ERIC Number: ED178151
Record Type: RIE
Publication Date: 1979-Nov
Reference Count: 0
Predicting Success of Programming Students.
Jones, Jerry L.
A study was conducted to determine the optimum combination of selected social, academic, and demographic variables to maximally differentiate membership in the successful, unsuccessful, and withdrawal groups of first-year computer programming majors in Virginia community colleges. A questionnaire focusing on 18 selected variables was administered to 106 students at eight community colleges. Course grades permitted classification into the successful, unsuccessful, and withdrawal groups. The most discriminating variables, as evidenced by the standardized coefficient values, were (1) grade-point average; (2) student's perception of teacher's attitude toward students; (3) student's perception of teacher's fairness in grading; (4) type of employment; (5) student's stated reason for initial enrollment in programming curriculum; and (6) total yearly income in student's household. The demographic variables (sex, marital status, race, and age) did not appear to discriminate among the groups. A number of academic and social variables commonly thought to discriminate among successful and unsuccessful groups (e.g., level of college English competence and amount of employment) did not contribute to the separation of the three respondent groups. The study report contains recommendations to administrators of computer programming curricula. (Author/AYC)
Descriptors: Academic Achievement, Academic Failure, Age, Community Colleges, Employment, Ethnic Groups, Females, Grade Point Average, Grade Prediction, Grades (Scholastic), Males, Marital Status, Persistence, Predictive Measurement, Predictive Validity, Predictor Variables, Student Characteristics, Student Evaluation of Teacher Performance, Two Year College Students, Two Year Colleges
Publication Type: Reports - Research
Education Level: N/A
Authoring Institution: N/A