Evaluating the performance of a diagnosis system in school algebra

Authors:
Naima El-Kechaï/;É/lisabeth Delozanne;Dominique Pré/vit;Brigitte Grugeon;Fran$#231/oise Chenevotot
Affiliations:
LIP6, UPMC-Sorbonne Université/s, Paris, France;LIP6, UPMC-Sorbonne Université/s, Paris, France;LIP6, UPMC-Sorbonne Université/s, Paris, France;LDAR --- Université/ Paris Diderot, Paris, France;LDAR --- Université/ Paris Diderot, Paris, France
Venue:
ICWL'11 Proceedings of the 10th international conference on Advances in Web-Based Learning
Year:
2011

Citing 5
Cited 0

Automatic Multi-criteria Assessment of Open-Ended Questions: A Case Study in School Algebra

ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
You Can't Fatten A Hog by Weighing It - Or Can You? Evaluating an Assessment for Learning System Called ACED

International Journal of Artificial Intelligence in Education
DIANE, a diagnosis system for arithmetical problem solving

Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Addressing the assessment challenge with an online system that tutors as it assesses

User Modeling and User-Adapted Interaction
Automatic calculation of students' conceptions in elementary algebra from aplusix log files

ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper deals with PépiMep, a diagnosis system in school algebra. Our proposal to evaluate the students' open-ended answers is based on a mixed theoretical and empirical approach. First, researchers in Math Education list different types of anticipated patterns of answers and the way to evaluate them. Then, this information is stored in an XML file used by the system to match a student's input with an anticipated answer. Third, as it is impossible to anticipate every student's answer, the system can improve: when an unknown form is detected, it is added to the XML file after expert inspection. Results from testing 360 students showed that, in comparison with human experts, PépiMep (1) was very effective in recognizing the different types of solutions when students' input was an algebraic expression (2) but was less effective when students entered a reasoned response expressed by a mix of algebraic expressions and natural language utterances.