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Interfaces for discourse summarisation: a human factors analysis

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Published:25 November 2013Publication History

ABSTRACT

Empirical studies assessing the effectiveness of novel document interfaces are becoming more prevalent, however relatively little attention has been paid to how such tools could work with less structured documents featuring multiple contributors. Participants in this study used different interfaces to answer questions requiring the exploration of collaborative discourse. User performance was influenced by an interaction of interface, transcript, and question type. Individual differences also impacted on performance with higher education levels and higher general knowledge scores being associated with better task performance. The results also revealed that unnecessary interface functionality can hinder performance.

References

  1. Allen, B. Cognitive research in information science: Implications for design. Annual Review of Information Science and Technology 26 (1991), 3--37.Google ScholarGoogle Scholar
  2. Butavicius, M. A., & Lee, M. D. An empirical evaluation of four data visualization techniques for displaying short news text similarities. International Journal of Human-Computer Studies, 65 (2007), 931--944. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Butavicius, M. A., Lee. M. D., Pincombe, B. M., Mullen, L. G., Navarro, D. J., Parsons, K. M. & McCormac, A. An assessment of email and spontaneous dialogue visualizations. International Journal of Human-Computer Interaction, 70 (2012), 432--449. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., and Harshman, R. Indexing by latent semantic analysis. Journal of the American Society for Information Science 41(6), 6 (1990), 391--407.Google ScholarGoogle ScholarCross RefCross Ref
  5. Dillon, A. & Watson, C. User analysis in HCI -- the historical lessons from individual differences research. International Journal of Human-Computer Studies, 45 (1996), 619--637. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Kruskal, J. B., and Wish, M. Multidimensional Scaling, Sage University Paper series on Quantitative Application in the Social Sciences, (1978) 07--011. Sage Publications.Google ScholarGoogle Scholar
  7. Lyman, P. & Varian H. R. How much information. Berkeley, CA: University of California at Berkeley, School of Information Management and Systems (2003).Google ScholarGoogle Scholar
  8. Shannon, C. E. A mathematical theory of communication. Bell System Technical Journal, 27, (1948), July and October, 379--423 and 623--656.Google ScholarGoogle ScholarCross RefCross Ref
  9. STAT (Special Tertiary Admissions Test) Candidate information booklet 2011--2012 by the Australian Council for Educational Research, accessed 20th of February 2012.Google ScholarGoogle Scholar
  10. Troy, M., Sprague, D. W., Wu, F., So, W. Y., Munzner, T., Spatialization Design: Comparing Points and Landscapes. IEEE Transactions on Visualizations and Computer Graphics, 13(6) (2007), 1262--1269. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Wechsler, D. Wechsler Adult Intelligence Scale -- Third Edition. San Antonio: The Psychological Cooperation (1997).Google ScholarGoogle Scholar

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  1. Interfaces for discourse summarisation: a human factors analysis

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    • Published in

      cover image ACM Other conferences
      OzCHI '13: Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration
      November 2013
      549 pages
      ISBN:9781450325257
      DOI:10.1145/2541016

      Copyright © 2013 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 25 November 2013

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      OzCHI '13 Paper Acceptance Rate34of70submissions,49%Overall Acceptance Rate362of729submissions,50%

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