research-article

Empowering authors to diagnose comprehension burden in textbooks

Authors:

Rakesh Agrawal,

Sunandan Chakraborty,

Sreenivas Gollapudi,

Krishnaram KenthapadiAuthors Info & Claims

KDD '12: Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining

Pages 967 - 975

https://doi.org/10.1145/2339530.2339682

Published: 12 August 2012 Publication History

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.

References

[1]

R. Agrawal, S. Chakraborty, S. Gollapudi, A. Kannan, and K. Kenthapadi. Quality of textbooks: An empirical study. In ACM DEV, 2012.

Digital Library

[2]

R. Agrawal, S. Gollapudi, A. Kannan, and K. Kenthapadi. Identifying enrichment candidates in textbooks. In WWW, 2011.

Digital Library

[3]

R. Agrawal, S. Gollapudi, K. Kenthapadi, N. Srivastava, and R. Velu. Enriching textbooks through data mining. In ACM DEV, 2010.

Digital Library

[4]

B. B. Armbruster and T. H. Anderson. Content area textbooks. Technical report, Reading Education Report No. 23, BBN, 1981.

[5]

B. B. Armbruster and T. H. Anderson. Producing considerate expository text: Or easy reading is damned hard writing. Technical report, Reading Education Report No. 46, BBN, 1984.

[6]

B. K. Britton, A. Woodward, and M. R. Binkley. Learning from Textbooks: Theory and Practice. Routledge, 1993.

[7]

B. Bruce, A. Rubin, and K. Starr. Why readability formulas fail. IEEE Transactions on Professional Communication, PC-24, 1981.

[8]

M. Chambliss and R. Calfee. Textbooks for Learning: Nurturing Children's Minds. Wiley-Blackwell, 1998.

[9]

R. Clark, F. Nguyen, and J. Sweller. Efficiency in learning: Evidence-based guidelines to manage cognitive load. Pfeiffer, 2006.

[10]

K. Collins-Thompson and J. P. Callan. A language modeling approach to predicting reading difficulty. In HLT-NAACL, 2004.

[11]

E. K. Dishner. Reading in the Content Areas: Improving Classroom Instruction. Kendall/Hunt, 1992.

[12]

W. DuBay. The principles of readability. Impact Information, 2004.

[13]

C. Fellbaum. WordNet: An electronic lexical database. MIT Press, 1998.

[14]

J. Gillies and J. Quijada. Opportunity to learn: A high impact strategy for improving educational outcomes in developing countries. USAID Educational Quality Improvement Program (EQUIP2), 2008.

[15]

S. R. Goldman. Learning from text: Reflections on the past and suggestions for the future. Discourse Processes, 23, 1997.

[16]

W. Gray and B. Leary. What makes a book readable. University of Chicago Press, 1935.

[17]

B. Grosz and C. Sidner. Attention, intentions, and the structure of discourse. Computational linguistics, 12(3), 1986.

Digital Library

[18]

R. Guillemette. Predicting readability of data processing written materials. ACM SIGMIS Database, 18(4), 1987.

Digital Library

[19]

E. A. Hanushek and L. Woessmann. The role of education quality for economic growth. Policy Research Department Working Paper 4122, World Bank, 2007.

[20]

E. B. Johnsen. Textbooks in the Kaleidoscope: A Critical Survey of Literature and Research on Educational Texts. Scandinavian University Press, 1992.

[21]

J. S. Justeson and S. M. Katz. Technical terminology: Some linguistic properties and an algorithm for indentification in text. Natural Language Engineering, 1(1), 1995.

[22]

R. Kate, X. Luo, S. Patwardhan, M. Franz, R. Florian, R. Mooney, S. Roukos, and C. Welty. Learning to predict readability using diverse linguistic features. In COLING, 2010.

Digital Library

[23]

D. Kieras and C. Dechert. Rules for comprehensible technical prose: A survey of the psycholinguistic literature. Technical Report TR-85/ONR-21, University of Michigan, 1985.

[24]

B. Lively and S. Pressey. A method for measuring the vocabulary burden of textbooks. Educational Administration and Supervision, 9(73), 1923.

[25]

D. Marcu. The theory and practice of discourse parsing and summarization. MIT Press, 2000.

Digital Library

[26]

F. Paas, A. Renkl, and J. Sweller. Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 2003.

[27]

J. M. Pawlowski, K. C. Barker, and T. Okamoto. Quality research for learning, education, and training. Reading & Writing Quarterly, 10(2), 2007.

[28]

J. Plass, R. Moreno, and R. Brünken. Cognitive load theory. Cambridge University Press, 2010.

[29]

L. Polanyi and R. Scha. A syntactic approach to discourse semantics. In COLING, 1984.

Digital Library

[30]

E. Pollock, P. Chandler, and J. Sweller. Assimilating complex information. Learning and Instruction, 12(1), 2002.

[31]

R. Seguin. The elaboration of school textbooks. Technical report, ED-90/WS-24, UNESCO, 1989.

[32]

L. Sherman. Analytics of literature: A manual for the objective study of English prose and poetry. Ginn and Company, 1893.

[33]

S. A. Thompson and W. C. Mann. Rhetorical structure theory: A framework for the analysis of texts. IPRA Papers in Pragmatics, 1(1), 1987.

[34]

K. Toutanova, D. Klein, C. D. Manning, and Y. Singer. Feature-rich part-of-speech tagging with a cyclic dependency network. In NAACL-HLT, 2003.

Digital Library

[35]

H. Tyson-Bernstein. A conspiracy of good intentions: America's textbook fiasco. Technical report, Council for Basic Education, Washington, 1989.

[36]

A. Verspoor and K. B. Wu. Textbooks and educational development. Technical report, World Bank, 1990.

[37]

K. Wang, C. Thrasher, E. Viegas, X. Li, and P. Hsu. An overview of Microsoft Web N-gram corpus and applications. In NAACL-HLT, 2010.

Digital Library

[38]

A. N. Whitehead. The organisation of thought. Proceedings of the Aristotelian Society, 17, 1916--17.

[39]

S. Witte and L. Faigley. Coherence, cohesion, and writing quality. College Composition and Communication, 32(2), 1981.

[40]

A. Woodward, D. L. Elliott, and C. Nagel. Textbooks in School and Society: An Annotated Bibliography and Guide to Research. Garland, 1988.

[41]

World-Bank. Knowledge for Development: World Development Report: 1998/99. Oxford University Press, 1999.

[42]

J. Zhao and M. Kan. Domain-specific iterative readability computation. In ACM JCDL, 2010.

Digital Library

Cited By

Ghosh K(2022)Remediating textbook deficiencies by leveraging community question answersEducation and Information Technologies10.1007/s10639-022-10937-527:7(10065-10105)Online publication date: 11-Apr-2022
https://doi.org/10.1007/s10639-022-10937-5
Ranawat RVenkataraman ASubramanian L(2021)CollectiveTeach: A System To Generate And Sequence Web-Annotated Lesson PlansProceedings of the 4th ACM SIGCAS Conference on Computing and Sustainable Societies10.1145/3460112.3471938(1-13)Online publication date: 28-Jun-2021
https://dl.acm.org/doi/10.1145/3460112.3471938
Karuna PPurohit HJajodia SGanesan RUzuner O(2021)Fake Document Generation for Cyber Deception by Manipulating Text ComprehensibilityIEEE Systems Journal10.1109/JSYST.2020.298017715:1(835-845)Online publication date: Mar-2021
https://doi.org/10.1109/JSYST.2020.2980177
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Index Terms

Empowering authors to diagnose comprehension burden in textbooks
1. Information systems
  1. Information retrieval
  2. Information storage systems

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cover image ACM Conferences

KDD '12: Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining

August 2012

1616 pages

ISBN:9781450314626

DOI:10.1145/2339530

General Chair:
Qiang Yang
Hong Kong University of Science and Technology
,
Program Chairs:
Deepak Agarwal
LinkedIn
,
Jian Pei
Simon Fraser University

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 12 August 2012

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KDD '12: The 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

August 12 - 16, 2012

Beijing, China

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Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Cited By

Ghosh K(2022)Remediating textbook deficiencies by leveraging community question answersEducation and Information Technologies10.1007/s10639-022-10937-527:7(10065-10105)Online publication date: 11-Apr-2022
https://doi.org/10.1007/s10639-022-10937-5
Ranawat RVenkataraman ASubramanian L(2021)CollectiveTeach: A System To Generate And Sequence Web-Annotated Lesson PlansProceedings of the 4th ACM SIGCAS Conference on Computing and Sustainable Societies10.1145/3460112.3471938(1-13)Online publication date: 28-Jun-2021
https://dl.acm.org/doi/10.1145/3460112.3471938
Karuna PPurohit HJajodia SGanesan RUzuner O(2021)Fake Document Generation for Cyber Deception by Manipulating Text ComprehensibilityIEEE Systems Journal10.1109/JSYST.2020.298017715:1(835-845)Online publication date: Mar-2021
https://doi.org/10.1109/JSYST.2020.2980177
Karuna PPurohit HGanesan RJajodia S(2018)Generating Hard to Comprehend Fake Documents for Defensive Cyber DeceptionIEEE Intelligent Systems10.1109/MIS.2018.287727733:5(16-25)Online publication date: 1-Sep-2018
https://dl.acm.org/doi/10.1109/MIS.2018.2877277
Diwan CSrinivasa SRam P(2018)Computing Exposition Coherence Across Learning ResourcesOn the Move to Meaningful Internet Systems. OTM 2018 Conferences10.1007/978-3-030-02671-4_26(423-440)Online publication date: 18-Oct-2018
https://doi.org/10.1007/978-3-030-02671-4_26
Contractor DNegi SPopat KIkbal SPrasad BVedula SKakaraparthy SSengupta BKumar V(2015)Smarter learning content management using the learning content hubIBM Journal of Research and Development10.1147/JRD.2015.245569159:6(3:1-3:9)Online publication date: 1-Nov-2015
https://dl.acm.org/doi/10.1147/JRD.2015.2455691
Chhabra SBedathur S(2014)Towards Generating Text Summaries for Entity ChainsProceedings of the 36th European Conference on IR Research on Advances in Information Retrieval - Volume 841610.5555/2964060.2964162(136-147)Online publication date: 13-Apr-2014
https://dl.acm.org/doi/10.5555/2964060.2964162
Chhabra SChung CBroder AShim KSuel T(2014)Entity-centric summarizationProceedings of the 23rd International Conference on World Wide Web10.1145/2567948.2567959(33-38)Online publication date: 7-Apr-2014
https://dl.acm.org/doi/10.1145/2567948.2567959
Singh GDoke AKumar VBhat SPedanekar N(2014)Assessing the Need of Augmenting Video Lectures with Supporting InformationLearning and Collaboration Technologies. Designing and Developing Novel Learning Experiences10.1007/978-3-319-07482-5_23(238-249)Online publication date: 2014
https://doi.org/10.1007/978-3-319-07482-5_23
Chhabra SBedathur S(2014)Towards Generating Text Summaries for Entity ChainsAdvances in Information Retrieval10.1007/978-3-319-06028-6_12(136-147)Online publication date: 2014
https://doi.org/10.1007/978-3-319-06028-6_12
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