scholarly journals Quantitative Reasoning for Proving Lock-Freedom

2013 ◽  
Author(s):  
Jan Hoffmann ◽  
Michael Marmar ◽  
Zhong Shao
Keyword(s):  
Quantitative Reasoning

Investigating the Effects of a Fact Family Fluency Intervention on Math Facts Fluency and Quantitative Reasoning

2021 ◽  
Author(s):  
James D. Stocker ◽  
Elizabeth M. Hughes ◽  
Andrew Wiesner ◽  
Shirley Woika ◽  
Michele Parker ◽  
...  
Keyword(s):  
Quantitative Reasoning ◽  
Fluency Intervention ◽  
Math Facts ◽  
Math Facts Fluency

An Inquiry-Based Quantitative Reasoning Course for Business Students

PRIMUS ◽  
2017 ◽  
Vol 27 (7) ◽  
pp. 693-706 ◽  
Author(s):  
Victor Piercey ◽  
Erin Militzer
Keyword(s):  
Business Students ◽  
Quantitative Reasoning

scholarly journals Using psychometric tools as a window into students’ quantitative reasoning in introductory physics

2020 ◽  
Author(s):  
Trevor I. Smith ◽  
Philip Eaton ◽  
Suzanne White Brahmia ◽  
Alexis Olsho ◽  
Andrew Boudreaux ◽  
...  
Keyword(s):  
Introductory Physics ◽  
Quantitative Reasoning

Integration of qualitative and quantitative reasoning in iterative parametric mechanical design

1992 ◽  
Vol 6 (2) ◽  
pp. 95-109 ◽  
Author(s):  
Von-Wun Soo ◽  
Tse-Ching Wang
Keyword(s):  
Parametric Design ◽  
Mechanical Design ◽  
Qualitative Reasoning ◽  
Quantitative Reasoning ◽  
Design Parameters ◽  
Qualitative And Quantitative ◽  
Compression Spring ◽  
Dependency Network ◽  
Previous Design ◽  
Local Variable

A framework IPD (Iterative Parametric Design) is proposed to assist the iterative parametric mechanical design process. To effectively find a set of satisfiable values for the design parameters the key is to find good heuristics to adjust or tune the parametric values resulting from previous design iterations. We propose that heuristics can come from two aspects by both qualitative and quantitative reasoning. Qualitative reasoning, based on confluences, provides global control over the feasible directions of variable adjustments, while quantitative reasoning, based on the dependency network and perturbation analysis, can be used to propose actual quantity of local variable adjustments. We used the design of a helical compression spring as an example to illustrate the performance of IPD system. We show that IPD can often find a solution faster than those without guidance of qualitative and quantitative reasoning.

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