Identifying potential to acquire programming skill

Authors:
Lawrence J. Mazlack
Affiliations:
Univ. of Cincinnati, Cincinnati, OH
Venue:
Communications of the ACM
Year:
1980

Citing 1
Cited 16

Grade and ability predictions in an introductory programming course

ACM SIGCSE Bulletin

Predicting performance in an introductory computer science course

Communications of the ACM
Predicting student performance in a beginning computer science class

SIGCSE '86 Proceedings of the seventeenth SIGCSE technical symposium on Computer science education
Cognitive style, personality type, and learning ability as factors in predicting the success of the beginning programming student

ACM SIGCSE Bulletin
People and organizations in software production: a review of the literature

ACM SIGCPR Computer Personnel
What best predicts computer proficiency?

Communications of the ACM
Math proficiency: a key to success for computer science students

Communications of the ACM
Predicting the success of freshmen in a computer science major

Communications of the ACM
Identifying predictors of programming skill

ACM SIGCSE Bulletin
A predictor for success in an introductory programming class based upon abstract reasoning development

SIGCSE '83 Proceedings of the fourteenth SIGCSE technical symposium on Computer science education
Validation of a model for predicting aptitude for introductory computing

SIGCSE '82 Proceedings of the thirteenth SIGCSE technical symposium on Computer science education
Effectiveness of paradigmatic approach in teaching programming

ACM '80 Proceedings of the ACM 1980 annual conference
The cryptic crossword puzzle as a useful analogue in teaching programming

ACE '04 Proceedings of the Sixth Australasian Conference on Computing Education - Volume 30
The effects of individual differences on CS2 course performance across universities

Proceedings of the 36th SIGCSE technical symposium on Computer science education
Identification of Cognitive Processes of Effective and Ineffective Students During Computer Programming

ACM Transactions on Computing Education (TOCE)
Predicting student exam's scores by analyzing social network data

AMT'12 Proceedings of the 8th international conference on Active Media Technology
Some prospective approaches for the shift of programming paradigms

Proceedings of the 2013 International Conference on Information Systems and Design of Communication

Quantified Score

Hi-index	48.28

Visualization

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.