Grade and ability predictions in an introductory programming course

Authors:
Peter R. Newsted
Affiliations:
Assistant Professor, School of Business Administration, University of Wisconsin - Milwaukee
Venue:
ACM SIGCSE Bulletin
Year:
1975

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Abstract

Two regression equations are derived to predict grade and ability in an introductory FORTRAN course. College GPA, programming experience, and career orientation are shown to be significant positive predictors; working in groups and time spent on the course are unexpectedly shown to be negative correlates. The implications of these findings for methods of teaching programming are discussed.