Predicting student success in an introductory programming course

ABSTRACT

This paper examines to what extent a student's aptitude in computer programming may be predicted through measuring certain cognitive skills, personality traits and past academic achievement. The primary purpose of this study was to build a practical and reliable model for predicting success in programming, with hopes of better counseling students. Results from correlating predictor variables with a student's final numerical score confirmed past studies which showed the diagramming and reasoning tests of the Computer Programmer Aptitude Battery and a student's GPA to be the predictors most closely associated with success. A multiple regression equation developed from 5 predictors correctly classified 61 of 79 students (77.2%) into low and high aptitude groups.

REFERENCES

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INDEX TERMS

Primary Classification:
  D. Software

Additional Classification:
  H. Information Systems
  H.1 MODELS AND PRINCIPLES

  K. Computing Milieux
  K.3 COMPUTERS AND EDUCATION
      K.3.2 Computer and Information Science Education
          Subjects: Curriculum

General Terms:
Design, Human Factors, Management, Measurement, Performance, Theory