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Enhancing Educational Virtual Reality with Headset-based Eye Tracking

Sponsor: University of Louisiana at Lafayette
Christoph Borst [email protected] (Principal Investigator)
Arun Kulshreshth (Co-Principal Investigator)
Award Number: 1815976


Virtual reality (VR) can bring lab or field-trip-like experiences to students who are unable to visit physical sites because of location, budget, or schedule. Potential advantages of these experiences over traditional teaching tools include increased student engagement and motivation, more direct viewing of size and spatial relationships of modeled objects, and stronger memories of the content. Emerging consumer VR devices are starting to provide sufficient quality and affordability for home and school use, and this will eventually make educational VR experiences broadly available. Future consumer VR headsets are expected to include increased sensing, such as eye tracking cameras to determine where users are looking and strain gauges to detect facial expressions. The sensor data can be analyzed for insight into users’ attention and emotional affect. The project will investigate how such insight into student attention can be used to improve educational VR through the design of personalized educational environments that respond to individual students’ attention. The project will also develop techniques for using sensor data to give teachers enhanced real-time insight into student activities and behavior patterns to help them provide better teacher-guided VR experiences. This will involve development of new approaches for educational VR technology and experiments that generate fundamental knowledge and guidelines for applying such approaches. In addition to the potential long-term benefit of improving education, the project will provide a number of more immediate, direct educational benefits. The team will incorporate the work into courses and undergraduate research experiences on human-computer interaction and VR, as well as outreach activities and summer programs aimed at high school students across Louisiana.

The team will design and assess methods including the following: 1) educational content that responds to student eye gaze for more responsive and engaging presentation; 2) visual effects or indicators, based on detected eye behaviors, to encourage student attention to particular content in a VR environment; and 3) visualizations of student eye gaze that use both raw and processed gaze data to help teachers understand and guide students. To understand the tradeoffs between approaches and to develop guidelines for wider development and use of these techniques, effects will be studied in terms of behavior, subjective experience, and learning. The most promising methods will be applied to a case study of a networked VR interface that allows teachers to monitor and guide students through an immersive educational VR environment. To do this, the team will build on their existing educational VR framework that has previously been deployed at regional high schools and to thousands of students at outreach events. The project is expected to improve the effectiveness of such VR systems and of teachers’ ability to supervise and assist students. Resulting methods and principles will provide a foundation for headset-based eye tracking in educational VR and in other related applications such as simulation-based training and accessibility.

This award reflects NSF’s statutory mission and has been deemed worthy of support through evaluation using the Foundation’s intellectual merit and broader impacts review criteria.


Impact of Building Design Attributes on Occupant Behavior in Response to Active Shooter Incidents in Offices and Schools

Sponsor: University of Southern California
Burcin Becerik-Gerber [email protected] (Principal Investigator)
David Pynadath (Co-Principal Investigator)
Gale Lucas (Co-Principal Investigator)
Erroll Southers (Co-Principal Investigator)
Award Number: 1826443


This project studies how various factors such as building design, size and demographics of the crowd, and individual differences like one’s familiarity with the building impact responses to active shooter incidents. Fundamental questions addressed by the project include: 1) How do building attributes designed to enhance security affect human behavior during active shooter incidents? 2) How do individual factors moderate occupant responses? and 3) How does the setting of the incident or familiarity with building affect occupants’ situational awareness and occupant behavior? The project explores these objectives by conducting human subject experiments using Immersive Virtual Environments (IVEs). This scientific research contribution thus supports NSF’s mission to promote the progress of science and to advance our national welfare. In this case, the benefits will be insights to improve preparedness and response to active shooter events, which will save lives and reduce panic, anger and confusion during these events. The project supports education and promotes diversity through outreach activities aimed at recruiting and retaining under-represented students in research.

The project models the built environment in virtual reality, simulating the behavior of both the adversaries and the crowd. By exposing participants to an active shooter incident using IVE, the researchers can measure their responses in realistic ways that are not possible outside the laboratory environment. Task 1 uses IVEs and agent-based simulations to create representative virtual built environments and realistic active shooter scenarios. There are three critical elements in the development of the IVEs: building attributes that enhance security, setting (school vs. office building), and virtual actors (crowd/adversary). Task 2 examines how various factors (building design attributes, individual factors, participant role, crowd setting, and familiarity with building layout) affect responses to active shooter incidents. Simulation scenarios will include security enhanced buildings versus standard buildings, and school versus office versions. The project outcomes can inform safer building designs and operations and train occupants and security personnel on how to respond to human-enabled catastrophic events, thus saving lives.

This award reflects NSF’s statutory mission and has been deemed worthy of support through evaluation using the Foundation’s intellectual merit and broader impacts review criteria.


SPICE (Supporting Pacific Indigenous Computing Excellence) Data Science Program for Native Hawaiians and Pacific Islanders

Sponsor: University of Texas at Austin
Kelly Gaither [email protected] (Principal Investigator)
Rosalia Gomez (Co-Principal Investigator)
Award Number: 1744526


The University of Texas at Austin’s Texas Advanced Computing Center, Chaminade University of Honolulu (CUH), and the Georgia Institute of Technology will lead this NSF INCLUDES Design and Development Launch Pilot (DDLP) to establish a model for data science preparation of Native Hawaiian and Pacific Islander (NHPI) students at the high school and undergraduate levels. The project is premised on the promise of NHPI communities gaining access to, and the ability to work with, large data sets to tackle emerging problems in the Pacific. Such agency over “big data” sets that are relevant to Pacific issues, and contemporary skills in data science, analytics and visualization have the potential to be transformative for community improvement efforts. The effort has the potential to advance knowledge, instructional pedagogy and practices to improve NHPI high school and undergraduate students performance in and attraction to STEM education and careers.

The project team will work to: 1) Increase interest and proficiency in data science and visualization among NHPI high school and undergraduate students through a summer immersion experience that bridges computation and culture; 2) Build data science capacity at an NHPI serving undergraduate institution (CUH) through creation of a certificate program; and 3) Develop and expand partnerships with other organizations with related goals working with NHPI populations. The month-long summer training for 20 NHPI college students, and five NHPI high school students, takes place at CUH and focuses on data science, visualization, and virtual reality, including working on problem sets that require data science approaches and incorporate geographically, socially- and culturally-relevant research themes.

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