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Working and Commuting College Students: How Do They Fare Academically?

Spady, William G., Jr.
Publication Year:
Report Number:
ETS Research Memorandum
Document Type:
Page Count:
Subject/Key Words:
Academic Achievement, College Students, Commuting college students.


The effects of working and commuting on the academic performance and attitudes of college students is studied here, using the College Student Questionnaire (CSQ). 253 students at a large, urban, Catholic college were given the questionnaire both as entering freshmen and at the end of the academic year. Attitudes toward school are considered in four categories, called the four philosophies: 1) Vocational (commitment mainly to career); 2) Collegiate (commitment mainly to college and extra-curricular activities); 3) Academic (commitment mainly to learning); and 4) Nonconformist (commitment mainly to search for individual values). Conclusions include: 1) the campus workers more often typified the "vocationalist" philosophy; 2) the campus non-workers more often typified the "collegiate philosophy; 3) the commuting workers, more often than not, tended to be curious, hard-working and involved; and 4) the nonworking commuters tended to resemble their non-commuting counterparts, but to be less involved and more "average." The same issues were then studied with the addition of a third independent variable--high school grade point average (GPA)--and it was discovered that some characteristics originally attributed to working or student residence were instead spurious effects of high school average (HSA) distribution within those groups. For some groups, however, the introduction of high school average as a control provided additional support for the earlier interpretations. Suggestions for future research strategies on this topic include 1) adding gender as a factor and increasing the sample size, 2) introducing gender as a control variable in place of HSA, and 3) substituting HSA for working, as a control variable. Five appendices show a correlation matrix of selected variables, instructions for computing gamma, strategies for working the CSQ data cards, testing the statistical significance of percentage differences, and problems for investigations with CSQ data.

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