Towards Academically Productive Talk Supported by Conversational Agents

Abstract

In this paper, we investigate the use of conversational agents to scaffold on-line collaborative learning discussions through an approach called academically productive talk. In contrast to past work, which has involved using agents to elevate the conceptual depth of collaborative discussion by leading students in groups through directed lines of reasoning, this approach lets students follow their own lines of reasoning and promotes productive practices such as explaining, stating agreement and disagreement, and reading and revoicing the statements of other students. We contrast two types of academically productive talk support for a discussion about 9th grade biology and show that one type in particular has a positive effect on the overall conversation, while the other is worse than no support. This positive effect carries over onto participation in a full-class discussion the following day. We use a sociolinguistic style analysis to investigate how the two types of support influence the discussion and draw conclusions for redesign. In particular, our findings have implications for how dynamic micro-scripting agents such as those scaffolding academically productive talk can be used in consort with more static macro- and micro- scripting.