Grade and ability predictions in an introductory programming course

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Grade and ability predictions in an introductory programming course

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ACM SIGCSE Bulletin archive
Volume 7 , Issue 2 (June 1975) table of contents

Pages: 87 - 91

Year of Publication: 1975

ISSN:0097-8418

Author

Peter R. Newsted

Assistant Professor, School of Business Administration, University of Wisconsin - Milwaukee

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 2, Downloads (12 Months): 16, Citation Count: 9

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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.

CITED BY 9

	Jeanne M. Lee , Ben Shneiderman, Personality and programming: Time-sharing vs. batch preference, Proceedings of the 1978 annual conference, p.561-569, January 1978
	David Gries , Dorothy Marsh, The 1988–89 Taulbee survey report, Communications of the ACM, v.33 n.9, p.160-169, Sept. 1990
	Thomas Moher , G. Michael Schneider, Methods for improving controlled experimentation in software engineering, Proceedings of the 5th international conference on Software engineering, p.224-233, March 09-12, 1981, San Diego, California, United States
	Ernest Ferguson, Conference grading of computer programs, ACM SIGCSE Bulletin, v.19 n.1, p.361-365, Feb. 1987
	Lawrence J. Mazlack, Identifying potential to acquire programming skill, Communications of the ACM, v.23 n.1, p.14-17, Jan. 1980
	Appa Rao Korukonda, Personality, individual characteristics, and predisposition to technophobia: some answers, questions, and points to ponder about, Information Sciences—Informatics and Computer Science: An International Journal, v.170 n.2-4, p.309-328, 25 February 2005
	Gary D. Boetticher , Wei Ding , Charles Moen , Kwok-Bun Yue, Using a pre-assessment exam to construct an effective concept-based genetic program for predicting course success, ACM SIGCSE Bulletin, v.37 n.1, 2005
	C. K. Capstick , J. D. Gordon , A. Salvadori, Predicting performance by university students in introductory computing courses, ACM SIGCSE Bulletin, v.7 n.3, p.21-29, Sept. 1975
	Laurie Honour Werth, Predicting student performance in a beginning computer science class, ACM SIGCSE Bulletin, v.18 n.1, p.138-143, February 1986