Abstract
We present a conditional rewrite system for arithmetic and membership univariate constraints over real numbers, designed for computer assisted learning (CAL) in elementary math. Two fundamental principles guided the design of the proposed rewrite rules: cognitive fidelity (emulating steps students should take) and correctness, aiming that step-by-step solutions to problems look like ones carried out by students. In order to gain more flexibility to modify rules, add new ones and customize solvers, the rules are written in a specification language and then compiled to Prolog. The rewrite system is complete for a relevant subset of problems found in high-school math textbooks.
Partially funded by FCT and POSI, co-financed by EC fund FEDER, under project AGILMAT (contract POSI/CHS/48565/2002).
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Keywords
- Specification Language
- Symbolic Computation
- Atomic Constraint
- Arithmetic Constraint
- Artificial Intelligence Application
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Tomás, A.P., Moreira, N., Pereira, N. (2006). Designing a Solver for Arithmetic Constraints to Support Education in Mathematics. In: Maglogiannis, I., Karpouzis, K., Bramer, M. (eds) Artificial Intelligence Applications and Innovations. AIAI 2006. IFIP International Federation for Information Processing, vol 204. Springer, Boston, MA . https://doi.org/10.1007/0-387-34224-9_50
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DOI: https://doi.org/10.1007/0-387-34224-9_50
Publisher Name: Springer, Boston, MA
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