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Two experiments using learning rate to evaluate an experimenter developed tool for splay trees

Published:09 March 2011Publication History

ABSTRACT

We conducted two experiments evaluating Sketchmate, a tool used to teach the splay tree data structure and its algorithms. Learning and learning rates were compared across two groups, one using Sketchmate and the other using paper-and-pencil on practice problems. Results from Experiment I showed that when students used Sketchmate with minimal feedback, there were no significant differences across learning, time spent learning, or learning rate. Experiment II used a version of Sketchmate that provided richer feedback. Results showed similar learning but Sketchmate took significantly less time. Thus when feedback was added, learning rates were significantly greater relative to the paper-and-pencil condition. Discussion focuses on measuring learning rates when evaluating instructional tools.

References

  1. P. S. Babcock and M. Marks. The falling time cost of college: Evidence from half a century of time use data. Working Paper 15954, National Bureau of Economic Research, April 2010.Google ScholarGoogle ScholarCross RefCross Ref
  2. H. Biermann. Binary search tree visualization. Website, 1998. http://www.cs.nyu.edu/algvis/java. (accessed June 1, 2008).Google ScholarGoogle Scholar
  3. R. Bramlett, G. L. Cates, E. Savina, and B. Lauinger. Assessing effectiveness and efficiency of academic interventions in school psychology journals: 1995--2005. Psychology in the Schools, 47(2):114--125, 2010.Google ScholarGoogle Scholar
  4. D. Campbell and J. Stanley. Experimental and quasi-experimental designs for research. Rand McNally College Pub. Co., 1966.Google ScholarGoogle Scholar
  5. E. Carroll, C. H. Skinner, H. Turner, E. McCallum, and S. Woodland. Evaluating and comparing responsiveness to two interventions designed to enhance math-fact fluency. School Psychology Forum: Research in Practice, 1:28--45, 2006.Google ScholarGoogle Scholar
  6. A. Gogeshvili. Java models. Website, 2002. http://webpages.ull.es/users/jriera/Docencia/AVL/ AVL tree applet.htm. (accessed June 1, 2008).Google ScholarGoogle Scholar
  7. D. Ierardi and T.-W. Li. Splay tree applet. Website, 1996. http://www.ibr.cs.tu-bs.de/courses/ss98/audii/ applets/BST/SplayTree-Example.html.(accessed June 1, 2008).Google ScholarGoogle Scholar
  8. A. Korhonen and L. Malmi. Algorithm simulation with automatic assessment. SIGCSE Bull., 32(3):160--163, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. L. Nist and L. M. Joseph. Effectiveness and efficiency of flashcard drill instructional methods on urban first-graders' word recognition, acquisition, maintenance, and generalization. School Psychology Review, 37(3):294--308, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  10. K. N. Rhymer, C. H. Skinner, S. Jackson, S. McNeill, T. Smith, and B. Jackson. The 1-minute explicit timing intervention: The influence of mathematics problem difficulty. Journal of Instructional Psychology, 29(4):305--311, 2002.Google ScholarGoogle Scholar
  11. C. Sanders, B. Segewick, and K. Wayne. Growing tree. Website, 2002. http://www.cs.princeton.edu/introcs/ GrowingTree/GT.jnlp. (accessed June 1, 2008).Google ScholarGoogle Scholar
  12. C. H. Skinner. Preventing academic skill deficits., pages 61--83. Handbook of child behavior therapy: Ecological considerations in assessment, treatment, and evaluation. Plenum, New York, 1998.Google ScholarGoogle Scholar
  13. C. H. Skinner. Theoretical and applied implications of precisely measuring learning rates. School Psychology Review, 37(3):309--314, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  14. C. H. Skinner. Applied comparative effectiveness researchers must measure learning rates: A commentary on efficiency articles. Psychology in the Schools, 47(2):166--172, 2010.Google ScholarGoogle Scholar
  15. C. H. Skinner, P. J. Belfiore, and T. S. Watson. Assessing the relative effects of interventions in students with mild disabilities: Assessing instructional time. Assessment in Rehabilitation and Exceptionality, 2:207--220, 1995.Google ScholarGoogle Scholar
  16. C. H. Skinner and E. S. Smith. Issues surrounding the use of self-management interventions for increasing academic performance. School Psychology Review, 21(2):202--210, 1992.Google ScholarGoogle ScholarCross RefCross Ref

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  1. Two experiments using learning rate to evaluate an experimenter developed tool for splay trees

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                cover image ACM Conferences
                SIGCSE '11: Proceedings of the 42nd ACM technical symposium on Computer science education
                March 2011
                754 pages
                ISBN:9781450305006
                DOI:10.1145/1953163

                Copyright © 2011 ACM

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                Publication History

                • Published: 9 March 2011

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                SIGCSE '11 Paper Acceptance Rate107of315submissions,34%Overall Acceptance Rate1,595of4,542submissions,35%

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