column

Data mining for improving textbooks

Authors:

Rakesh Agrawal,

Sreenivas Gollapudi,

Krishnaram KenthapadiAuthors Info & Claims

ACM SIGKDD Explorations Newsletter, Volume 13, Issue 2

Pages 7 - 19

https://doi.org/10.1145/2207243.2207246

Published: 01 May 2012 Publication History

Abstract

We present our early explorations into developing a data mining based approach for enhancing the quality of textbooks. We describe a diagnostic tool to algorithmically identify deficient sections in textbooks. We also discuss techniques for algorithmically augmenting textbook sections with links to selective content mined from the Web. Our evaluation, employing widely-used textbooks from India, indicates that developing technological approaches to help improve textbooks holds promise.

References

[1]

Improving India's Education System through Information Technology. IBM, 2005.

[2]

S. Abney. Parsing by chunks. Principle-based parsing, 1991.

[3]

A. Adams and J. van der Gaag. First step to literacy: Getting books in the hands of children. The Brookings Institution, January 2011.

[4]

R. Agrawal, S. Gollapudi, A. Kannan, and K. Kenthapadi. Enriching textbooks with images. In CIKM, 2011.

Digital Library

[5]

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

Digital Library

[6]

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

Digital Library

[7]

J. Anderson and J. Pérez-Carballo. The nature of indexing: how humans and machines analyze messages and texts for retrieval. Part II: Machine indexing, and the allocation of human versus machine effort. Information Processing & Management, 37(2), 2001.

Digital Library

[8]

K. Bakewell. Research in indexing: more needed? Indexer, 18(3), 1993.

[9]

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

[10]

M. Charikar. Similarity estimation techniques from rounding algorithms. In STOC, 2002.

Digital Library

[11]

J. Coiro, M. Knobel, C. Lankshear, and D. Leu, editors. Handbook of research on new literacies. Lawrence Erlbaum, 2008.

Digital Library

[12]

E. Coke and E. Rothkopf. Note on a simple algorithm for a computer-produced reading ease score. Journal of Applied Psychology, 54(3), 1970.

[13]

A. Csomai and R. Mihalcea. Linking educational materials to encyclopedic knowledge. In AIED, 2007.

Digital Library

[14]

E. Dale and J. Chall. A formula for predicting readability. Educational research bulletin, 27(1), 1948.

[15]

L. Downes. The laws of disruption: Harnessing the new forces that govern life and business in the digital age. Basic Books, 2009.

[16]

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

[17]

I. Fang. By computer: Flesch's reading ease score and a syllable counter. Behavioral Science, 13(3), 1968.

[18]

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

[19]

K. Gaikwad, G. Paruthi, and W. Thies. Interactive DVDs as a platform for education. In ICTD, 2010.

Digital Library

[20]

B. Ganter, G. Stumme, and R. Wille. Formal concept analysis: Foundations and applications. Springer, 2005.

Digital Library

[21]

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.

[22]

P. Glewwe, M. Kremer, and S. Moulin. Many children left behind? Textbooks and test scores in Kenya. American Economic Journal: Applied Economics, 1(1), 2009.

[23]

S. Gollapudi and R. Panigrahy. Exploiting asymmetry in hierarchical topic extraction. In CIKM, 2006.

Digital Library

[24]

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

[25]

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

[26]

M. Hu, E. Lim, A. Sun, H. Lauw, and B. Vuong. Measuring article quality in Wikipedia: models and evaluation. In CIKM, 2007.

Digital Library

[27]

S. Huston and W. B. Croft. Evaluating verbose query processing techniques. In SIGIR, 2010.

Digital Library

[28]

P. G. Ipeirotis. Analyzing the Amazon mechanical turk marketplace. ACM Crossroads, 17(2), 2010.

Digital Library

[29]

A. Jawa, S. Datta, S. Nanda, V. Garg, V. Varma, S. Chande, and M. K. P. Venkata. SMEO: A platform for smart classrooms with enhanced information access and operations automation. In International Conference on Next Generation Wired/Wireless Advanced Networking, 2010.

Digital Library

[30]

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

[31]

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.

[32]

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.

[33]

B. Lent, R. Agrawal, and R. Srikant. Discovering trends in text databases. In KDD, 1997.

[34]

D. Marcu. Discourse trees are good indicators of importance in text. In I. Mani and M. Maybury, editors, Advances in Automatic Text Summarization. MIT Press, 1999.

Digital Library

[35]

W. McCall and L. Crabbs. Standard test lessons in reading. Columbia University Teachers College Press, 1926.

[36]

P. Menon. Mis-oriented textbooks. Frontline, August 2002.

[37]

J. Moulton. How do teachers use textbooks and other print materials: A review of the literature. The Improving Educational Quality Project, 1994.

[38]

N. Mulvany. Indexing books. University of Chicago Press, 2005.

[39]

S. Panjwani, L. Micallef, K. Fenech, and K. Toyama. Effects of integrating digital visual materials with textbook scans in the classroom. International Journal of Education and Development using Information and Communication Technology, 5(3), 2009.

[40]

C. Papadimitriou and K. Steiglitz. Combinatorial optimization: Algorithms and complexity. Dover, 1998.

Digital Library

[41]

D. Saari. Decisions and elections: Explaining the unexpected. Cambridge University Press, 2001.

[42]

S. Sarawagi. Information extraction. Foundations and Trends in Databases, 1(3):261--377, 2008.

Digital Library

[43]

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

[44]

B. W. Speck, T. R. Johnson, C. P. Dice, and L. B. Heaton. Collaborative writing: An annotated bibliography. Greenwood Press, 1999.

[45]

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

[46]

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

[47]

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

[48]

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

[49]

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

[50]

S. E. Wright and G. Budin. Handbook of Terminology Management. John Benjamins, 2001.

[51]

X. Xue, S. Huston, and W. B. Croft. Improving verbose queries using subset distribution. In CIKM, 2010.

Digital Library

Cited By

Kushwaha R(2023)Big graph based online learning through social networksPrinciples of Big Graph: In-depth Insight10.1016/bs.adcom.2021.10.012(313-328)Online publication date: 2023
https://doi.org/10.1016/bs.adcom.2021.10.012
Nafa FBabour AMelton A(2022)Prerequisite Relations among Knowledge Units: A Case Study of Computer Science DomainComputer Modeling in Engineering & Sciences10.32604/cmes.2022.020084133:3(639-652)Online publication date: 2022
https://doi.org/10.32604/cmes.2022.020084
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: 1-Aug-2022
https://dl.acm.org/doi/10.1007/s10639-022-10937-5
Show More Cited By

Recommendations

Enriching textbooks through data mining
ACM DEV '10: Proceedings of the First ACM Symposium on Computing for Development

Textbooks play an important role in any educational system. Unfortunately, many textbooks produced in developing countries are not written well and they often lack adequate coverage of important concepts. We propose a technological solution to address ...
Feasibility study of PDF based digital textbooks for university students with difficulty to handle print textbooks
i-CREATe '13: Proceedings of the 7th International Convention on Rehabilitation Engineering and Assistive Technology

Digital Textbooks have been developed by using electronic editing format such as Epub and DAISY so far, and have been gradually introduced as alternative textbooks for print textbooks from elementally schools to high schools in Japan. However, almost no ...
Diagramming Encouragement in CS1 Textbooks
ITiCSE '20: Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education

Drawing is an effective learning tool, incorporating engagement, increasing recall, and improving problem-solving skills. However, it is not widely practiced by computer science educators. This poster reports an analysis of 15 commonly used CS1 ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM SIGKDD Explorations Newsletter

ACM SIGKDD Explorations Newsletter Volume 13, Issue 2

December 2011

101 pages

ISSN:1931-0145

EISSN:1931-0153

DOI:10.1145/2207243

Issue’s Table of Contents

Copyright © 2012 Authors.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 May 2012

Published in SIGKDD Volume 13, Issue 2

Check for updates

Qualifiers

Column

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

23
Total Citations
View Citations
505
Total Downloads

Downloads (Last 12 months)8
Downloads (Last 6 weeks)1

Reflects downloads up to 16 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Kushwaha R(2023)Big graph based online learning through social networksPrinciples of Big Graph: In-depth Insight10.1016/bs.adcom.2021.10.012(313-328)Online publication date: 2023
https://doi.org/10.1016/bs.adcom.2021.10.012
Nafa FBabour AMelton A(2022)Prerequisite Relations among Knowledge Units: A Case Study of Computer Science DomainComputer Modeling in Engineering & Sciences10.32604/cmes.2022.020084133:3(639-652)Online publication date: 2022
https://doi.org/10.32604/cmes.2022.020084
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: 1-Aug-2022
https://dl.acm.org/doi/10.1007/s10639-022-10937-5
Das SDas Mandal SBasu A(2020)Mining multiple informational text structure from text dataProcedia Computer Science10.1016/j.procs.2020.03.273167(2211-2220)Online publication date: 2020
https://doi.org/10.1016/j.procs.2020.03.273
Das SDas Mandal SBasu A(2020)Cognitive Complexity Analysis of Learning-Related Texts: A Case Study on School TextbooksMethodologies and Intelligent Systems for Technology Enhanced Learning, 10th International Conference10.1007/978-3-030-52538-5_9(74-84)Online publication date: 28-Jul-2020
https://doi.org/10.1007/978-3-030-52538-5_9
Lu WMa PYu JZhou YWei B(2019)Metro maps for efficient knowledge learning by summarizing massive electronic textbooksInternational Journal on Document Analysis and Recognition10.1007/s10032-019-00319-y22:2(99-111)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1007/s10032-019-00319-y
Singha ANamgay P(2018)Methodologies and Technologies to Retrieve Information From Text SourcesModern Technologies for Big Data Classification and Clustering10.4018/978-1-5225-2805-0.ch004(99-123)Online publication date: 2018
https://doi.org/10.4018/978-1-5225-2805-0.ch004
Tang YHuang WLiu QTung AWang XYang JZhang BLim EWinslett MSanderson MFu ASun JCulpepper SLo EHo JDonato DAgrawal RZheng YCastillo CSun ATseng VLi C(2017)QALinkProceedings of the 2017 ACM on Conference on Information and Knowledge Management10.1145/3132847.3132934(1359-1368)Online publication date: 6-Nov-2017
https://dl.acm.org/doi/10.1145/3132847.3132934
Kristianto GAizawa A(2017)Linking Mathematical Expressions to WikipediaProceedings of the 1st Workshop on Scholarly Web Mining10.1145/3057148.3057156(57-64)Online publication date: 10-Feb-2017
https://dl.acm.org/doi/10.1145/3057148.3057156
Kalyani LSharma VMurthy B(2016)Sentiment analysis in assessing mobile learning adoption in education sectorInternational Journal of Advanced Intelligence Paradigms10.1504/IJAIP.2016.0801928:4(392-399)Online publication date: 1-Jan-2016
https://dl.acm.org/doi/10.1504/IJAIP.2016.080192
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Issue’s Table of Contents