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Composing Interface Demonstrations Automatically from Usage Logs

Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 141)

Abstract

The benefits of Enterprise Resource Planning (ERP) systems for managing enterprise-wide processes and resources may be counterbalanced by the burdens placed on their users in learning to operate the system. In this paper, we present an approach to creating system tutorials in which the system itself produces interface demonstrations as dynamic visualizations of previously occurring system-user interactions. This approach is motivated by our observations of ERP users in the workplace in conjunction with theoretical accounts of system-user collaboration. The playback interface culls information from the usage log records of the data model, which was specifically designed to overcome the challenges of identifying and aggregating relevant process-related data. This approach is a less costly, more flexible alternative to pre-recorded tutorials and has far-reaching implications for assisting users in learning to navigate and use any complex or confusing interface.

Keywords

Human-computer collaboration Tutorial systems Enterprise systems ERP Human-computer interaction Usability 

Notes

Acknowledgments

This material is based in part upon work supported by the National Science Foundation under Grant No. 0819333. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

References

  1. 1.
    Hestermann, C.: Key issues for enterprise resource planning. Gartner (2009)Google Scholar
  2. 2.
    Hamerman, P.: ERP applications 2007: innovation rekindles. Forrester Research (2007)Google Scholar
  3. 3.
    Iansiti, M.: Erp end-user business productivity: a field study of sap & microsoft. Technical report, Keystone Strategy (2007)Google Scholar
  4. 4.
    Topi, H., Lucas, W., Babaian, T.: Identifying usability issues with an ERP implementation. In: Proceedings of the International Conference on, Enterprise Information Systems (ICEIS-2005), pp. 128–133 (2005)Google Scholar
  5. 5.
    Cooprider, J., Topi, H., Xu, J., Dias, M., Babaian, T., Lucas, W.: A collaboration model for erp user-system interaction. In: Proceedings of HICCS’2010, pp. 1–9. IEEE Computer Society (2010)Google Scholar
  6. 6.
    Terveen, L.G.: Overview of human-computer collaboration. Knowl.-Based Syst. 8(2–3), 67–81 (1995)CrossRefGoogle Scholar
  7. 7.
    Grosz, B.G.: Beyond mice and menus. Proc. Am. Philos. Soc. 149(4), 529–543 (2005)Google Scholar
  8. 8.
    Shieber, S.: A call for collaborative interfaces. ACM Comput. Surv. 28A (electronic). http://www.acm.org/pubs/citations/journals/surveys/1996-28-4es/a143-shieber/ (1996)
  9. 9.
    Babaian, T., Lucas, W., Xu, J., Topi, H.: Usability through system-user collaboration. In: Winter, R., Zhao, J.L., Aier, S., et al. (eds.) DESRIST 2010. LNCS, vol. 6105, pp. 394–409. Springer, Heidelberg (2010)Google Scholar
  10. 10.
    Leshed, G., Haber, E.M., Matthews, T., Lau, T.: Coscripter: automating & sharing how-to knowledge in the enterprise. In: CHI ’08: Proceeding of the Twenty-Sixth Annual SIGCHI Conference on Human factors in Computing Systems, pp. 1719–1728. ACM, New York (2008)Google Scholar
  11. 11.
    Ivory, M.Y., Hearst, M.A.: The state of the art in automating usability evaluation of user interfaces. ACM Comput. Surv. 33(4), 470–516 (2001)CrossRefGoogle Scholar
  12. 12.
    Lucas, W., Babaian, T.: Implementing design principles for collaborative ERP systems. In: Peffers, K., Rothenberger, M., Kuechler, B., et al. (eds.) DESRIST 2012. LNCS, vol. 7286, pp. 88–107. Springer, Heidelberg (2012)Google Scholar
  13. 13.
    Rozinat, A., van der Aalst, W.M.P.: Conformance checking of processes based on monitoring real behavior. Inf. Syst. 33(1), 64–95 (2008)CrossRefGoogle Scholar
  14. 14.
    Quast, M., Handel, M.J.: Social information systems - the end of shadow applications? In: Cordeiro, J., Maciaszek, L.A., Filipe, J. (eds.) ICEIS 2012. LNBIP, vol. 141, pp. 5–15. Springer, Heidelberg (2012)Google Scholar
  15. 15.
    Plaisant, C., Shneiderman, B.: Show me! guidelines for producing recorded demonstrations. In: Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing, pp. 171–178. IEEE Computer Society (2005)Google Scholar
  16. 16.
    Grossman, T., Fitzmaurice, G.: Toolclips: an investigation of contextual video assistance for functionality understanding. In: Proceedings of the 28th International Conference on Human Factors in Computing Systems, CHI ’10, pp. 1515–1524. ACM (2010)Google Scholar
  17. 17.
    Chakravarthi, Y.A., Lutteroth, C., Weber, G.: Aimhelp: generating help for gui applications automatically. In: Proceedings of the 10th International Conference NZ Chapter of the ACM’s Special Interest Group on Human-Computer Interaction. CHINZ ’09, pp. 21–28. ACM, New York (2009)Google Scholar
  18. 18.
    Caldwell, D.E., White, M.: Cogenthelp: a tool for authoring dynamically generated help for java guis. In: Proceedings of the 15th Annual International Conference on Computer Documentation, SIGDOC ’97, pp. 17–22. ACM, New York (1997)Google Scholar
  19. 19.
    Yeh, T., Chang, T.H., Xie, B., Walsh, G., Watkins, I., Wongsuphasawat, K., Huang, M., Davis, L.S., Bederson, B.B.: Creating contextual help for guis using screenshots. In: Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology, UIST ’11, pp. 145–154. ACM, New York (2011)Google Scholar
  20. 20.
    Ramachandran, A., Young, R.M.: Providing intelligent help across applications in dynamic user and environment contexts. In: Proceedings of the 10th International Conference on Intelligent User Interfaces, IUI ’05, pp. 269–271. ACM, New York (2005)Google Scholar
  21. 21.
    Brusilovsky, P., Cooper, D.W.: Domain, task, and user models for an adaptive hypermedia performance support system. In: IUI ’02: Proceedings of the 7th International Conference on Intelligent User Interfaces, pp. 23–30. ACM Press, New York (2002)Google Scholar
  22. 22.
    Linton, F., Joy, D., Schaefer, H.P., Charron, A.: Owl: a recommender system for organization-wide learning. Educ. Technol. Soc. 3(1), 62–76 (2000)Google Scholar
  23. 23.
    Shen, J., Fitzhenry, E., Dietterich, T.G.: Discovering frequent work procedures from resource connections. In: Proceedings of the 13th International Conference on Intelligent User, Interfaces, pp. 277–285 (2009)Google Scholar
  24. 24.
    van der Aalst, W.M.P., Pesic, M., Song, M.: Beyond process mining: from the past to present and future. In: Pernici, B. (ed.) CAiSE 2010. LNCS, vol. 6051, pp. 38–52. Springer, Heidelberg (2010)Google Scholar
  25. 25.
    Dorn, C., Burkhart, T., Werth, D., Dustdar, S.: Self-adjusting recommendations for people-driven ad-hoc processes. In: Hull, R., Mendling, J., Tai, S. (eds.) BPM 2010. LNCS, vol. 6336, pp. 327–342. Springer, Heidelberg (2010)Google Scholar
  26. 26.
    Greco, G., Guzzo, A., Sacc, D.: Mining and reasoning on workflows. IEEE Trans. Knowl. Data Eng. 17, 519–534 (2005)CrossRefGoogle Scholar
  27. 27.
    van der Aalst, W.M.P.: Process discovery: capturing the invisible. IEEE Comp. Int. Mag. 5(1), 28–41 (2010)CrossRefGoogle Scholar
  28. 28.
    Rich, C., Sidner, C.L., Lesh, N.: Collagen: applying collaborative discourse theory to human-computer interaction. AI Mag. 22(4), 15–25 (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Bentley UniversityWalthamUSA

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