Predicting student performance in a beginning computer science class

This study investigated the relationship between the student's grade in a beginning computer science course and their sex, age, high school and college academic performance, number of mathematics courses, and work experience. Standard measures of cognitive development, cognitive style, and personality factors were also given to 58 students in three sections of the beginning Pascal programming class. Significant relationships were found between the letter grade and the students' college grades, the number of hours worked and the number of high school mathematics classes. Both the Group Embedded Figures Test (GEFT) and the measure of Piagetian intellectual development stages were also significantly correlated with grade in the course. There was no relationship between grade and the personality type, as measured by the Myers-Briggs Type Indicator (MBTI); however, an interesting and distinctive personality profile was evident.

[1]  Peter R. Newsted,et al.  Grade and ability predictions in an introductory programming course , 1975, SGCS.

[2]  William Mitchell,et al.  Computer education in the 1980s, a somber view , 1980, SIGCSE '80.

[3]  Allen Newell,et al.  Human Problem Solving. , 1973 .

[4]  Arlie Daniel,et al.  Cognitive Style as a Predictor of Achievement: A Multivariate Analysis. , 1984 .

[5]  Herbert P. Ginsburg,et al.  The development of mathematical thinking , 1983 .

[6]  George P. McCabe,et al.  Predicting the success of freshmen in a computer science major , 1984, CACM.

[7]  C. A. Moore,et al.  Field-Dependent and Field-Independent Cognitive Styles and Their Educational Implications , 1977 .

[8]  Louis W. Glorfeld,et al.  Predicting Aptitude in Introductory Computing: A Classification Model , 1981 .

[9]  G. Michael Schneider,et al.  Methods for improving controlled experimentation in software engineering , 1981, ICSE '81.

[10]  D. F. Butcher,et al.  Predicting performance in an introductory computer science course , 1985, CACM.

[11]  Richard W.V. Cawley,et al.  Cognitive Styles and the Adult Learner , 1976 .

[12]  J. Piaget.  Intellectual Evolution from Adolescence to Adulthood , 1972 .

[13]  William M. Gray,et al.  Development of a Piagetian-Based Written Test: A Criterion-Referenced Approach. , 1973 .

[14]  M. Manis.  An introduction to cognitive psychology , 1971 .

[15]  Patricia W. Cox.  FIELD DEPENDENCE‐INDEPENDENCE AND PSYCHOLOGICAL DIFFERENTIATION BIBLIOGRAPHY WITH INDEX , 1980 .

[16]  Barry L. Kurtz,et al.  Investigating the relationship between the development of abstract reasoning and performance in an introductory programming class , 1980, SIGCSE '80.

[17]  I. B. Myers.  The Myers-Briggs Type Indicator: Manual (1962). , 1962 .

[18]  Mary S. Riley,et al.  Development of Children's Problem-Solving Ability in Arithmetic. , 1984 .

[19]  Donald Ross Green,et al.  Measurement and Piaget , 1971 .

[20]  Louis W. Glorfeld,et al.  Validation of a model for predicting aptitude for introductory computing , 1982, SIGCSE '82.

[21]  W GlorfeldLouis,et al.  Validation of a model for predicting aptitude for introductory computing , 1982 .

[22]  Dennis H. Sorge,et al.  Factors for Success as a Computer Science Major , 1984 .

[23]  Peter E. Pezaro.  Comments on “the development and construct validation of a group-administered test of formal thought”† , 1982 .

[24]  E. A. Unger,et al.  A predictor for success in an introductory programming class based upon abstract reasoning development , 1983, SIGCSE '83.

[25]  L KurtzBarry.  Investigating the relationship between the development of abstract reasoning and performance in an introductory programming class , 1980 .

[26]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[27]  Terry R. Hostetler,et al.  Predicting student success in an introductory programming course , 1983, SGCS.

[28]  Richard H. Austing,et al.  Curriculum '78: recommendations for the undergraduate program in computer science— a report of the ACM curriculum committee on computer science , 1979, CACM.

[29]  Meredith D. Gall,et al.  Educational Research: An Introduction , 1965 .

[30]  Michael Shayer,et al.  Group tests of cognitive development ideals and a realization , 1981 .

[31]  Alan K. Griffiths,et al.  Limitations of Recent Research Relating Piaget’s Theory to Adolescent Thought , 1982 .

[32]  D. Stevens.  Cognitive Processes and Success of Students in Instructional Computer Courses , 1983 .

[33]  Carol Ann Alspaugh.  Identification of Some Components of Computer Programming Aptitude. , 1972 .

[34]  John Konvalina,et al.  Math proficiency: a key to success for computer science students , 1983, CACM.

[35]  Lawrence J. Mazlack,et al.  Identifying potential to acquire programming skill , 1980, CACM.

[36]  J. E. Sammet,et al.  Software psychology: human factors in computer and information systems , 1983, SGCH.

[37]  Charles G. Petersen,et al.  Predicting Academic Success in Introduction to Computers. , 1979 .

[38]  Ruven E. Brooks,et al.  Studying programmer behavior experimentally: the problems of proper methodology , 1980, CACM.

[39]  H AustingRichard,et al.  Curriculum '78: recommendations for the undergraduate program in computer science a report of the ACM curriculum committee on computer science , 1979 .

[40]  Ronald J. Raven.  The development of a test of Piaget's logical operations , 1973 .

[41]  Gerald M. Weinberg,et al.  Psychology of computer programming , 1971 .

[42]  L. Greene,et al.  Effects of field dependence on affective reactions and compliance in dyadic interactions. , 1976 .

[43]  Marcia C. Linn,et al.  Influence of Cognitive Style and Training on Tasks Requiring the Separation of Variables Schema. , 1978 .

[44]  Kenneth L. Whipkey.  Identifying predictors of programming skill , 1984, SGCS.

[45]  R. H. Walters.  The Growth of Logical Thinking from Childhood to Adolescence , 1960 .

[46]  John Konvalina,et al.  Factors Influencing Success in Beginning Computer Science Courses. , 1981 .