Towards Careful Practices for Automated Linguistic Analysis of Group Learning


  • Iris K Howley Stanford University
  • Carolyn Penstein Rose Carnegie Mellon University



Discourse analytics, transactivity, systemic functional linguistics


This paper reviews work in progress towards bridging the field of linguistics and its operationalizations of discourse, and that of frameworks for studying collaborative learning that are rooted directly in the learning sciences.  We begin with the vision of a multi-dimensional coding and counting analysis approach that might serve as a boundary object between the variety of methodological approaches to analysis of collaborative learning that exist within the Learning Sciences.  We outline what we have discovered from a combination of hand coding, comparison with alternative analytic approaches including network analytic and qualitative approaches, correlational analyses in connection with learning-relevant extralinguistic variables, and computational modeling.  We explore both the contribution of work to date as well as the many remaining challenges.

Author Biographies

Iris K Howley, Stanford University

Iris Howley's research focuses on answering questions regarding how to leverage affordances of educational technologies to overcome students’ social obstacles to seeking help, with a particular emphasis on those social obstacles encompassed by evaluation apprehension and self-presentation concerns. She enjoys incorporating student dispositions (motivation, self-efficacy, life aspirations, etc) and social influences (identity & positioning) into intelligent tutoring systems. Much of learning today takes place in social environments, and I believe it is important to incorporate these social factors into educational technologies. Her main goal is to help students overcome obstacles to effective participation in both academic discussions and the community at large.

Carolyn Penstein Rose, Carnegie Mellon University

Dr. Carolyn Rosé is an Associate 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.  She serves as President Elect of the International Society of the Learning Sciences and the Executive Board of the International Artificial Intelligence in Education Society.  She serves as Associate Editor of the International Journal of Computer Supported Collaborative Learning and the IEEE Transactions on Learning Technologies.




How to Cite

Howley, I. K., & Rose, C. P. (2016). Towards Careful Practices for Automated Linguistic Analysis of Group Learning. Journal of Learning Analytics, 3(3), 239-262.