Abstract: A method is described comprising receiving a conversational transcript of a conversational interaction among a plurality of participants, wherein each participant contributes a sequence of contributions to the conversational interaction. The method includes projecting contributions of the plurality of participants into a semantic space using a natural language vectorization, wherein the semantic space describes semantic relationships among words of the conversational interaction. The method includes computing interaction process measures using information of the conversational transcript, the conversational interaction, and the natural language vectorization.

Abstract: A method is described comprising receiving a conversational transcript of a conversational interaction among a plurality of participants, wherein each participant contributes a sequence of contributions to the conversational interaction. The method includes projecting contributions of the plurality of participants into a semantic space using a natural language vectorization, wherein the semantic space describes semantic relationships among words of the conversational interaction. The method includes computing interaction process measures using information of the conversational transcript, the conversational interaction, and the natural language vectorization.

Abstract: Techniques are described for disaggregating learning curves by student mastery for refining and accurately evaluating automated tutoring models. A method comprises receiving performance data for users logging whether a correct response was provided for each opportunity to use a particular skill in a tutoring system, determining a plurality of subpopulations from the users by using the performance data to group by number of opportunities needed for the particular skill to reach a mastery threshold, creating disaggregated learning curves for each of the plurality of subpopulations that map performance opportunities to percentages correct, and evaluating the disaggregated learning curves to identify a suitable adaptation for the tutoring system. The suitable adaptation may then be carried out and may include sending a notification of portions of the tutoring system that need attention and/or adjusting parameters of the tutoring system for a projected learning progression of a particular user.