Survival Analysis on Duration Data in Intelligent Tutors

  • Michael Eagle
  • Tiffany Barnes
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8474)


Effects such as student dropout and the non-normal distribution of duration data confound the exploration of tutor efficiency, time-in-tutor vs. tutor performance, in intelligent tutors. We use an accelerated failure time (AFT) model to analyze the effects of using automatically generated hints in Deep Thought, a propositional logic tutor. AFT is a branch of survival analysis, a statistical technique designed for measuring time-to-event data and account for participant attrition. We found that students provided with automatically generated hints were able to complete the tutor in about half the time taken by students who were not provided hints. We compare the results of survival analysis with a standard between-groups mean comparison and show how failing to take student dropout into account could lead to incorrect conclusions. We demonstrate that survival analysis is applicable to duration data collected from intelligent tutors and is particularly useful when a study experiences participant attrition.


ITS EDM Survival Analysis Efficiency Duration Data 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Anderson, J.R., Corbett, A.T., Koedinger, K.R., Pelletier, R.: Cognitive tutors: Lessons learned. The Journal of the Learning Sciences 4(2), 167–207 (1995)CrossRefGoogle Scholar
  2. 2.
    Anderson, J.R., Reiser, B.J.: The lisp tutor. Byte 10(4), 159–175 (1985)Google Scholar
  3. 3.
    Blischke, W.R., Murthy, D.P.: Reliability: Modeling, prediction, and optimization, vol. 767. Wiley (2011)Google Scholar
  4. 4.
    Breen, R., Lindsay, R., Jenkins, A., Smith, P.: The role of information and communication technologies in a university learning environment. Studies in Higher Education 26(1), 95–114 (2001)CrossRefGoogle Scholar
  5. 5.
    Crow, E.L., Shimizu, K.: Lognormal distributions: Theory and applications, vol. 88. CRC Press, LLC (1988)Google Scholar
  6. 6.
    Croy, M.J.: Graphic interface design and deductive proof construction. J. Comput. Math. Sci. Teach. 18, 371–385 (1999)Google Scholar
  7. 7.
    Hosmer, D.W., Lemeshow, S., May, S.: Applied Survival Analysis: Regression Modeling of Time to Event Data, 2nd edn. Wiley-Interscience, New York (2008)CrossRefGoogle Scholar
  8. 8.
    McGuigan, K.A., Ellickson, P.L., Hays, R.D., Bell, R.M.: Adjusting for attrition in school-based samples bias, precision, and cost trade-offs of three methods. Evaluation Review 21(5), 554–567 (1997)CrossRefGoogle Scholar
  9. 9.
    Meeker, W.Q., Escobar, L.A.: Statistical methods for reliability data, vol. 314. Wiley. com (1998)Google Scholar
  10. 10.
    Miller, R.B., Hollist, C.S.: Attrition bias (2007)Google Scholar
  11. 11.
    Scanlon, E., Issroff, K.: Activity theory and higher education: evaluating learning technologies. Journal of Computer Assisted Learning 21(6), 430–439 (2005)CrossRefGoogle Scholar
  12. 12.
    Stamper, J., Eagle, M., Barnes, T., Croy, M.: Experimental evaluation of automatic hint generation for a logic tutor. International Journal of Artificial Intelligence in Education (IJAIED) 22(1), 3–18 (2012)Google Scholar
  13. 13.
    Stamper, J.C., Eagle, M., Barnes, T., Croy, M.: Experimental evaluation of automatic hint generation for a logic tutor. In: Biswas, G., Bull, S., Kay, J., Mitrovic, A. (eds.) AIED 2011. LNCS, vol. 6738, pp. 345–352. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  14. 14.
    Therneau, T.M., Grambsch, P.M.: Modeling Survival Data: Extending the Cox Model. Springer, New York (2000)CrossRefGoogle Scholar
  15. 15.
    Therneau, T.M.: A Package for Survival Analysis in S, R package version 2.37-7 (2014)Google Scholar
  16. 16.
    Weibull, W., et al.: A statistical distribution function of wide applicability. Journal of Applied Mechanics 18(3), 293–297 (1951)zbMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Michael Eagle
    • 1
  • Tiffany Barnes
    • 1
  1. 1.Department of Computer ScienceNorth Carolina State UniversityRaleighUSA

Personalised recommendations