Searching for variables and models to investigate mediators of learning from multiple representations

Proceedings of the 5th International Conference on Educational Data Mining, EDM 2012

Volumn , Issue , 2012, Pages

  Rau, Martina A ^a   Scheines, Richard ^b  

^a Carnegie Mellon University ^*  (United States)

^b CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

Log data; Mediation; Model search; Multiple representations; Variable search

Indexed keywords

ERRORS; GRAPHIC METHODS;

LOG DATA; MEDIATION; MODEL SEARCH; MULTIPLE REPRESENTATION; VARIABLE SEARCH;

DATA MINING;

EID: 85084017083     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. Aleven, A., Stahl, E., Schworm, S., Fischer, F., & Wallace, R. 2003. Help Seeking and Help Design in Interactive Learning Environments. Review of Educational Research, 73(3), 277-320.
2. Ainsworth, S. 2006. A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16, 183-198.
3. Anderson, J. R. 1993. Problem Solving and Learning. American Psychologist, 48(1), 1-35.
4. Baker, R., et al. 2008. Why Students Engage in “Gaming the System” Behavior in Interactive Learning Environments. Journal of Interactive Learning Research, 19(2), 185-224.
5. Bollen, K. 1989. Structural Equations with Latent Variables. Wyley, New York.
6. Charalambous, C. Y., & Pitta-Pantazi, D. 2007. Drawing on a Theoretical Model to Study Students' Understandings of Fractions. Educational Studies in Mathematics, 64, 293-316.
7. Chickering, D. M. 2002. Optimal Structure Identification with Greedy Search. Journal of Machine Learning Research 3, 507-554.
8. Croteau, E., Heffernan, N. T., & Koedinger, K. R. 2004. Why Are Algebra Word Problems Difficult? Using Tutorial Log Files and the Power Law of Learning to Select the Best Fitting Cognitive Model. Lecture Notes in Computer Science, 32200, 15-53.
9. De Croock, M. B. M., Van Merrienboer, J. J. G., & Paas, F. G. W. C. 1998. High versus low contextual interference in simulation-based training of troubleshooting skills: Effects on transfer performance and invested mental effort. Computers in Human Behavior, 14(2), 249-267.
10. Koedinger, K., & Corbett, A. 2006. Cognitive Tutors: Technology Bringing Learning Sciences to the Classroom. In: Sawyer, R. K. (ed.).The Cambridge handbook of the learning sciences, pp. 61-77, Cambridge University Press, New York, NY, US.
11. Koedinger, K., Anderson, J. R., Hadley, W., & Mark, M. 1997. Intelligent Tutoring Goes to School in the Big City. International Journal of Artificial Intelligence in Education, 8, 30-43.
12. National Mathematics Advisory Panel. 2008. Foundations for Success: Report of the National Mathematics Advisory Board Panel, U.S. Government Printing Office.
13. Newell, A., & Rosenbloom, P. 1981. Mechanisms of Skill Acquisition and the Law of Practice. In Anderson, J. (ed.). Cognitive Skills and Their Acquisition, Erlbaum Hillsdale NJ.
14. Pearl, J. 2000. Causality: Models, Reasoning, and Interference. Cambridge University Press.
15. Rau, M. A., Aleven, V., & Rummel, N. 2009. Intelligent tutoring systems with multiple representations and self-explanation prompts support learning of fractions. International Conference on Artificial Intelligence, 441-448.
16. Rau, M. A., Aleven, V., Tunc-Pekkan, Z., Pacilio, L., & Rummel, N. accepted. How to schedule multiple graphical representations? A classroom experiment with an intelligent tutoring system for fractions. To appear in the proceedings of ICLS 2012.
17. Ritter, S., Anderson, J. R., Koedinger, K. R., & Corbett, A. 2007. Cognitive Tutor: Applied Research in Mathematics Education. Psychometric Bulletin & Review, 14(2), 249-255.
18. Robers, Y. 1999. What Is Different about Interactive Graphical Representations? Learning and Instruction, 9, 419-425.
19. Robins, J., Scheines, R., Spirtes, P., & Wasserman, L. (2003). Uniform Consistency in Causal Inference, Biometrika, 90, 491 – 515.
20. Spirtes, P. Glymour, C., Scheines, R. (2000). Causation, Prediction, and Search. 2nd Edition, MIT Press.