Abstract: Methods, systems, and computer program products for cognitive content mapping and collating are provided herein. A computer-implemented method includes identifying resources relevant to an existing course; partitioning, based on pre-determined partitioning parameters, (i) the existing course into multiple portions and (ii) the resources into multiple portions; detecting content coverage gaps in the existing course by semantically comparing (i) the multiple portions of the existing course with (ii) the multiple portions of the resources; retrieving, based on the detected content coverage gaps, at least one of the multiple portions of the resources; and generating an updated version of the existing course by incorporating the at least one retrieved portion of the resources into the existing course.

Abstract: Methods, systems, and computer program products for cognitive content mapping and collating are provided herein. A computer-implemented method includes identifying resources relevant to an existing course; partitioning, based on pre-determined partitioning parameters, (i) the existing course into multiple portions and (ii) the resources into multiple portions; detecting content coverage gaps in the existing course by semantically comparing (i) the multiple portions of the existing course with (ii) the multiple portions of the resources; retrieving, based on the detected content coverage gaps, at least one of the multiple portions of the resources; and generating an updated version of the existing course by incorporating the at least one retrieved portion of the resources into the existing course.

Abstract: A method, computer program product and system including inputting defined user attributes and course facets; mining existing course data for course facets; mining existing course data for user rating data; decomposing user rating data in terms of course facets and user attributes. The method, computer program product and system further including performing a course simulation for a new course including mining associations from existing course data for associations between course facets and user attributes and for associations between facets, responsive to inputting an intended target audience and course facets of the new course to be examined, predicting an expected user rating for each course facet to be examined; and when the user rating meets or exceeds predetermined criteria for each defined course facet, outputting the expected user rating and the expected user feedback to a course designer.