Researchers have a long-standing interest in better understanding why some students avoid challenging academic course work at the risk of harming their academic standing, whereas others are willing to pursue these types of challenges. The Academic Hardiness Scale (AHS) was developed to better understand characteristics that may differentiate these two types of students. Although preliminary findings provided support for the initial version of the AHS, the measure exhibited only good to marginal coefficient alphas and limited discriminant validity. The present investigation represents the second phase of measurement development for the AHS. The study was designed to evaluate the factor structure; internal consistency reliability; discriminant, convergent, and concurrent validity; and testretest reliability of the Revised Academic Hardiness Scale (RAHS). Results from this study identified a three-component measure that has very good basic psychometric properties. The RAHS is a significant improvement over its parent instrument.
Anaya, G. (1999). Accuracy of self-reported test scores. College and University, 75(2), 13-19.
2.
Bandura, A. (1991). Social cognitive theory of self-regulation. Organizational Behavior and Human Decision Processes, 50, 248-287.
3.
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.
4.
Becker, B. E., & Luthar, S. S. (2002). Social-emotional factors affecting achievement outcomes among disadvantaged students: Closing the achievement gap. Educational Psychologist, 37(4), 197-214.
5.
Benishek, L. A., & Lopez, F. G. (2001). Development and initial validation of a measure of academic hardiness. Journal of Career Assessment, 9(4), 333-352.
6.
Bouffard, T., Vezeau, C., & Bordeleau, L. (1998). A developmental study of the relation between combined learning and performance goals and students’ self-regulated learning. British Journal of Educational Psychology, 68, 309-310.
7.
Borkowski, J. G., & Thorpe, P. K. (1994). Self-regulation and motivation: A life-span perspective on underachievement. In D. H. Schunk & B. J. Zimmerman (Eds.), Self-regulation of learning and performance: Issues and educational applications (pp. 45-73). Hillsdale, NJ: Lawrence Erlbaum.
8.
Bryant, F. B., & Yarnold, P. R. (1995). Principal components analysis and exploratory and confirmatory factor analysis. In L. G. Grimm & P. R. Yarnold (Eds.), Reading and understanding multivariate statistics (pp. 99-136). Washington, DC: American Psychological Association.
9.
Campbell, D. T., & Fiske, D. (1959). Convergent and discriminant validation by the multitraitmultimethod matrix. Psychological Bulletin, 56, 81-105.
10.
Chamorro-Premuzic, T., & Furnham, A. (2003). Personality predicts academic performance: Evidence from two longitudinal university samples. Personality and Individual Differences, 37, 319-338.
11.
Clark, L. A., & Watson, D. (1995). Constructing validity: Basic issues in objective scale development. Psychological Assessment, 7(3), 309-319.
12.
Clifford, M. M., & Chou, F. C. (1991). Effects of payoff and task context on academic risk-taking. Journal of Educational Psychology, 83, 499-507.
13.
Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155-159.
14.
Costa, P. T., Jr., & McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO-PI-R) and the NEO Five-Factor Inventory (NEO-FFI). Odessa, FL: Psychological Assessment Resources.
15.
DeVellis, R. F. (2003). Scale development: Theory and applications (2nd ed.). Thousand Oaks, CA: Sage.
16.
Diseth, A. (2002). Personality approaches to learning as predictors of academic achievement. European Journal of Personality, 17, 143-155.
17.
Dunteman, G. H. (1989). Principal components analysis. Newbury Park, NJ: Sage.
18.
Dweck, C. S. (2002). Messages that motivate: How praise molds students’ beliefs, motivation, and performance (in surprising ways). In J. Aronson (Ed.), Improving academic achievement (pp. 37-60). San Diego, CA: Academic Press.
19.
Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95, 256-273.
20.
Elliot, A., & Harackiewicz, J. (1996). Approach and avoidance achievement goals and intrinsic motivation: A mediational analysis. Journal of Personality and Social Psychology, 70, 461-475.
21.
Floyd, F. J., & Widaman, K. F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological Assessment, 7, 286-299.
22.
Funk, S. C. (1992). Hardiness: A review of theory and research. Health Psychology, 11, 335-345.
23.
Funk, S. C., & Houston, B. K. (1987). A critical analysis of hardiness scales validity and utility. Journal of Personality and Social Psychology, 53, 572-578.
24.
George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference, 11.0 update (4th ed.). New York: Allyn & Bacon.
25.
Khoshaba, D. M., & Maddi, S. R. (1999). Early experiences in hardiness development. Consulting Psychology Journal: Practice and Research, 51(2), 106-116.
26.
Kobasa, S. C. (1982). The hardy personality: Toward a social psychology of stress and health. In G. S. Sanders & J. Suls (Eds.), Social psychology of health and illness (pp. 3-32). Hillsdale, NJ: Lawrence Erlbaum.
27.
Lopez, F. G., & Lent, R. W. (1992). Sources of mathematics self-efficacy in high school students. Career Development Quarterly, 41, 3-12.
28.
Marsh, H. W., Byrne, B. M., & Yeung, A. S. (1999). Causal ordering of academic self-concept and achievement: Reanalysis of a pioneering study and revised recommendations. Educational Psychologist, 34, 155-167.
29.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York: McGraw Hill.
30.
Ouellette, S. C. (1993). Inquiries into hardiness. In L. Goldberger & S. Breznitz (Eds.), Handbook of stress: Theoretical and clinical aspects (pp. 77-100). New York: Free Press.
31.
Reynolds, W. M. (1988). Measurement of academic self-concept in college students. Journal of Personality Assessment, 52, 223-240.
32.
Ross, S. R., Canada, K. E., & Rausch, M. K. (2002). Self-handicapping and the five factor model of personality: Mediation between neuroticism and conscientiousness. Personality and Individual Differences, 32, 1173-1184.
33.
Ross, S. R., Stewart, J., Mugge, M., & Fultz, B. (2001). The imposter phenomenon, achievement dispositions, and the five factor model. Personality and Individual Differences, 31, 1347-1355.
34.
Sinclair, R. R., & Tetrick, L. E. (2000). Implications of item wording for hardiness structure, relation with neuroticism, and stress buffering. Journal of Research on Personality, 34, 1-25.
35.
Snelbecker, G. E., McConlogue, T., & Teitelbaum, J. M. (2001). Cognitive Risk Tolerance Scale: Research Edition. Wyndmoor, PA: M*A*T*C*H.
36.
Stevens, J. (1992). Applied multivariate statistics for the social sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
37.
Tabachnick, B. G., & Fidell, L. S. (1996). Using multivariate statistics (3rd ed.). New York: Harper Collins College.
38.
Teitelbaum, J. M., & McConlogue, T. (2001). [Cognitive risk tolerance: Pilot study]. Unpublished raw data.
39.
Velting, D. M. (1999). Personality and negative expectancies: Trait structure of the Beck Hopelessness Scale. Personality and Individual Differences, 26, 913-921.
40.
Wendorf, C. A. (2002). Grade point average and changes in (great) grade expectations. Teaching of Psychology, 29(2), 136-138.
41.
Zhang, L. (2003). Does the Big Five predict learning approaches?Personality and Individual Differences, 34, 1431-1446.
