Professor Carolyn Penstein Rosé gave a talk entitled: Towards Computer-Supported Collaborative Learning in the Workplace Enabled by Language Technologies
Well meaning companies offer training opportunities to their employees, but when push comes to shove, companies are known to push for short term productivity over learning and higher productivity in the long term. The practical goal of the research is to enable learning during work, with a focus on software development teams.
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. Project courses provide an effective test bed to begin our investigations due to similar tensions imposed by the reward structure. Project courses are believed to be valuable experiences for students to engage in reflection on concepts while applying them in practice. However there is a concern that the reward structure encourages students to engage in performance oriented behaviors, such as the most capable student taking on the lion's share of the work while leaving the others behind. These behaviors undercut the opportunity to use the project experience for each student to gain practice and for the students to reflect together on underlying concepts. In our classroom work, we have adapted an industry standard team practice referred to as Mob Programming into a paradigm called Online Mob Programming (OMP) for the purpose of encouraging teams to reflect on concepts and share work in the midst of their project experience. At the core of this work are process mining technologies that enable real time monitoring and just-in-time support for learning during productive work.
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 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, she invokes approaches from computational discourse analysis and text mining, conversational agents, and computer supported collaborative learning. Her research group’s highly interdisciplinary work, published in over 230 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 in 3 of these fields. She serves as Past President and Inaugural Fellow of the International Society of the Learning Sciences, Senior member of IEEE, Founding Chair of the International Alliance to Advance Learning in the Digital Era, Co-Editor-in-Chielf of the International Journal of Computer-Supported Collaborative Learning, and Associate Editor of the IEEE Transactions on Learning Technologies.
Last updated: 11.2.2020