Investigating the effect of reverse engineering pedagogy in K‐12 robotics education

Author(s):  
Baichang Zhong ◽  
Siya Kang ◽  
Zehui Zhan
2013 ◽  
pp. 1342-1364
Author(s):  
Kristen Stubbs ◽  
Jennifer Casper ◽  
Holly A. Yanco

While a large number of robotics programs for K-12 students have been developed and deployed in the past twenty years, the effect that these programs have on students' motivations to enter science, technology, engineering, and mathematics (STEM) careers has yet to be fully determined. In order to demonstrate the value of these programs, researchers must make a concerted effort to measure their impact. Based on prior work in the evaluation of educational robotics programs, the authors of this chapter present frequently-utilized evaluation and measurement methods as well as guidelines for selecting these methods based on factors such as a program's duration, size, and maturity. This chapter is intended for use as a reference guide for designing evaluations of K-12 educational robotics programs.


Author(s):  
Kristen Stubbs ◽  
Jennifer Casper ◽  
Holly A. Yanco

While a large number of robotics programs for K-12 students have been developed and deployed in the past twenty years, the effect that these programs have on students’ motivations to enter science, technology, engineering, and mathematics (STEM) careers has yet to be fully determined. In order to demonstrate the value of these programs, researchers must make a concerted effort to measure their impact. Based on prior work in the evaluation of educational robotics programs, the authors of this chapter present frequently-utilized evaluation and measurement methods as well as guidelines for selecting these methods based on factors such as a program’s duration, size, and maturity. This chapter is intended for use as a reference guide for designing evaluations of K-12 educational robotics programs.


2008 ◽  
Vol 45 ◽  
pp. 161-176 ◽  
Author(s):  
Eduardo D. Sontag

This paper discusses a theoretical method for the “reverse engineering” of networks based solely on steady-state (and quasi-steady-state) data.


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