STEAM Innovation Grant 2019-2020 Award Recipients
The School of Fine Arts is pleased to announce the recipients of the 2019-2020 STEAM Innovation Grant awards. We received a very strong pool of proposals and are grateful to all who applied.
Jasna Jankovic - Materials Science and Engineering
Christopher Sancomb – Art & Art History
UConn STEAM Tree $40,000
As global climate change rises to the foreground of our current social, political and scientific consciousness, the collective awareness of viable solutions that offer options for accessible renewable energy sources is relegated to experts. Many people have general knowledge of “green” energy options but lack firsthand experience or engagement with these technologies. In addition, several proposed “green” energy options (e.g. solar panels, windmills) are considered eyesores by many. This lack of firsthand experience, coupled with negative aesthetic appeal, can be a barrier to adoption. Our collaborative team seeks to develop an artistically designed portable renewable energy UConn STEAM Tree and then to explore human social reactions to the presence of the tree. Our vision is that this tree would serve as a multidisciplinary research instrument, teaching tool, and most importantly a beautiful, functioning clean energy-harvesting power source that would promote social interactions and understanding though public engagement. We are seeking funding to initiate the project, including the planning, research, and public engagement through focus groups and design charrettes. Then our team will develop, design and construct a prototype of a functioning tree for temporary site-specific installation on the UConn campus.
A second phase is planned utilizing the prototype and research data to seek external funding for an increase in scale and functionality that would enable us to seek partners for public installation and production.
We believe this tree could become an integral part of the landscape at UConn and provide an appealing design that would help raise public awareness of renewable energy and other global solutions through firsthand experience and social interaction, while also serving to illuminate current research, interdisciplinary work, and positive change at UConn.
Robert Astur – Psychological Sciences
Kenneth Thomson – Digital Media & Design
A Virtual Reality Intervention for Decreasing Vaping in College $20,000
Undergraduates
College students have the highest prevalence rate of electronic cigarette use, commonly called “vaping,” of any other group, and this rate is rising. Aside from cancers and other health risks that accompany nicotine use, there is growing literature indicating that vaping in young adults leads to an increase in future use of nicotine, marijuana, and alcohol. Moreover, there is evidence that vaping during adolescence modifies the brain to create aberrant reward processing and an increased vulnerability to addiction and psychiatric problems.
Previously, we published a tobacco smoking cessation intervention in which participants searched for and crushed virtual cigarettes in a virtual reality (VR) world (Girard et al., 2009). Compared to the control group, the crushing-cigarettes group displayed significant reductions in nicotine addiction and significantly higher abstinence rates from real-life cigarettes. In the current project, we will dovetail the unique strengths of UConn’s Digital Arts and Design department in VR and graphic design with the experimental and research expertise of UConn’s Psychological Sciences department to create a similar intervention.
The goal of this project is to use a novel VR behavioral intervention in UConn undergraduates with problematic e-cigarette use to reduce real-life e-cigarette use and decrease cravings for nicotine. Accordingly, we will implement a customized 4-week VR intervention in which 80 undergraduates with problematic vaping will seek and crush virtual electronic cigarettes within a VR environment. Their change in real-life vaping and cravings will be compared to 80 undergraduates in a control group.
This intervention will produce clear health benefits and will create excellent pilot data for larger grants to the National Institute on Drug Abuse (NIDA) and other NIH institutes. Additionally, success in this project will kindle UConn opportunities to create marketable VR software that can be disseminated to various health care and clinical providers.
Daniel Goldberg – Music
Insoo Kim – Medicine and Biomedical Engineering
Synchronizing Movement and Sound: A Wearable Sensor System to Track Coordination between Dance and Music $20,000
During a dance performance, dancers and musicians synchronize their movements with a remarkable level of precision. We propose to develop and apply a system that uses pressure sensors inside dancers’ shoes and motion sensors on dancers’ bodies to record data about how dancers move in time with music. Our analysis of these data will contribute to understanding of the nature of human synchronization and of the cognitive and neural mechanisms that control timing and coordination in creative temporal performance. Recently researchers have employed
video motion capture systems to collect data about dance movements. Unlike motion capture, our system of wearable sensors will be portable and minimally disruptive, facilitating the study of dance in realistic performance contexts instead of in a lab. We will use the sensor system to record movement and audio data from dancers and musicians in Bulgaria, and these data will allow us to analyze the periodicity, phasing, and variability of dance movements in coordination with music. Bulgarian folk dance is of special interest in this regard because it includes uneven rhythmic patterns that most models of synchronization developed in the context of Western European music do not fully explain. In addition to the wearable sensor system itself, this project will generate results to support an application for NSF funding, two articles published in academic journals, and musical recordings that can serve as stimuli for other types of experiments about Bulgarian music. The sensor system also has broad applications beyond our test case of synchronization with Bulgarian dance: the system will facilitate data collection from many other styles of dance, and these data may serve a variety of goals such as creating dance animations or teaching dance.