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A computational approach to understanding and predicting the behavior of educators using an online curriculum planning tool

Published: 08 September 2014 Publication History

Abstract

This paper presents a computational approach to understanding and predicting the behavior of Earth Science educators using an online curriculum planning tool incorporating digital library resources. It expands on prior work on understanding educators' adoption and use of digital library resources [2] by introducing a methodology for characterizing user behaviors and understanding the trends and frequent patterns of use that are observable from these behaviors.

References

[1]
P. B. Brandtzæg. Towards a unified media-user typology (mut): A meta-analysis and review of the research literature on media-user typologies. Computers in Human Behavior, vol. 26, no.5, pp. 940--956, 2010
[2]
K. E. Maull, M. G. Saldivar, and T. Sumner. Understanding digital library adoption: a use diffusion approach. In Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries, Ottawa, 2011, pp. 259--268.
[3]
S. Ram and H.-S. Jung. The conceptualization and measurement of product usage. Journal of the Academy of Marketing Science, vol. 18, no. 1, pp. 67--76, 1990.
[4]
C.-F. Shih and A. Venkatesh. Beyond adoption: development and application of a use-diffusion model. Journal of Marketing, vol. 68, no. 1, pp. 59--72, 2004.
[5]
T. Sumner and C. Team. Customizing science instruction with educational digital libraries. In Proc of the 10th annual joint Conf. on Digital libraries ACM, Gold Coast, 2010, pp. 353--356

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Published In

cover image ACM Conferences
JCDL '14: Proceedings of the 14th ACM/IEEE-CS Joint Conference on Digital Libraries
September 2014
498 pages
ISBN:9781479955695

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IEEE Press

Publication History

Published: 08 September 2014

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Author Tags

  1. classification
  2. educational digital libraries
  3. frequent pattern mining
  4. prediction
  5. technology use
  6. use diffusion

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  • Research-article

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JCDL '14
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JCDL '14: 14th ACM/IEEE-CS Joint Conference on Digital Libraries
September 8 - 12, 2014
London, United Kingdom

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Overall Acceptance Rate 415 of 1,482 submissions, 28%

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