Identifying potential to acquire programming skill

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Identifying potential to acquire programming skill

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Communications of the ACM archive
Volume 23 , Issue 1 (January 1980) table of contents

Pages: 14 - 17

Year of Publication: 1980

ISSN:0001-0782

Author

Lawrence J. Mazlack

Univ. of Cincinnati, Cincinnati, OH

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 5, Downloads (12 Months): 44, Citation Count: 13

Additional Information:

abstract references cited by index terms collaborative colleagues

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ABSTRACT

Over several years, a large number of students took the same introductory programming course. The students were drawn from all academic disciplines and academic experience levels. Low correlations were found between success in the course or its evaluation components when posed against academic program, gender, or semester in school. Additionally, when the IBM Programmer's Aptitude Test was administered, the predictive value of the test was found to be low.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Bateman, C.R. Predicting performance in a basic computer course. Proc. of the Fifth Annual Meeting of the Amer. Inst. for Decision Sciences, Boston, Mass., 1973.
	2	Peter R. Newsted, Grade and ability predictions in an introductory programming course, ACM SIGCSE Bulletin, v.7 n.2, p.87-91, June 1975 [doi>10.1145/382205.382897]

CITED BY 13

	Gerald E. Evans , Mark G. Simkin, What best predicts computer proficiency?, Communications of the ACM, v.32 n.11, p.1322-1327, Nov. 1989
	Patricia F. Campbell , George P. McCabe, Predicting the success of freshmen in a computer science major, Communications of the ACM, v.27 n.11, p.1108-1113, Nov. 1984
	Ricky J. Barker , E. A. Unger, A predictor for success in an introductory programming class based upon abstract reasoning development, ACM SIGCSE Bulletin, v.15 n.1, p.154-158, February 1983
	N. Ram, Effectiveness of paradigmatic approach in teaching programming, Proceedings of the ACM 1980 annual conference, p.484-489, January 1980
	John Konvalina , Stanley A. Wileman , Larry J. Stephens, Math proficiency: a key to success for computer science students, Communications of the ACM, v.26 n.5, p.377-382, May 1983
	Louis W. Glorfeld , George C. Fowler, Validation of a model for predicting aptitude for introductory computing, ACM SIGCSE Bulletin, v.14 n.1, p.140-143, February 1982
	D. F. Butcher , W. A. Muth, Predicting performance in an introductory computer science course, Communications of the ACM, v.28 n.3, p.263-268, March 1985
	Simon, The cryptic crossword puzzle as a useful analogue in teaching programming, Proceedings of the sixth conference on Australasian computing education, p.299-303, January 01, 2004, Dunedin, New Zealand
	Tracy L. Lewis , J. D. Chase , Manuel A. Pérez-Quiñones , Mary Beth Rosson, The effects of individual differences on CS2 course performance across universities, ACM SIGCSE Bulletin, v.37 n.1, 2005
	Sarah H. Nash , Samuel T. Redwine, Jr., People and organizations in software production: a review of the literature, ACM SIGCPR Computer Personnel, v.11 n.3, p.10-21, Jan., 1988
	Kenneth L. Whipkey, Identifying predictors of programming skill, ACM SIGCSE Bulletin, v.16 n.4, p.36-42, Dec. 1984
	Larry S Corman, Cognitive style, personality type, and learning ability as factors in predicting the success of the beginning programming student, ACM SIGCSE Bulletin, v.18 n.4, p.80-89, Dec. 1986
	Laurie Honour Werth, Predicting student performance in a beginning computer science class, ACM SIGCSE Bulletin, v.18 n.1, p.138-143, February 1986

INDEX TERMS

Keywords:
PAT, ability, aptitude test correlation, prediction, programmer

Collaborative Colleagues:

Lawrence J. Mazlack: colleagues

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