Carolyn Penstein Rosť
Associate Professor (Effective July, 2011)
Carnegie Mellon University
Language Technologies Institute
and HCI Institute
Gates-Hillman Center 5415
5000 Forbes Ave.
Pittsburgh, PA 15213-3891
+1 (412) 268-7130 (W)
+1 (412) 268-6298 (F)
Selected Publications: Selected Publications
Full CV: 2013-CV-Rose-External-Web.pdf
My Group: MyGroup.html
Recent Press Coverage: News.html
Outreach: Internship Program in Technology Supported Education
Personal: Stuff about Me
Spinoff Company: LightSIDE Labs
Tutorial at Learning@Scale: Tutorial on What we know about discussion for learning
Upcoming Tutorial: Discourse Analytics
Goals After Tenure: Into the Future
Secretary/Treasurer and elected member of the Board of Directors of The International Society of the Learning Sciences
Associate Editor of the International Journal of Computer Supported Collaborative Learning and the IEEE Transactions on Learning Technologies
Statement of Career Goals
My research program is focused on better understanding the social and pragmatic nature of conversation, and using this understanding to build computational systems that can improve the efficacy of conversation between people, and between people and computers. In order to pursue these goals, I invoke approaches from computational discourse analysis and text mining, conversational agents, and computer supported collaborative learning. I ground my research in the fields of language technologies and human-computer interaction, and I am fortunate to work closely with students and post-docs from the Language Technologies Institute and the Human-Computer Interaction Institute, as well as to direct a lab of my own, called TELEDIA. My groupís highly interdisciplinary work, published in 150 peer reviewed publications, is represented in the top venues in 5 fields: namely, Language Technologies, Learning Sciences, Cognitive Science, Educational Technology, and Human-Computer Interaction, with awards or award nominations in 3 of these fields.
My research towards this end has birthed and substantially contributed to the growth of two thriving inter-related areas of research: namely, Automated Analysis of Collaborative Learning Processes and Dynamic Support for Collaborative Learning, where intelligent conversational agents are used to support collaborative learning in a context sensitive way. The key idea behind all of my work is to draw insights from rich theoretical models from sociolinguistics and discourse analysis, and pair them down to precise operationalizations that capture the most important essence of what is happening for achieving impact. My approach is always to start with investigating how conversation works and formalizing this understanding in models that are precise enough to be reproducible and that demonstrate explanatory power in connection with outcomes that have real world value. The next step is to adapt, extend, and apply machine learning and text mining technologies in ways that leverage that deep understanding in order to build computational models that are capable of automatically applying these constructs to naturally occurring language interactions. Finally, with the technology to automatically monitor naturalistic language communication in place, the final stage is to build interventions that lead to real world benefits.
This approach leads to three aspects included in each project:
In an effort to arrive at generalizable models, I am pursuing this research program in multiple parallel contexts that provide opportunities to investigate how both the manifestation of the conversational constructs as well as their effects on outcomes are nuanced through mediating contextual variables. Thus, I am conducting research on eight currently funded projects from four different funding agencies, including NSF, DARPA, ONR, and ARL, including 1,215K of grants for which I am PI and 5,278K for which I am co-PI. Many of these projects fall within my primary impact area of education, while others are in the areas of Health, Culture, and Emergency Response. Below I highlight the impact my work has had resulting from the three strands of basic research including discourse analysis, text classification, and conversational agent technology. Across the three strands of my research, the broad impact of my work has been demonstrated in three main ways including seminal ideas and findings, tools and resources for other researchers, and change in research, teaching and assessment practices.