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Science, Technology, Engineering, and Mathematics (STEM) Education

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Integrated Software for Artificial Intelligence Tutoring and Assessment in Science

Year: 2004
Name of Institution:
Quantum Simulations, Inc.
Goal: Development and Innovation
Principal Investigator:
Johnson, Benny
Award Amount: $1,500,000
Award Period: 3 years
Award Number: R305K040008

Description:

Purpose: In the early 2000s, the capacity of computer-assisted instruction in science to strengthen student learning was quite limited. In this project, the researchers planned to complete the development of a computer-based tutoring and assessment system for a first-year high school chemistry course. Additionally, they hoped to accumulate evidence of the potential of the system to improve student learning and achievement. The proposed system would be for use by individual students on demand at school or at home.

Structured Abstract

THE FOLLOWING CONTENT DESCRIBES THE PROJECT AT THE TIME OF FUNDING

Intervention: 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.

Research Design and Methods: 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. 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.

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

Products and Publications

ERIC Citations: Find available citations in ERIC for this award here.

Select Publications:

Journal articles

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.