Abstract
It is difficult to build intelligent tutoring systems in the domain of programming due to the complexity and variety of possible answers. To simplify this process, we have constructed a language-independent canonicalized model for programming solutions. This model allows for much greater overlap across different students than a basic text model, which enables more self-sustaining hint generation methods in programming tutors.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Pears, A., Seidman, S., Malmi, L., Mannila, L., Adams, E., Bennedsen, J., Devlin, M., Paterson, J.: A survey of literature on the teaching of introductory programming. ACM SIGCSE Bulletin 39(4), 204–223 (2007)
Xu, S., Chee, Y.S.: Transformation-Based Diagnosis of Student Programs for Programming Tutoring Systems. IEEE Transactions on Software Engineering 29(4), 360–384 (2003)
Barnes, T., Stamper, J.: Toward Automatic Hint Generation for Logic Proof Tutoring Using Historical Student Data. In: Woolf, B.P., Aïmeur, E., Nkambou, R., Lajoie, S. (eds.) ITS 2008. LNCS, vol. 5091, pp. 373–382. Springer, Heidelberg (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rivers, K., Koedinger, K.R. (2012). A Canonicalizing Model for Building Programming Tutors. In: Cerri, S.A., Clancey, W.J., Papadourakis, G., Panourgia, K. (eds) Intelligent Tutoring Systems. ITS 2012. Lecture Notes in Computer Science, vol 7315. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30950-2_80
Download citation
DOI: https://doi.org/10.1007/978-3-642-30950-2_80
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30949-6
Online ISBN: 978-3-642-30950-2
eBook Packages: Computer ScienceComputer Science (R0)