Multivariate analysis of student performance in large engineering economy classes

Author

Sullivan, William G. ; Daghestani, Shamil F. ; Parsaei, Hamid R.

Author_Institution

Dept. of Ind. & Syst. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA

Volume

1

fYear

1996

fDate

6-9 Nov 1996

Firstpage

180

Abstract

Based on multivariate data collected over three years, linear regression equations are developed and used to assess student learning in large sections of engineering economy taught at Virginia Tech. In each year (1993, 1994 and 1995), more than 350 students in the fall semester voluntarily participated in this research. This paper presents the principal findings of the study and demonstrates the use of multivariate linear regression for evaluating student performance (learning) in engineering economy

Keywords

economics; educational administrative data processing; engineering education; statistical analysis; engineering economy classes; linear regression equations; multivariate data; student learning; student performance; Data analysis; Data engineering; Industrial engineering; Linear regression; Nonlinear equations; Performance analysis; Quantum cellular automata; Regression analysis; Systems engineering and theory; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Frontiers in Education Conference, 1996. FIE '96. 26th Annual Conference., Proceedings of

Conference_Location

Salt Lake City, UT

ISSN

0190-5848

Print_ISBN

0-7803-3348-9

Type

conf

DOI

10.1109/FIE.1996.569939

Filename

569939