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The Chemical Educator

ISSN: 1430-4171 (electronic version)

Table of Contents

Abstract Volume 15 (2010) pp 455-460

Quantitative Impact of an Artificial Intelligence Tutoring System on Student Performance in Assigning Oxidation Numbers in Chemical Formulas

Joseph J. Kuhel†, Matthew C. Wheeler†, Paul E. Miele†, Dale A. Holder† and Benny G. Johnson* Alicia A. Paterno Parsi‡, and Jeffry D. Madura‡

†Quantum Simulations, Inc., 5275 Sardis Road, Murrysville, PA 15668,; ‡Department of Chemistry and Biochemistry, Duquesne University, 308 Mellon Hall, Pittsburgh, PA 15282
Received August 7, 2010. Accepted September 23, 2010.

Published: 22 December 2010

Abstract. We report the evaluation in a university general chemistry course of a tutoring system for oxidation number assignment that is based on artificial intelligence principles. The system evaluated differs from conventional chemistry tutorial software in several important respects. It can tutor the assignment of oxidation numbers for any chemical formula entered by the student, rather than being limited to a fixed set of problems, and analyze and respond to the student’s own work, which is directly entered by the student in detail one step at a time. A quasi-experimental pre-/post-test study found that students who used the tutor to study during homework had a 60.7% greater performance gain between the pre-test and post-test than control group students who did the same homework. The increase in ability to solve problems correctly was statistically significant with a significance level of p << 0.001.

Key Words: In the Classroom; general chemistry; oxidation numbers; intelligent tutoring systems; computer-assisted instruction; post-secondary education; secondary education

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