Zhen Bai, Soniya Gadgil-Sharma, Hernisa Kacorri
Post-Doctoral Fellows, HCII, Carnegie Mellon University
- Friday, October 21, 2016 - 1:30pm to 2:30pm
- Newell-Simon Hall 1305 (Michael Mauldin Auditorium)
- Seminar Video
Speaker: Zhen Bai
Title: Fostering Curiosity Through Peer Support in Collaborative Science Learning
Abstract: Curiosity is a key motivational factor in learning. This is, however, often neglected in many classrooms, especially larger and inner-city classrooms, which have instead become very test-oriented. This project focuses on designing learning technologies that foster and maintain curiosity, exploration and self-efficacy in scientific inquiry. In particular, we are interested in understanding social factors among peers that evoke students’ desire for new knowledge, and encourage knowledge seeking through hands-on and collaborative activities. In this talk, I will present the theoretical foundation of curiosity, followed by our on-going work of human-human behavior analysis in small group science learning, and discuss how the theoretical and empirical work lead toward the development of a computational model of curiosity that enables an embodied conversational virtual peer to sense and scaffold curiosity for elementary and middle school students.
Speaker: Soniya Gadgil-Sharma
Title: Insights from Personalized Learning Product Efficacy Pilots in K-12 Education
Abstract: With recent advances in technology, adoption of personalized learning practices has greatly increased in K-12 education across the United States. Personalized learning shows great promise in leveling the playing field for underserved students by offering instruction tailored to their specific competencies (Pane et al., 2015). Yet, schools face significant hurdles in choosing educational technology products well aligned with their curricular goals and objectives from the multitude of options available (Morrison et al., 2014). Existing evidence about educational technology product effectiveness is scarce and school district leaders struggle to access, validate, and apply findings to their unique settings. In this short seminar, I will present some key findings from product efficacy pilot studies of educational technology products conducted at two school districts in the Pittsburgh area. We used a mixed methods approach to evaluate product efficacy on four key dimensions — student learning, student engagement, teacher support, and teacher satisfaction. I will highlight the contrasts between the two pilots, and describe key factors that led to a successful pilot.
Speaker: Hernisa Kacorri
Title: Supporting Orientation and Object Recognition for Blind People
Abstract: In the field of assistive technology, large scale user studies are hindered by the fact that potential participants are ge-ographically sparse and longitudinal studies are often time consuming. In our work, we rely on remote usage data to perform large scale and long duration behavior analysis on users of iMove, a mobile app that supports the ori-entation of blind people. Our analysis provides insights into iMove’s user base and can inform decisions for tailoring the app to diverse user groups, developing future improvements of the software, or guiding the design process of similar assistive tools. Another important factor for independent living of blind people is object identification. Blind people often need to identify objects around them, from packages of food to items of clothing. We explore personal object recognizers, where blind people train a mobile application with a few snapshots of objects of interest and provide custom labels. We adopt transfer learning with a deep learning system for userdefined multi-label k-instance classification. Experiments with blind participants demonstrate the feasibility of our approach, which reaches accuracies over 90% for some participants.
- Speaker's Bio
Zhen Bai: Zhen Bai is a post-doctoral fellow at the ArticuLab. She leads the Sensing Curiosity in Play and Responding (SCIPR) project, which focuses on exploring the design space of playful learning environments that foster curiosity, exploration and self-efficacy for science education. Zhen is passionate to design innovative interfaces that augment our cognitive, emotional and social experiences in a playful and accessible way. Her research interests include augmented reality, tangible interfaces, design for children, developmental psychology, education, and computer-supported collaborative work. She received her Ph.D. in Computer Science from the Graphics & Interaction Group at the University of Cambridge in 2015. Her Ph.D. research focused on designing augmented and tangible interfaces that support symbolic play for young children with and without autism spectrum condition.
Soniya Gadgil-Sharma: Soniya Gadgil earned her doctorate in cognitive psychology with a focus on learning and higher order cognition from University of Pittsburgh in 2014. Her research focuses on applying cognitive science principles to the design, development, implementation, and assessment of educational technology products. In a current role as post-doctoral researcher at the Learning Media Design Center, Soniya supports three school districts in the Pittsburgh area in conducting product efficacy pilots of educational technologies, and implementing rapid cycle feedback loops with developers of said technologies.
Hernisa Kacorri: Hernisa Kacorri is a Postdoctoral Fellow at the Human-Computer Interaction Institute at Carnegie Mellon University. As a member of the Cognitive Assistance Lab she works with Chieko Asakawa, Kris Kitani, and Jeffrey Bigham to help people with visual impairment understand the surrounding world. She recently received her Ph.D. in Computer Science from the Graduate Center CUNY, as a member of the Linguistic and Assistive Technologies Lab at CUNY and RIT, advised by Matt Huenerfauth. Her dissertation focused on developing mathematical models of human facial expressions for synthesizing animations of American Sign Language that are linguistically accurate and easy to understand. As part of the emerging field of human-data interaction, her work lies at the intersection of accessibility, computational linguistics, and applied machine learning. Her research was supported by NSF, CUNY Science Fellowship, and Mina Rees Dissertation Fellowship in the Sciences. During her Ph.D. Hernisa also visited, as a research intern, the Accessibility Research Group at IBM Research – Tokyo (2013) and the Data Science and Technology Group at Lawrence Berkeley National Lab (2015).