In this article, we present an analysis of communication transcripts from computer-mediated teams that illustrates how different kinds of decision support impact collaborative knowledge construction. Our analysis introduces an algorithmic technique called Topic Evolution Analysis (TEvA), which tracks clusters of words in conversation, and illustrates how these clusters change and merge over time. This analysis is combined with measurements of group dynamics to distinguish between teams using different kinds of decision support. Our analysis offers evidence that some kinds of decision support improve the apparent rationality of a team, but at the cost of collaborative knowledge construction. This result is not apparent when simply measuring team decision performance. We use this finding to motivate the utility and importance of the approach when assessing the impact of technology on collaborative knowledge processing.