I hung around their lab senior year) receive a fair amount of play in Learning Sciences. Having learned from them directly, I have been able to really thoughtfully consider and comment on the ideas that they advanced and are still advancing. That really came through when I was on the job market and interviewing with different people.

What was your favorite aspect of the cognitive science program here at UCSD?

UCSD's Cognitive Science program is really cutting edge. It always has been. As an undergraduate, I didn't fully appreciate that whoever was teaching would include papers or books that they had written as required reading in the classes, but I came to realize that was because they were leading the field, and what they were showing us was essentially material that was "hot off the presses". In hindsight, that was really valuable. At the time, however, my favorite thing was the interdisciplinary curriculum. I enjoyed taking a mix of courses that integrated psychology, computation, anthropology, philosophy, and neuroscience. I felt quite well-rounded from that balance. Oh, and you are not asking me this, but I can tell you my least favorite thing was the building. It was a very confusing maze that seemed to change exteriors depending on which side you were facing, It also had really unclear floor labeling and signage. Other students and I would sometimes joke about the irony of Cognitive Science, a field that was so in tune with the mind and focused on designing things to be usable, being housed in that building.

Is there anything you wish you had done differently during your time here as a cognitive science student?

I do, but I only know this now in hindsight. I wish I was more assertive about getting involved in research, I wish I did it sooner, and I wish I did a Senior Thesis. Jim Hollan suggested I do one and was really encouraging, but I was getting a bit of senioritis and politely declined. When I was a junior, I arranged to be an IA for Seana Coulson, in part because I liked the language and cognition class a lot (Gilles Fauconnier taught it when I took it) but also because I thought it could be a way to get acquainted and involved in her research at the time because she was new on the faculty, and her work sounded cool. Of course, I never approached her and asked to be involved, so I just went along my business being an IA. Since I am a researcher now, that obviously colors my opinion about the importance of research experience. But I do think that even had I not gone on to my current career path, it would have been a really great opportunity to get some one-on-one mentoring and to see what it feels like to work on a project team and see how people try to answer hard questions. There is value in that no matter what you eventually do.

Oh, and I never took a class with Marta Kutas and wish I could have done that. The years I was supposed to take the core courses she taught, she was on sabbatical or the course got reassigned to someone else. I sometimes wonder if I am the only UCSD Cognitive Science graduate who had never taken a course with her (or even physically seen Marta Kutas). Maybe she will read this and reach out to me, but even if she did I wouldn't have the foggiest idea for what to say. "So, Marta - Event Related Potentials are pretty cool, huh?" or "Scan any interesting brains lately?"

Do you have any advice for current students in cognitive science?

Try research out. Seriously. UCSD has amazing research opportunities. Follow the topics that you feel passionate about and not what you think is marketable later. That advice might sound hollow given the current job market, but things will get better. Even if the next few years look rocky for those seeking jobs, I consistently see that passion and dedication tend to separate the wheat from the chaff in any profession. Get to know the professors who are interesting to you. Go to their office hours or set up a meeting to talk with them about things you find interesting.

And graduate students, my advice to you is simply to survive. And commisserate with each other. And just accept that no one in your family will ever understand what you are doing in graduate school nor why you are doing it. Oh, and if you find love while you are in graduate school, it's probably for real because they certainly don't love you for your money. Unless it is with one of the undergraduates whom you TA for, in which case you might get in trouble for that.

Now that you're an academic professional, how do you balance work and life?

I work at Utah State University, a "Research I" university that is located in a very quiet and scenic part of Northern Utah. A lot of the people who come here are drawn to the intellectual environment of the university coupled with the truly amazing outdoor activities and scenery that come with the rocky mountains. If you don't take time off during the week or weekend to go skiing or hiking or biking, it comes off as a little odd to the folks here. I have to admit, I was really drawn to that mentality. I can get caught up in my work, and having the sort of peer pressure to go out and enjoy nature was really appealing. I also have two awesome little girls and an amazing wife, so I try to set up my schedule in such a way that I can spend a lot of time with them every day. When I come home from work, as long as I don't have an urgent deadline, I have a cut off time in the evening when I will stop checking email or doing work. I try to reserve one weekend day a week when I try to avoid even opening my work laptop. I absolutely enjoy what I do, but there are a number of other things that are very important to me so I create time for them. Since so many people come to Utah State seeking intellectual excellence and a good quality of life, I don't feel too pressured to privilege one set of responsibilities over others.

Outside of your own research area, what developments in cognitive science do you find most exciting/interesting?

This is sort of cheating because it does influence my research area, but embodiment has really become more and more interesting to me over the years. There is some level of knowledge and understanding that our bodies provide or facilitate that we have not spent enough time understanding. I left right before Rafael Nunez started, so aside from reading his book (with George Lakoff) and some of Rafael's papers, I have not been able to learn more about embodiment with him.

Fortunately, there is a strong contingent of Learning Scientists who have been pushing along with research on embodiment and its implications for learning, and I get some intellectual satisfaction from talking with those folks or reading their work. We are also at a point in time where advances in robotics are raising some interesting questions about how we think and interact with technology. I certainly like seeing some of the new research that explores the human side of robotics. My recreational reading right now is Sherry Turkle's new book about what technology interaction tells us about our human needs to connect with others. And one area that has also been a cognitive science interest for me has been modeling of knowledge. When I went to graduate school in Learning Sciences at Northwestern, I worked closely with folks who did work that could be considered involving very "in-the-head" cognitivist approaches. Their approach was modeling knowledge as emerging from a complex system of knowledge elements, and they could illustrate why that approach made sense using some fascinating excerpts of qualitative data. That has really influenced me and certainly has kept me interested on newer research that has tackled territory historically covered under the umbrella of "mental models".

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