skip to main content
10.1145/2207676.2208413acmconferencesArticle/Chapter ViewAbstractPublication PageschiConference Proceedingsconference-collections
research-article

Designing a debugging interaction language for cognitive modelers: an initial case study in natural programming plus

Authors Info & Claims
Published:05 May 2012Publication History

ABSTRACT

In this paper, we investigate how a debugging environment should support a population doing work at the core of HCI research: cognitive modelers. In conducting this investigation, we extended the Natural Programming methodology (a user-centered design method for HCI researchers of programming environments), to add an explicit method for mapping the outcomes of NP's empirical investigations to a language design. This provided us with a concrete way to make the design leap from empirical assessment of users' needs to a language. The contributions of our work are therefore: (1) empirical evidence about the content and sequence of cognitive modelers' information needs when debugging, (2) a new, empirically derived, design specification for a debugging interaction language for cognitive modelers, and (3) an initial case study of our "Natural Programming Plus" methodology.

References

  1. Anderson, J., Boyle, C. Corbett, A., and Lewis, M. Cognitive modeling and intelligent tutoring, In Artificial Intelligence and Learning Environments, W. Clancey and E. Soloway, (Eds.). MIT Press (1990), 7--49. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Bates, M. Where should the person stop and the information search interface start? Information Processing and Management, 26:5, (1990), 575--591. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Bogart, C., Burnett, M., Douglass, S., Piorkowski, D., Shinsel, A. Does my model work? Evaluation abstractions of cognitive modelers. Proc. VLHCC, IEEE (2010), 49--56. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Bothell, D. et al., ACT-R Tutorial. Distributed with ACT-R 6.0 version 1.3 r766. http://actr.psy.cmu.edu/actr6/. Retrieved August, 2009.Google ScholarGoogle Scholar
  5. Douglass, S., Mittal, S., Using domain specific languages to improve scale and integration of cognitive models, Behavior Representation in Modeling and Simulation, (2011).Google ScholarGoogle Scholar
  6. Fu, W. and Pirolli, P. SNIF-ACT: A cognitive model of user navigation on the world wide web. HumanComputer Interaction, 22:4 (2007), 355--412 Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Green, T. and Petre, M. Usability Analysis of Visual Programming Environments: A "Cognitive Dimensions" Framework. Journal of Visual Languages and Computing, 7:2 (1996), 131--174.Google ScholarGoogle ScholarCross RefCross Ref
  8. John, B. and Kieras, D. The GOMS family of user interface analysis techniques: comparison and contrast. ACM TOCHI 3:4 (1996), 320--351. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Ko, A., Myers, B. A framework and methodology for studying the causes of software errors in programming systems. J. Vis. Langs. & Computing, 16 (2005), 41--84. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Ko, A., DeLine, R. and Venolia, G. Information needs in collocated software development teams. Proc. ICSE, ACM (2007) 344--353. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Ko A., Myers, B. Finding causes of program output with the Java Whyline. Proc. CHI, ACM (2009), 1569--1578. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Little, G., Miller, R., Chou, V., Bernstein, M., Lau, T. and Cypher, A., Sloppy programming, In No Code Required, Cypher, A., Dontcheva, M., Lau, T. and Nichols, J. (Eds.). Morgan Kaufmann (2010), 289--307.Google ScholarGoogle Scholar
  13. Myers, B., Weitzman, D., Ko, A., Chau, D. Answering why and why not questions in user interfaces. Proc. CHI, ACM (2006), 397--406. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Neumann, C., Metoyer, R. and Burnett, M. End-user strategy programming. J. Visual Languages and Computing, 20:1 (2009), 16--29. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Newell, A. and Card. S. The prospects for psychological science in human-computer interaction. HumanComputer Interaction, 1:3 (1985), 209--242. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Pane, J., Ratanamahatana, C. and Myers, B., Studying the language and structure in non-programmers' solutions to programming problems, Intl. J. HumanComputer Studies, 54:2 (2001) 237--264. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Pane, J., Myers, B., More Natural Programming Languages and Environments, In End User Development, vol. 9 of the Human-Computer Interaction Series, H. Lieberman, F. Paterno, V. Wulf, (Eds.). Springer (2006).Google ScholarGoogle Scholar
  18. Pirolli, P., Card, S. Information foraging in information access environments. Proc CHI, ACM (1995), 51--58. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Segal, J. Some problems of professional end user developers. Proc. VLHCC, IEEE (2007), 111--118. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Tor, K., Ritter, F., Haynes, S. and Cohen, M., CaDaDis: A tool for displaying the behavior of cognitive models and agents. Proc. Conf. on Behavior Representation in Modeling and Simulation, (2004), 192--200.Google ScholarGoogle Scholar
  21. Wong, J. and Hong, J. Making mashups with Marmite: Re-purposing web content through end-user programming. Proc. CHI, ACM (2007), 1435--1444. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Yaremko, R., Harari, H., Harrison, R., Lynn, E. Reference Handbook of Research and Statistical Methods in Psychology for Students and Professionals. Harper and Row (1982), New York.Google ScholarGoogle Scholar

Index Terms

  1. Designing a debugging interaction language for cognitive modelers: an initial case study in natural programming plus

      Recommendations

      Comments

      Login options

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

      Sign in
      • Published in

        cover image ACM Conferences
        CHI '12: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
        May 2012
        3276 pages
        ISBN:9781450310154
        DOI:10.1145/2207676

        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]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 5 May 2012

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

        Acceptance Rates

        Overall Acceptance Rate6,199of26,314submissions,24%
      • Article Metrics

        • Downloads (Last 12 months)5
        • Downloads (Last 6 weeks)1

        Other Metrics

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader