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On the Dynamic Adaptation of Computer Assisted Assessment of Free-Text Answers

  • Diana Pérez-Marín
  • Enrique Alfonseca
  • Pilar Rodríguez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4018)

Abstract

To our knowledge, every free-text Computer Assisted Assessment (CAA) system automatically scores the students and gives feedback to them according to their responses, but, none of them include yet personalization options. The free-text CAA system Atenea [1] had simple adaptation possibilities by keeping static student profiles [2]. In this paper, we present a new adaptive version called Willow. It is based on Atenea and adds the possibility of dynamically choosing the questions to be asked according to their difficulty level, the students’ profile and previous answers. Both Atenea and Willow have been tested with 32 students that manifested their satisfaction after using them. The results stimulate us to continue exploiting the possibilities of incorporating dynamic adaptation to free-text CAA.

Keywords

Natural Language Processing Dynamic Adaptation Automatic Assessment Adaptive Version Apply Psychological Measurement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Alfonseca, E., Pérez, D.: Automatic assessment of short questions with a bleu-inspired algorithm and shallow NLP. In: Vicedo, J.L., Martínez-Barco, P., Muńoz, R., Saiz Noeda, M. (eds.) EsTAL 2004. LNCS (LNAI), vol. 3230, pp. 25–35. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  2. 2.
    Pérez, D., Alfonseca, E., Rodríguez, P.: Adapting the automatic assessment of free-text answers to the students profiles. In: Proceedings of the CAA conference, Loughborough, U.K. (2005)Google Scholar
  3. 3.
    Birenbaum, M., Tatsuoka, K., Gutvirtz, Y.: Effects of response format on diagnostic assessment of scholastic achievement. Applied psychological measurement 16 (1992)Google Scholar
  4. 4.
    Page, E.: The imminence of grading essays by computer. Phi Delta Kappan 47, 238–243 (1966)Google Scholar
  5. 5.
    Valenti, S., Neri, F., Cucchiarelli, A.: An overview of current research on automated essay grading. Journal of Information Technology Education 2, 319–330 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Diana Pérez-Marín
    • 1
  • Enrique Alfonseca
    • 1
    • 2
  • Pilar Rodríguez
    • 1
  1. 1.Computer Science DepartmentUniversidad Autonoma de Madrid 
  2. 2.Precision and Intelligence LaboratoryTokyo Institute of Technology 

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