October 17 - 21, 2022: iSAT welcomes special guest speaker Dr. Carolyn Rosé, Professor of Language Technologies and Human-Computer Interaction in the School of Computer Science at Carnegie Mellon University
Dr. Carolyn Rosé will be giving a talk to iSAT and the Institute of Cognitive Sciences on Friday, October 21 titled: A Layered Model of Learning during Collaborative Software Development: Programs, Programming, and Programmers
Collaborative software development, whether synchronous or asynchronous, is a creative, integrative process in which something new comes into being through the joint engagement, something new that did not fully exist in the mind of any one person prior to the engagement. Past work in the area of software engineering has explored the symbiosis between the management structure of a software team and the module structure of the resulting software. In this talk, we focus instead on small scale software teams of between 2 and 5 developers, working on smaller-scale efforts of between one hour and 9 months, through more fine grained analysis of collaborative processes and collaborative products. In this more tightly coupled engagement within small groups, we see again a symbiosis between people, processes, and products. This talk bridges between the field of Computer-Supported Collaborative Learning and the study of software teams in the field of Software Engineering by investigating the inner-workings of small scale collaborative software development. Building on over a decade of AI-enabled collaborative learning experiences in the classroom and online, in this talk we report our work in progress beginning with classroom studies in large online software courses with substantial teamwork components.
Dr. Carolyn Rosé is a Professor of Language Technologies and Human-Computer Interaction in the School of Computer Science at Carnegie Mellon University. Her research program focuses on computational modeling of discourse to enable scientific understanding the social and pragmatic nature of conversational interaction of all forms, and using this understanding to build intelligent computational systems for improving collaborative interactions.