QUANTUM ACCOUNTING
Quantum Tutors - Field Research:
Targeted Practice Feature Proven to Increase Student Learning Efficiency
with Less Study Time (Cal Poly State University)
Students in the Targeted Practice Group completed transactions
in less time and with greater accuracy than students in the Textbook
Group (15.5% faster with 26.5% more correct answers achieved per unit
of study time).
[View the one page PDF summary] [Download the full paper]
Quantum Tutors - Field Research:
AI Tutoring software Improves Student Test Scores by at least a Full
Letter Grade (Baldwin-Wallace College)
Sudents using the Quantum Tutor for transaction analysis achieved
3.5 times more gain in test scores over students who studied with
the textbook.
[View
the one page PDF summary] [Download
the full paper]
Quantum Tutors - Field Research: AI Tutoring Software Increases Test Scores and Maximizes Student Effectiveness (University of Saskatchewan)
After one group of students completed a homework assignment using the Quantum Tutor, their test scores improved 1.9 times more than a group of students who used an online homework management system. When the Quantum Tutor was removed from the first group of students and given to the other group, the pattern of performance differences was reversed, with the tutored group gaining 2.6 times more than the online homework group.
[View
the one page PDF summary] [Download the full paper]
Quantum Tutors - Learning Principles
of AI Technology
In this guide you will find an executive summary of the relevant educational research, learning theories and effective classroom practices that support the design of the Quantum Tutors. The paper discusses how the Quantum Tutors utilize inquiry-based learning, scientific thinking, modeling and scaffolding to teach students how to become better learners and independent thinkers. (PDF) [more]
QUANTUM CHEMISTRY/MATH
Quantum Tutors - Wexford Evaluation
Report
See what teachers and students say about the Quantum Tutors compared
to human tutors and other tutorial software. (PDF) [more]
Quantum Tutors - Balancing Chemical
Equations (High School Study)
Quantum Artificial Intelligence Tutoring
Software and Assessment Tool Improves Student Test Scores by Full
Letter Grade. (PDF) [more]
Quantum Tutors - Oxidation Numbers
(University Study)
Students Improve Problem-Solving Ability by 45% with Quantum Artificial
Intelligence Tutors. (PDF) [more]
Quantum Tutors - Learning Principles
of AI Technology
In this guide you will find an executive summary of the relevant educational research, learning theories and effective classroom practices that support the design of the Quantum Tutors. The paper discusses how the Quantum Tutors utilize inquiry-based learning, scientific thinking, modeling and scaffolding to teach students how to become better learners and independent thinkers. (PDF) [more]
Quantum Assessment Advisors - Oxidation Numbers (High School Study)
Research proves that Quantum Assessment
Advisors can significantly reduce or eliminate teachers' grading time
and are more accurate and consistent than human graders. (PDF)
[more]
PUBLISHED PAPERS
B. G. Johnson and D. A. Holder, “A Model-Tracing Intelligent Tutoring System for Oxidation Number Assignment”
The Chemical Educator, 15, 447-454 (2010). [more]
J. J. Kuhel, M. C. Wheeler, P. E. Miele, D. A. Holder, B. G. Johnson, A. A. Paterno Parsi and J. D. Madura, “Quantitative Impact of an Artificial Intelligence Tutoring System on Student Performance in Assigning Oxidation Numbers in Chemical Formulas”
The Chemical Educator, 15, 455-460 (2010). [more]
B. G. Johnson, E. Slayter and J. N. Tost, "Impact of Structure of Early Practice on Student Performance in Transaction Analysis"
Proceedings of the 2010 American Accounting Association Annual Meeting, San Francisco, CA (2010). [more]
B. G. Johnson, J. S. Dittel and D. A. Holder, “Accessible Artificial Intelligence-Based Chemistry Tutoring for Blind and Visually Impaired Students”
The Chemical Educator, 15, 171-177 (2010). [more]
B. G. Johnson, F. Phillips and L. G. Chase, “An Intelligent Tutoring System for the Accounting Cycle: Enhancing Textbook Homework with Artificial Intelligence”
Journal of Accounting Education, 27, 30-39 (2009).
M. B. Walsh, C. M. Moss, B. G. Johnson,
D. A. Holder and J. D. Madura, "Quantitative Impact of a Cognitive
Modeling Intelligent Tutoring System on Student Performance in Balancing
Chemical Equations," Chem. Educator 7, 379 (2002). [more]
D. A. Holder, B. G. Johnson and P. J.
Karol, "A Consistent Set of Oxidation Number Rules for Intelligent
Computer Tutoring," J. Chem. Educator 79, 465 (2002).
[more]
B. G. Johnson and D. A. Holder, "A Cognitive
Modeling Tutor Supporting Student Inquiry for Balancing Chemical Equations,"
Chem. Educator 7, 297 (2002). [more]
B. G. Johnson and D. A. Holder, "An
Artificial Intelligence-Based Program for Automated Grading of Student
Work in Balancing Chemical Equations," Chem. Educator 8,
271 (2003). [more]

Copies of these publications are available
upon request.