Automatic hint generation for logic proof tutoring using historical data

Educational Technology and Society

Volumn 13, Issue 1, 2010, Pages 3-12

  Barnes, Tiffany ^a   Stamper, John ^a  

^a University of North Carolina at Charlotte   (United States)

Author keywords

Educational data mining; Hint generation; Intelligent tutoring; Propositional logic proofs

Indexed keywords

EID: 77954289006     PISSN: 11763647     EISSN: 14364522     Source Type: Journal    
DOI: None     Document Type: Article

References (19)

1. Anderson, J., & Gluck, K. (2001). What role do cognitive architectures play in intelligent tutoring systems? In D. Klahr & S. Carver (Eds.), Cognition & Instruction: 25 years of progress (pp. 227-262). Mahwah, NJ: Erlbaum.
2. Baffes, P., & Mooney, R. J. (1996). A novel application of theory refinement to student modeling. AAAI-96: Proceedings of the 13th National Conference on Artificial Intelligence (pp. 403-408), Menlo Park, CA: AAAI Press.
3. Barnes, T. (2006). Evaluation of the q-matrix method in understanding student logic proofs. In G. Sutcliffe & R. Goebel (Eds.), Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference, Menlo Park, CA: AAAI Press.
4. Barnes, T., & Stamper, J. (2007). Toward the extraction of production rules for solving logic proofs, In Proc. 13th Intl. Conf. on Artificial Intelligence in Education, Educational Data Mining Workshop. Online proceedings retrieved March 25, 2009, from http://aied.inf.ed.ac.uk/AIED2007/AIED-EDM_proceeding_full2.pdf.
5. st Annual International Conference on Educational Data Mining. Montreal, CA, June 20-21, 2008, Retrieved March 25, 2009, from http://www.educationaldatamining.org/EDM2008/index.php?page=proceedings.
6. Beck, J., Woolf, B., & Beal, C. (2000). ADVISOR: A machine learning architecture for intelligent tutor construction. In AAAI-96: Proceedings of the 7th National Conference on Artificial Intelligence pp. (552-557). Menlo Park, CA: AAAI Press.
7. Croy, M. J, (2000). Problem solving, working backwards, and graphic proof representation, Teaching Philosophy 23, 169-187.
8. Croy, M., Barnes, T., & Stamper, J. (2007). Towards an intelligent tutoring system for propositional proof construction. In P. Brey, A. Briggle, & K. Waelbers (Eds.), Proceedings of the 2007 European Computing And Philosophy Conference, Amsterdam, Netherlands: IOS Publishers.
9. Joint Task Force for Computing Curricula, ACM, AIS, & IEEE. (2005). Computing curricula 2005. Retrieved March 26, 2009, from http://www.acm.org/education/education/curric_vols/CC2005-March06Final.pdf
10. Koedinger, K., Aleven, V., Heffernan, N., McLaren, B., & Hockenberry, M. (2004, August). Opening the door to nonprogrammers: Authoring intelligent tutor behavior by demonstration. Proceedings of the 7th Intl. Conf. ITS-2004: Intelligent Tutoring Systems. Maceió, Brazil: Springer.
11. McKendree, J. (1990, December). Effective feedback content for tutoring complex skills. Human-Computer Interaction, 5(4), pp. 381-413.
12. McLaren, B., Koedinger, K., Schneider, M., Harrer, A., & Bollen, L. (2004, August). Bootstrapping Novice Data: Semiautomated tutor authoring using student log files, In Proc. Workshop on Analyzing Student-Tutor Interaction Logs to Improve Educational Outcomes, Proceedings of the 7th Intl. Conf. ITS-2004: Intelligent Tutoring Systems. Maceió, Brazil: Springer.
13. Merceron, A., & Yacef, K. (2005). Educational data mining: A case study. In 12th Intl. Conf. Artificial Intelligence in Education. Amsterdam, Netherlands: IOS Press.
14. Mitrovic, A., Koedinger, K. & Martin, B. (2003). A comparative analysis of cognitive tutoring and constraint-based modeling. User Modeling 2003: Proceedings of the 9th International Conference, UM 2003, Johnstown, PA, USA, June 22-26, 2003, Lecture Notes in Computer Science (pp. 313-322). Berlin: Springer.
15. Murray, T. (1999). Authoring intelligent tutoring systems: An analysis of the state of the art. Intl. J. Artificial Intelligence in Education, 10: 98-129.
16. Sieg, W. (2007). The AProS Project: Strategic thinking & computational logic. Logic Journal of IGPL. Retrieved March 26, 2009, from http://jigpal.oxfordjournals.org/cgi/content/abstract/jzm026v1
17. Stamper. J. (2006, September). Automating the generation of production rules for intelligent tutoring systems. Proc. Intl. Conf. Computer-Aided Learning (ICL2006), Villach, Austria: Kassel University Press.
18. Sutton, R., and Barto, A. G. (1998). Reinforcement learning: An introduction. Cambridge, MA: MIT Press.
19. Van Lehn, K. (2006). The behavior of tutoring systems, International Journal of Artificial Intelligence in Education 16, 227-265.