NexP: A Beginner Friendly Toolkit for Designing and Conducting Controlled Experiments

  • Xiaojun MengEmail author
  • Pin Sym Foong
  • Simon Perrault
  • Shengdong Zhao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10515)


In this paper, we introduce NexP (Next Experiment Toolkit), an open-source toolkit for designing and running controlled experiments. Unlike previous toolkits, it is targeted for the unmet needs of the beginners in experimental design, who may not have had prior statistical training, or experience in creating, implementing and executing controlled experiments. To accommodate such users, NexP features a hypothesis development process that scaffolds beginners into bridging the gap between daily language and formal statistical language. In our evaluation, we compared NexP against a state-of-the-art experimental design toolkit. Results showed that novices considered NexP more intuitive and easier to use. Users also reported that NexP helped them to better understand the experimental design process, making it a useful tool for both productivity and education.


NexP Controlled experiment Toolkit Design platform 


  1. 1.
    Ben-Zvi, D., Garfield, J.: The Challenge of Developing Statistical Literacy, Reasoning and Thinking. Springer, Dordrecht (2016). doi: 10.1007/1-4020-2278-6. Accessed 1 Sept 2016
  2. 2.
    Jonassen, David H.: Instructional design models for well-structured and III-structured problem-solving learning outcomes. Educ. Tech. Res. Dev. 45(1), 65–94 (1997). doi: 10.1007/BF02299613 CrossRefGoogle Scholar
  3. 3.
    MacKenzie, I.S.: Human-Computer Interaction an Empirical Research Perspective. Newnes, Boston (2012)Google Scholar
  4. 4.
    Callahan, J., Hopkins, D., Weiser, M. Shneiderman, B.: An empirical comparison of pie vs. linear menus. In: Proceedings of SIGCHI Conference on Human Factors in Computing Systems, pp. 95–100 (1988). doi: 10.1145/57167.57182
  5. 5.
    Lewis, J.R.: IBM computer usability satisfaction questionnaires: psychometric evaluation and instructions for use. Int. J. Hum.-Comput. Interact. 7(1), 57–78 (1995). doi: 10.1080/10447319509526110 CrossRefGoogle Scholar
  6. 6.
    Lazar, J., Feng, J.H., Hochheiser, H.: Research Methods in Human-Computer Interaction. Wiley, Hoboken (2010)Google Scholar
  7. 7.
    Rosson, M.B., Carroll, J.M.: Scaffolded examples for learning object-oriented design. Commun. ACM 39(4), 46–47 (1996). doi: 10.1145/227210.227223 CrossRefGoogle Scholar
  8. 8.
    NexP online access.
  9. 9.
    NexP’s design platform source code., NexP’s running platform source code:
  10. 10.
    Cairns, P., Cox, A.L.: Research Methods for Human-Computer Interaction. Cambridge University Press, New York (2008)CrossRefGoogle Scholar
  11. 11.
    Cobb, P., McClain, K.: Principles of instructional design for supporting the development of students’ statistical reasoning. In: Ben-Zvi, D., Garfield, J. (eds.) The Challenge of Developing Statistical Literacy, Reasoning and Thinking, pp. 375–395. Springer, Dordrecht (2004). doi: 10.1007/1-4020-2278-6_16 CrossRefGoogle Scholar
  12. 12.
    Soukoreff, R.W, MacKenzie, I.S.: Generalized Fitts’ law model builder. In: Conference Companion on Human Factors in Computing Systems - CHI 1995, pp. 113–114 (1995). doi: 10.1145/223355.223456
  13. 13.
    Zhao, S., Meng, X., Foong, P.S., Perrault, S.: A Dummy’s guide to your Next EXperiment: experimental design and analysis made easy. In: Proceedings of 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA 2016), pp. 1016–1019. ACM, New York (2016). doi: 10.1145/2851581.2856675
  14. 14.
    Zhai, S. Kristensson, P.O., Gong, P., Greiner, M., Peng, S.A., Liu, L.M, Dunnigan, A.: Shapewriter on the iPhone - from the laboratory to the real world. In: CHI 2009 Extended Abstracts on Human Factors in Computing Systems, pp. 2667–2670 (2009). doi: 10.1145/1520340.1520380
  15. 15.
    Malik, S.: Undergraduates’ statistics anxiety: a phenomenological study. Qual. Rep. 20(2), 120–133 (2015)Google Scholar
  16. 16.
    Roumen, T., Perrault, S.T, Zhao, S.: NotiRing: a comparative study of notification channels for wearable interactive rings. In: Proceedings of 33rd Annual ACM Conference on Human Factors in Computing Systems, pp. 2497–2500 (2015). doi: 10.1145/2702123.2702350
  17. 17.
    Mackay, W.E, Appert, C., Beaudouin-Lafon, M., et al.: Touchstone: exploratory design of experiments. In: Proceedings of SIGCHI Conference on Human Factors in Computing Systems - CHI 2007, p. 1425 (2007). doi: 10.1145/1240624.1240840
  18. 18.
    Meng, X., Foong, P.S, Perrault, S., Zhao, S.: Approach to designing controlled experiments. In: Buono, P., Lanzilotti, R., Matera, M. (eds.) Proceedings of International Working Conference on Advanced Visual Interfaces (AVI 2016), pp. 358–359. ACM, New York, 5 September 2016. doi: 10.1145/2909132.2926086
  19. 19.
    Li, Y., Hinckley, K., Guan, Z., Landay, J.A.: Experimental analysis of mode switching techniques in pen-based user interfaces. In: CHI 2005, Proceedings of SIGCHI Conference on Human Factors in Computing Systems, pp. 461–470 (2005). doi: 10.1145/1054972.1055036
  20. 20.
    Guiard, Y., Beaudouin-Lafon, M., Du, Y., Appert, C., Fekete, J.D, Chapuis, O.: Shakespeare’s complete works as a benchmark for evaluating multiscale document navigation techniques. In: Proceedings of 2006 AVI Workshop on BEyond Time and Errors Novel Evaluation Methods for Information Visualization - BELIV 2006, p. 1 (2006). doi: 10.1145/1168149.1168165

Copyright information

© IFIP International Federation for Information Processing 2017

Authors and Affiliations

  • Xiaojun Meng
    • 1
    Email author
  • Pin Sym Foong
    • 1
  • Simon Perrault
    • 2
  • Shengdong Zhao
    • 1
  1. 1.NUS-HCI LabNational University of SingaporeSingaporeSingapore
  2. 2.Yale-NUS CollegeSingaporeSingapore

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