Price, Joseph A., IIICoalition for Advancing Digital Research and Education (2020)2020-06-032020-06-032020-04-17Price, J. A., III. (2020, April 17). How similar are sources of content for courses? Poster presented at the fourth annual Coalition for Advancing Digital Research and Education (CADRE) Conference, Stillwater, OK.https://hdl.handle.net/20.500.14446/324827For course content selection, to establish a measure of consensus on topics of relevance, and to compare sources of content, a novel quantitative method was developed and applied to a medical school course. Sources included texts, board review books, and a listing of topics currently taught in the course. Data mining of topics from sources developed data as binary encoded lists of what was present (among 350 topics) before two classical similarity measures were used to compute relatedness in pairwise comparisons of 13 sources. Relatedness was not always as expected. Total topics included ranged from highest in the course handouts, to lower in all other sources. This quantitative indication is opposed to reliance on subjective impressions, and can help faculty make better choices on content topics to include in a course and to compare texts.application/pdfIn the Oklahoma State University Library's institutional repository this paper is made available through the open access principles and the terms of agreement/consent between the author(s) and the publisher. The permission policy on the use, reproduction or distribution of the article falls under fair use for educational, scholarship, and research purposes. Contact Digital Resources and Discovery Services at lib-dls@okstate.edu or 405-744-9161 for further information.Conference proceedingsconsensuscompare sources of contentdata miningrelatednesscurriculum