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Development of the Student

Success Scale to Predict Non-Intellectual Factors Related to Student Retention and Achievement

By Joan H. Rollins, Mary Zahm, Peter F. Merenda, and Gary Burkholder

This article reports on the preliminary development of a Student Success Scale to measure non-intellectual factors related to college achievement as measured by grade point average (GPA). A 200 item scale was completed by 340 students at Rhode Island College during fall semester 1998. Grade point averages were obtained 275 students from the Records Office in February of 2000. Exploratory factor analysis indicated there were seven factors. Three of the factors, Hard Work/Time Management, Responsibility and Self-Confidence were significantly correlated with students’ grade point averages. Some items that did not load on any factor were also correlated with GPA.

The purpose of the research reported is the development of a Student Success Scale that is being constructed to delineate non-intellectual psychological factors related to student achievement, as measured by grade point average (GPA) and graduation rates.

We are proposing that attaining of high grades in college, often while working at a job full-time or part-time and, as is the case of many of our students today managing family obligations as well, qualifies as a stressful situation that requires non-intellectual psychological skills as well as intellectual ability Although college and university admissions offices select students based on high school grade point averages (GPAs) and standardized test scores such as the Scholastic Aptitude Exams (SATs), which measure math and verbal academic potential, many students who begin college fail to graduate. United States Education Secretary Richard Reilly recently reported that the college drop out rate stands at 25 percent (Panel to study ‘who cares-syndrome,’ 2000, June 16). The percentage is higher at state supported colleges such as Rhode Island College where only 45% of students entering the college in 1991 had graduated six years later (Student Retention, 1998). The drop out rate is costly in terms of personal lives, the college or institution spending financial aid and other resources on students who do not graduate, and society not benefiting from a trained citizenry.

A body of research has been emerging in recent years, reporting certain non-intellectual factors to be correlated with GPA of college students. Several studies have found that students who actively manage their time have higher GPAs than students who do not plan and schedule their time. One study with ninety college students at the University of Georgia found that time management was a better predictor of GPA than SAT test scores. Students self-report questionnaires indicated that better students had better Time Attitudes, which meant they had a better sense of control over their time and said “No” to unproductive activities (Britton & Tesser, 199l). The second factor predictive of higher grades was Short Range Planning. It encompassed activities such as weekly and daily planning lists. In another study, students were randomly divided into two experimental groups, a specific monthly schedule group and a moderately specific monthly schedule group and a control group (Kirschenbaum, Malett, & Humphrey, 1982). In a one-year follow-up study, they found that students who used the more flexible moderately specific monthly planning schedule in combination with rewards to encourage themselves to persist in achieving their goals had significantly better performance in school work than students in the other conditions.

Self-efficacy is concerned with judgments of capability of performing a specific task (Bandura, 1997). Self-efficacy for performing well in specific courses has been related to less worry about the course and lower general test anxiety (Bandalos, Yates, & Thorndike-Christ (1995). Another factor related to levels of text anxiety has been goal orientation. When the goal is a performance goal (i. e., the grade) the student is more likely to have test anxiety than when the student has a learning goal (i.e., learning statistics), which is more likely to lead to changes in learning strategies and increased effort when the student encounters difficulty (Ames & Archer, 1988; Elliot & Dweck, 1988). The reason for this difference seems to be that students who have performance goals are more likely to attribute failure to external, uncontrollable causes such as luck or hard teachers, and to attribute success to internal, controllable causes such as effort.

People with high self-esteem are more accurate in judging their strengths and weaknesses than individuals low in self-esteem (Baumgardner, 1990). Therefore, people with high self-esteem are able to set appropriate goals, and are able to make use of information about a task to determine the optimal level of persistence and personal effort that they need to expend in order to successfully complete it (Sandelands, Brockner, & Glynn, 1988). The sense of self-certainty, the feeling that the person knows oneself, seems to be a factor leading to high self-esteem.

Based on research such as this, we undertook to write 200 items for the initial Student Success Scale. We hypothesized that factors on the Student Success Scale would correlate with grade point average (GPA).


The research proposal was approved by the Human Participants in Research Committee at Rhode Island College. A 200 item Student Success Scale was completed by 340 undergraduate students who responded to the scale on a scan sheet during class time, or as volunteers outside of class. Many of the students responding to the scale were first semester freshman enrolled in College Course 101, which is a course designed to help them adjust to college. I asked the Psychology Department secretary to inform me of when a faculty member was going to cancel class because of illness and asked the faculty member if I could go to their class and administer the scale instead of canceling it. Some faculty also gave students extra credit for taking the scale outside of class. In that case, faculty members were informed that they had to make an alternative for extra credit available to the class.

Participants were given an informed consent sheet that indicated that “the purpose of this research is to pre-test a scale which is designed to determine those feelings, thoughts and behaviors related to a successful transition to college.” They were also told that responding to the scale was completely voluntary and that they could discontinue responding to the scale at any time. They were asked not to put their names on the scan sheet, but to put their social security numbers on the scan sheet in order for it to be possible to examine the relationship of scale scores to college grade point average and college completion. They were informed that their academic record would be checked every year for up to six years in order to determine their grade point average (GPA) and enrollment status. The research reported here was a prospective design. Students completed the scale during fall semester 1998, and GPAs were checked in February of 2000.


Factor analysis was performed using SAS Version 6.12. The purpose of factor analysis is to determine if the observed variables, in this case the responses to the individual questions, could be explained in terms of a much smaller number of variables called factors. Exploratory factor analysis using oblique (PROMAX) rotation was conducted on 194 items of the original instrument (six items were deleted since they were redundant with other items in the instrument). Analysis indicated that there were seven principal components. Items associated with the seven factors were resubmitted to principal components analysis after removing items that were complex (i.e., difference in factor loadings on two or more factors were less than or equal to .20). The solution indicated seven factors: Resiliency versus Vulnerability (34 items; _ =.94); Hard Work (22 items; _ =.91); Responsibility (18 items; _ =.85); Self-confidence (10 items; _ =.76); Empathy (9 items; _ =.74); Future Orientation (6 items; _ =.84); and Community Orientation (4 items; _ =.88). All factors indicated high internal consistency.

A correlation analysis was conducted to determine the correlation of factors with overall GPA. The correlation coefficient, denoted by r, is a statistic that measures the degree of association between two quantitative variables. It is measured on a scale that varies from + 1 through 0 to - 1. A perfect correlation between two variables is expressed by either + 1. or -1. When one variable increases as the other increases the correlation is positive; when one increases as the other decreases it is negative. Complete absence of correlation is indicated by 0. The factor correlations with GPA are provided below:

Table 1
Factor Correlations with GPA

Factor Correlation Coefficient (r)

HW +.27***
RSP +.15*
SC +.15*
EM .00
FO .00
CO +.04


HW=Hard Work/Time Management
FO=Future Orientation
CO=Community Orientation

* p < .05
** p < .001
***p < .0001

The correlations between three factors and GPA were statistically significant: Hard Work/Time Management, Responsibility and Self Concept.

A multiple regression analysis was performed to determine the relative contribution of each of the factors to prediction of overall GPA. All items were entered simultaneously into the model to get the relative contribution of each while controlling for other factors in the model.

Table 2

Factor Parameter Estimate (_) P-value Partial R2

RV -11.4 .24 .005
HW 43.5 .0001 .07
RSP 14.6 .18 .005
SC 18.7 .03 .01
EM -14.1 .22 .01
FO -14.0 .02 .02
CO 1.3 .81 .00


HW=Hard Work/Time Management
FO=Future Orientation
CO=Community Orientation

The Hard Work/Time Management factor made a highly significant contribution to prediction of GPA. Self Concept also significantly contributed to GPA, with Responsibility making a marginal contribution to prediction of GPA. Future Orientation, on the other hand, was somewhat of a negative predictor or GPA.

The items that correlated with GPA but did not form part of the resulting factor structure were run in a regression analysis with the factors to see if there were questions that appeared to be explaining variance unique from the factors. The model explained variance was 26%. The following items added unique variance to the model:

I feel that circumstances have prevented me from being successful. -.16 (p = .007)

When I start a project I begin with the end in mind. +.25 (p = .0001)

I am always responding to the needs of others rather than my own. -.13 (p = .03)

I find it hard to believe that I will be able to graduate from college. -.22 (p = .0002)

My mind wanders when I try to study. -.26 (p = .0001)

These items appear to be important and will be included in future versions of the Student Success Scale.


The factor named Hard Work/Time Management was highly correlated with student achievement as measured by GPA. It is not surprising, in view of the work of Carol Dweck and others on entity theorists and incrementalists (Hong, Chiu, Dweck, Lin, & Wan, 1999). Students who are entity theorists believe that intelligence is a fixed trait and tend not to perform as well at academic tasks, particularly after negative feedback, in comparison to students who are incrementalists, who believe that high grades in school demonstrate hard work. Examples of items from this factor that were positively correlated with GPA were: “My teachers have felt that I work harder than most other students”; “I work harder than most other students that have been in my classes”; “I schedule my time”; and “I work hard at pursuing my goals.” Examples of items from this factor that were negatively correlated with GPA were: “I put off doing homework until the last minute”; and “I put things off that I don’t feel like doing.”

Responsibility was also a significant predictor of GPA. People who are irresponsible in a variety of ways are particularly unlikely to do well in college. Examples of items in this scale that negatively correlate with GPA are: “I turn in assignments late”; “I am always borrowing money from people”; “I use drugs to help improve my mood”; “I lose my temper with a friend”; “I think that I have a learning disability” and “I plan to improve my life by winning the lottery”.

Self Confidence was also a significant predictor of GPA. The item from this factor most strongly correlated with GPA, in a negative direction, was, “I am not as smart as most other college students”. Items positively correlated with GPA from this factor are: “I work well under pressure”; and “I try to live with integrity”.

The counter intuitive finding that Future Orientation is negatively correlated with GPA may have occurred because of lack of process in any of the statements in that factor. Examples of items in the Future Orientation factor are: “I know what I want my major to be”; “I have no idea what I want to do when I graduate from college”; “I can clearly see where I want to be five years from now.” The importance of process has some support in the research literature. In research by Lien Pham and Shelley Taylor (as cited in Aspinwall, L. G. & Taylor, S. 1997), 77 student participants took part in an experiment in which they received training in mental simulations, which they were then instructed to practice on their own for five minutes a day for five to seven days prior to the midterm exam. In the process-simulation condition, they were told to visualize themselves studying for the exam in a place such as the library, or at their desks at home and going over the lecture notes and reading the text chapters with the goal of achieving a grade of A. In the outcome-simulation condition they were told to see themselves having received the grade of A, beaming with joy and feeling proud of their accomplishment. A third group was a control group not given any mental simulation training or exercises to practice. All three groups were called the night before the exam, and asked about the number of hours they had studied, when they had started studying for the exam and their expected grade. The results indicated that the process-simulation group began studying for the exam earlier and spent more hours studying and received significantly higher grades on the exam than students who were in the outcome-simulation or the control group. What this study shows us is the importance of focusing on the steps to achieving our goals rather than on the goal itself. In the Future Orientation factor none of the items refer to the steps in the process of goal achievement.

Two factors that did not correlate with GPA at all were Empathy and Community Orientation. These factors are tapping a helping orientation toward others, but however laudatory this may be as an attribute for students to possess, it is unrelated to academic achievement and items on these factors are being dropped from the revised Student Success Scale.

The ultimate goal of this research is to use the Student Success Scale to screen students at risk of college failure based on non-intellectual psychological variables and to design an intervention to teach those skills to students at risk. Rollins and Zahm have written a book, Secrets of Success in College and Life, which has an extensive bibliography and incorporates the research basis of many of the psychological variables represented in the Student Success Scale.


Ames, C., & Archer, J. (1988). Achievement in the classroom: Student learning strategies and motivational responses. Journal of Educational Psychology, 80, 260–267.

Aspinwall, L. G., & Taylor, S. (1997). A stitch in time: Self-regulation and proactive coping. Psychological Bulletin, 121, 417–436.

Bandalos, D. L., Yates, K., & Thorndike-Christ, T. (1995). Effects of math self-concept, perceived self-efficacy, and attributions for failure and success on test anxiety. Journal of Educational Psychology, 87, 611–623.

Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman & Company.

Baumgardner, A. H. (1990). To know oneself is to like oneself: Self-certainty and self-affect. Journal of Personality and Social Psychology, 58, 1062-1072.

Britton, B. K., & Tesser, A. (1991). Effects of time-management practices on college grades. Journal of Educational Psychology, 83, 405–410.

Elliottt, E. S., & Dweck, C. S. (1988). Goals: An approach to motivation and achievement. Journal of Personality and Social Psychology, 54, 5-12.

Hong, Y., Chiu, C., Dweck, C. S., Lin, D. M. S., & Wan, W. (1999). Implicit theories, attributions, and coping: A meaning system approach. Journal of Personality and Social Psychology, 77, 588-599.

Kirshenbaum, D. S., Malett, S. D., & Humphrey, L. (1982). Specificity of planning and maintenance of self-control: A one year follow-up of a study improvement program. Behavior Therapy, 13, 232-242.

Panel to study “who-cares syndrome’ in high school seniors. (2000, June 16). The Providence Journal, p. 8.

Rollins, J. H. & Zahm, M. (1999). Secrets of success in college and life. Providence, RI: Authors.

Sandelands, L. E., Brockner, J., & Glynn, M. A. (1988). If at first you don’t succeed, try, try again. Effects of persistence performance contingencies, ego involvement and self esteem on task persistence. Journal of Applied Psychology, 73,208–218.

Student Retention and Graduation Rates. (1998, April). Rhode Island College: Providence, RI: Office of Institutional Research.

Copyright © 2002 Joan H. Rollins, Mary Zahm, Peter F. Merenda, and Gary Burkholder

Development of the Student Success Scale to Predict Non-Intellectual Factors Related to Student Retention and Achievement, Issues in Teaching and Learning, 1:1, 2002.

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