Human-machine student model discovery and improvement using datashop

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6738 LNAI, Issue , 2011, Pages 353-360

  Stamper, John C ^a   Koedinger, Kenneth R ^a  

^a Carnegie Mellon University   (United States)

Author keywords

cognitive modeling; data mining; machine learning

Indexed keywords

COGNITIVE MODELING; DATA SETS; GEOMETRY MODEL; HUMAN-MACHINE; MACHINE-LEARNING; MODELING TOOL; PLANNING AND EXECUTION; PROBLEM DECOMPOSITION; STUDENT MODELS; TUTORING SYSTEM;

ARTIFICIAL INTELLIGENCE; DATA VISUALIZATION; EDUCATION COMPUTING; VISUALIZATION;

STUDENTS;

EID: 79959321670     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-21869-9_46     Document Type: Conference Paper

References (13)

1. Cen, H., Koedinger, K.R., Junker, B.: Learning Factors Analysis-A General Method for Cognitive Model Evaluation and Improvement. In: Ikeda, M., Ashley, K.D., Chan, T.-W. (eds.) ITS 2006. LNCS, vol. 4053, pp. 164-175. Springer, Heidelberg (2006). (Pubitemid 44117589)
2. Clark, R.E., Feldon, D., van Merriënboer, J., Yates, K., Early, S.: Cognitive task analysis. In: Spector, J., Merrill, M., van Merriënboer, J., Driscoll, M. (eds.) Handbook of Research on Educational Communications and Technology, Mahwah, NJ, pp. 577-593 (2007).
3. Collins, M., Dasgupta, S., Schapire, R.: A generalization of PCA to the exponential family. In: Procs. of the 14th Conf. on Neural Info. Processing Systems, NIPS (2001).
4. Corbett, A.T., Anderson, J.R.: Knowledge tracing: Modeling the acquisition of Procedural knowledge. User Modeling and User-Adapted Interaction, 253-278 (1995).
5. Heffernan, N., Koedinger, K.: A developmental model for algebra symbolization: The results of a difficulty factors assessment. In: Gernsbacher, M.A., Derry, S.J. (eds.) Procs. of the 20th Annual Conf. of the Cognitive Science Society, Mahwah,NJ, pp. 484-489 (1998).
6. Koedinger, K.R., Baker, R.S.J.d., Cunningham, K., Skogsholm, A., Leber, B., Stamper, J.: A Data Repository for the EDM commuity: The PSLC DataShop. In: Romero, V., Pechenizkiy, B. (eds.) Handbook of Educational Data Mining. CRC Press, Boca Raton (2010).
7. Koedinger, K., McLaughlin, E.: Seeing language learning inside the math: Cognitive analysis yields transfer. In: Procs. of the 32nd Ann. Conf. of the Cogitive Science Society (2010).
8. Koedinger, K.R., Nathan, M.J.: The real story behind story problems: Effects of representations on quantitative reasoning. The Jrnl of the Learning Sciences 13(2), 129-164 (2004). (Pubitemid 38614619)
9. Lee, R.L.: Cognitive task analysis: A meta-analysis of comparative studies. Unpublished doctoral dissertation, University of Southern California, Los Angeles, CA (2003).
10. Tatsuoka, K.K.: Rule space: An approach for dealing with misconceptions based on item response theory. Journal of Educational Measurement 20, 345-354 (1983).
11. VanLehn, K.: The behavior of tutoring systems. Intl Jrnl of AIED 16, 227-265 (2006).
12. Villano, M.: Probabilistic student models: Bayesian Belief Networks and Knowledge Space Theory. In: Procs. of the 2nd International Conference on ITS, pp. 491-498. Springer, Heidelberg (1992).
13. Wilson, M., de Boeck, P.: Descriptive and explanatory item response models. In: de Boeck, P., Wilson, M. (eds.) Explanatory Item Response Models, pp. 43-74. Springer, Heidelberg (2004)