XIP Dashboard: Visual Analytics from Automated Rhetorical Parsing of Scientific Metadiscourse

A key competency that we seek to build in learners is a critical mind, i.e. ability to engage with the ideas in the literature, and to identify when significant claims are being made in articles. The ability to decode such moves in texts is essential, as is the ability to make such moves in one’s own writing. Computational techniques for extracting them are becoming available, using Natural Language Processing (NLP) tuned to recognize the rhetorical signals that authors use when making a significant scholarly move. After reviewing related NLP work, we introduce the Xerox Incremental Parser (XIP), note previous work to render its output, and then motivate the design of the XIP Dashboard, a set of visual analytics modules built on XIP output, using the LAK/EDM open dataset as a test corpus. We report preliminary user reactions to a paper prototype of such a novel dashboard, describe the visualizations implemented to date, and present user scenarios for learners, educators and researchers. We conclude with a summary of ongoing design refinements, potential platform integrations, and questions that need to be investigated through end-user evaluations.