Empowering authors to diagnose comprehension burden in textbooks

Authors:
Rakesh Agrawal;Sunandan Chakraborty;Sreenivas Gollapudi;Anitha Kannan;Krishnaram Kenthapadi
Affiliations:
Microsoft Research, Mountain View, CA, USA;New York University, New York, NY, USA;Microsoft Research, Mountain View, CA, USA;Microsoft Research, Mountain View, CA, USA;Microsoft Research, Mountain View, CA, USA
Venue:
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Year:
2012

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Abstract

Good textbooks are organized in a systematically progressive fashion so that students acquire new knowledge and learn new concepts based on known items of information. We provide a diagnostic tool for quantitatively assessing the comprehension burden that a textbook imposes on the reader due to non-sequential presentation of concepts. We present a formal definition of comprehension burden and propose an algorithmic approach for computing it. We apply the tool to a corpus of high school textbooks from India and empirically examine its effectiveness in helping authors identify sections of textbooks that can benefit from reorganizing the material presented.