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IES Grant

Title: Integrated Software for Artificial Intelligence Tutoring and Assessment in Science
Center: NCER Year: 2004
Principal Investigator: Johnson, Benny Awardee: Quantum Simulations, Inc.
Program: Science, Technology, Engineering, and Mathematics (STEM) Education      [Program Details]
Award Period: 3 years Award Amount: $1,500,000
Type: Development and Innovation Award Number: R305K040008

American students do comparatively poorly in international studies of academic achievement at the high school level in chemistry, which is a core subject in the physical sciences course sequence in American high schools. To date the capacity of computer-assisted instruction in science to strengthen student learning has been considered quite limited. The purposes of this project are to complete the development of a computer-based tutoring and assessment system for a first-year chemistry course and to accumulate evidence of the potential of the system to improve student learning and achievement. The system is being designed for use by individual students on demand at school or at home.

The researchers are first developing the procedures for grading student work in an intelligent tutoring system that they have already created. Actual student work samples will be used to test and validate the system's procedures and to conduct an initial external review of the system with a small group of high school chemistry teachers. The system is being designed to provide helpful detailed comments to students if they make mistakes while trying to solve chemistry problems and to generate reports for teachers and students that analyze student learning as reflected by their performance on a given set of chemistry problems.

When the system is fully developed, it will be field tested with chemistry teachers in several high schools. In this quasi-experimental study, 10 to 12 teachers will implement the tutoring system with the assessment component in one chemistry class. In a second class, each teacher will continue normal instruction, not using any functions of the tutoring system. With a third class, each teacher will use the assessment system, but not the tutorial, and with a fourth class, each teacher will use only the tutoring program. Using a pre-post design, student achievement will be compared across the four groups. Because it is not possible to have a randomly selected group in this test, statistical analyses will be used to determine preexisting similarities and differences between the groups. The end result of this project will be a fully developed intelligent tutor and assessment system for high school chemistry with evidence of the potential of this system to improve high school students' chemistry achievement.

Project Website:

Related IES Projects: Integrated Software for Artificial Intelligence Tutoring and Assessment in Science (R305A070067) and A Randomized Controlled Study of the Effects of Intelligent Online Chemistry Tutors in Urban California School Districts (R305A080063)


Journal article, monograph, or newsletter

Johnson, B.G., and Holder, D.A. (2010). A Model-Tracing Intelligent Tutoring System for Oxidation Number Assignment. The Chemical Educator, 15: 447–454.

Kuhel, J.J., Wheeler, M.C., Miele, P.E., Holder, D.A., Johnson, B.G., Paterno Parsi, A.A., and Madura, J.D. (2010). Quantitative Impact of an Artificial Intelligence Tutoring System on Student Performance in Assigning Oxidation Numbers in Chemical Formulas. The Chemical Educator, 15: 455–460.