Multivariate analysis of student performance in large engineering economy classes

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

Research output: Contribution to journalArticle

3 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)180-184
Number of pages5
JournalProceedings - Frontiers in Education Conference
Publication statusPublished - 1996
Externally publishedYes

Fingerprint

multivariate analysis
Students
engineering
Linear regression
economy
performance
regression
learning performance
student
semester
learning
Multivariate Analysis

ASJC Scopus subject areas

  • Engineering(all)
  • Industrial and Manufacturing Engineering

Cite this

Multivariate analysis of student performance in large engineering economy classes. / Sullivan, William G.; Daghestani, Shamil F.; Parsaei, Hamid.

In: Proceedings - Frontiers in Education Conference, 1996, p. 180-184.

Research output: Contribution to journalArticle

@article{0d69b4ef1e8948fe8a1c3ec6b1437024,
title = "Multivariate analysis of student performance in large engineering economy classes",
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.",
author = "Sullivan, {William G.} and Daghestani, {Shamil F.} and Hamid Parsaei",
year = "1996",
language = "English",
pages = "180--184",
journal = "Proceedings - Frontiers in Education Conference, FIE",
issn = "0190-5848",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Multivariate analysis of student performance in large engineering economy classes

AU - Sullivan, William G.

AU - Daghestani, Shamil F.

AU - Parsaei, Hamid

PY - 1996

Y1 - 1996

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0030411370&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0030411370&partnerID=8YFLogxK

M3 - Article

SP - 180

EP - 184

JO - Proceedings - Frontiers in Education Conference, FIE

JF - Proceedings - Frontiers in Education Conference, FIE

SN - 0190-5848

ER -