Multivariate analysis of student performance in large engineering economy classes

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

Research output: Contribution to journalConference article

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 - 1 Dec 1996
EventProceedings of the 1996 26th Annual Conference on Frontiers in Education, FIE'96. Part 1 (of 3) - Salt Lake City, UT, USA
Duration: 6 Nov 19969 Nov 1996

ASJC Scopus subject areas

  • Software
  • Education
  • Computer Science Applications

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