City Unviersity of New York, College of Staten Island (UNITED STATES)
About this paper:
Appears in: ICERI2010 Proceedings
Publication year: 2010
Pages: 136-137 (abstract only)
ISBN: 978-84-614-2439-9
ISSN: 2340-1095
Conference name: 3rd International Conference of Education, Research and Innovation
Dates: 15-17 November, 2010
Location: Madrid, Spain
It is generally believed that resilience—definable as being inordinately unaffected by stress and/or barriers—may be an important ingredient in academic success (e.g., Bauman, 2002). Although there are a handful of instruments that measure resilience (e.g., Ahren, Kiehl, Sole, and Byers, 2006), we have found none designed to measure the ability of young adult students to overcome stressors to succeed academically. Thus, we designed and tested an academic resilience inventory (ARI), designed to represent various domains of resilience.

1. Predictive Validity
Cognitive ability was operationalized as scores on the Sternberg Triarchic Abilities Test–Modified: Abbreviated Version (STAT-M, Sternberg, 1991). Since the components of academic resilience that are unrelated to cognitive ability may not be much more than aspects of well-known personality constructs; operationalized as scores on the Big Five (Goldberg, 1990) personality scores were added to the model.

Resilient individuals appear to demonstrate strong motivation to succeed (e.g., Rutter, 1981). Therefore, motivation was added to the model as well, operationalized as scores on Dishman, Ickes, and Morgan’s (1980) Self-Motivation Inventory (SMI).

Respondents were 272 (185 female) college students. A linear regression model with cumulative GPA as the criterion was significant (F11, 111=2.95, p<.05). More importantly, the regression weight for the standardized ARI scores (β=.24) was significant; the R² for a model without ARI scores was .20, and R² for the model with the ARI scores was .24 (F1,100=5.64, p<.05).

Adding ARI to models predicting either present or cumulative GPA significantly improved the predictive ability of these models. That which the ARI measures makes a unique contribution to our understanding of what contributes to academic success in college.

2. Construct Validity
Tests of construct validity centered on the ability of the ARI to predict academic success when aspects of stressors and/or life barriers are added to the model. Participants supplied (a) responses to the ARI, (b) responses to a measure of stressful life events (measured as Miller and Rahe’s (1997) Recent Life Changes Questionnaire, RLCQ), and (c) economic status.

A total of 115 (78 female) college students participated. With cumulative GPA as the criterion, the overall model was significant (F6,104=2.91, R²=.15, p<.05). The ARI (β=.17, t1=1.95, p<.05) and economic status (β=.21, t1=2.18, p<.05) parameters were also significant. Note that although ARI scores moderated the relation between RLCQ scores and GPA, ARI and RLCQ scores were not significantly correlated. In other words, it appears that the effect of the academic resilience measured by the ARI is to moderate the relationship between stressors and GPA and not so much to influence (or be influenced by) stressors directly. This combination of results (i.e., a significant ARI x RLCQ interaction and a non-significant ARI-RLCQ correlation) lends support to Werner et al.’s (Werner, 1984; Werner and Smith, 1992; 1982) hypothesis that stressors appear largely not to affect resilience: Experiencing more stressors does not make one more resilient.

These results indicate that resilience is a significant contributor to academic success for typical college students, and one that should—and now can—be assessed. Knowledge of students’ level of academically resilience can help counselors better advise them and know better how to support them.
Academic resilience, stress, Emmy Werner, psychometrics.