Assessing need for cognition in early adolescence: Validation of a german adaption of the cacioppo/petty scale

European Journal of Psychological Assessment

Volumn 30, Issue 1, 2014, Pages 65-72

  Preckel, Franzis ^a  

^a UNIVERSITY OF TRIER   (Germany)

Author keywords

Goals; Item wording; Method effects; Need for cognition

Indexed keywords

EID: 84892634016     PISSN: 10155759     EISSN: 21512426     Source Type: Journal    
DOI: 10.1027/1015-5759/a000170     Document Type: Article

References (25)

1. Bless, H., Wänke, M., Bohner, G., Fellhauer, R. F., & Schwartz, N. (1994). Need for Cognition: Eine Skala zur Erfassung von Engagement und Freude bei Denkaufgaben [Need for Cognition: A scale for the assessment of engagement and enjoyment of thinking]. Zeitschrift für Sozialpsychologie, 25, 147-154.
2. Bors, D.A., Vigneau, F., & Lalande, F. (2006).Measuring the need for cognition: Itempolarity, dimensionality and the relation with ability. Personality and Individual Differences, 40, 819-828.
3. Cacioppo, J.T., & Petty, R.E. (1982).The need for cognition. Journal of Personality and Social Psychology, 42, 116-131.
4. Cacioppo, J.T., Petty, R.E., Feinstein, J.A., & Jarvis, B. G. (1996). Dispositional differences in cognitive motivation: The life and times of individuals varying in need for cognition. Psychological Bulletin, 119, 197-253.
5. Day, E. A., Espejo, J., Kowollik, V., Boatman, P. R., & McEntire, L. (2007). Modeling the links between need for cognition and the acquisition of a complex skill. Personality and Individual Differences, 42, 201-212.
6. Elliot, A. J., & McGregor, H.A. (2001). A 2 × 2 achievement goal framework. Journal of Personality and Social Psychology, 80, 501-519.
7. Enders, C. K., & Tofighi, D. (2007). Centering predictor variables in cross-sectional multilevel models: A new look at an old issue. Psychological Methods, 12, 121-138.
8. Forsterlee, R., & Ho, R. (1999). An examination of the short form of the need for cognition scale applied in an Australian sample. Educational and Psychological Measurement, 59, 471-480.
9. Ginet, A., & Py, J. (2000). Le besoin de cognition: Une échelle française pour enfants et ses conséquences au plan sociocognitif [The need for cognition: A French scale for children]. L'Année Psychologique, 100, 585-627.
10. Heller, K.A., & Perleth, C. (2000). Kognitiver Fähigkeitstest für 4. bis 12. Klassen, Revision (KFT 4-12+R) [Cognitive ability test for class level 4 to 12, revised version]. Göttingen: Hogrefe.
11. Inzlicht, M., & Schmader, T. (2011). Stereotype threat: Theory, process, and application. New York: Oxford University Press.
12. McArdle, J. J., & Grimm, K. J. (2010). Five steps in latent curve and latent change score modeling with longitudinal data. In K. van Montfort, A. Satorra, & J.H. Oud (Eds.), Longitudinal research with latent variables (pp. 245-273). Berlin, Germany: Springer-Verlag.
13. Meredith, W., & Horn, J. (2001). The role of factorial invariance in modeling growth and change. In L.M. Collins&A.G. Sayer (Eds.), New methods for the analysis of change (pp. 203-240). Washington, DC: American Psychological Association.
14. Mussel, P. (2010). Epistemic curiosity and related constructs: Lacking evidence of discriminant validity. Personality and Individual Differences, 49, 506-510.
15. Muthén, L. K., & Muthén, B. O. (1998-2010). Mplus Version 6.1 [statistical software]. Los Angeles, CA: Muthén & Muthén.
16. Pekrun, R., Hofe, R. v., Blum, W., Goetz, T., Wartha, S., Frenzel, A., & Jullien, S. (2006). Projekt zur Analyse der Leistungsentwicklung in Mathematik (PALMA) - Entwicklungsverläufe, Schülervoraussetzungen und Kontextbedingungen von Mathematikleistungen in der Sekundarstufe I [Project for the longitudinal analysis of mathematics achievement (PALMA): Development, predictors, and context factors ofmath achievement in secondary school]. In M. Prenzel & L. Allolio-Näcke (Eds.), Untersuchungen zurBildungsqualität von Schule. Abschlussbericht desDFGSchwerpunktprogramms (pp. 21-53). Münster, Germany: Waxmann.
17. Podsakoff, P. M., MacKenzie, S. M., Lee, J., & Podsakoff, N. P. (2003). Common method variance in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88, 879-903.
18. Preckel, F., Holling, H., & Vock, M. (2006). Academic underachievement: Relationship with cognitive motivation, achievement motivation, and conscientiousness. Psychology in the Schools, 43, 401-411.
19. Preckel, F., Lipnevich, A. A., Boehme, K., Brandner, L., Georgi, K., Könen, T., . . . Roberts, R.D. (2012). Morningness-eveningness and educational outcomes: The lark has an advantage over the owl at high school. British Journal of Educational Psychology. Advance online publication. doi 10.1111/j.2044- 8279.2011.02059.x
20. Quilty, L. C., Oakman, J. M., & Risko, E. (2006). Correlates of the Rosenberg self-esteem scale method effects. Structural Equation Modeling, 13, 99-117.
21. Rauch, W.A., Schweizer K., & Moosbrugger, H. (2007). Method effects due to social desirability as a parsimonious explanation of the deviation from unidimensionality in LOT-R scores. Personality and Individual Differences, 42, 1597-1607.
22. Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of university students' academic performance: A systematic review and meta-analysis. Psychological Bulletin, 138, 35-387.
23. Schweizer, K. (2010). Some guidelines concerning the modeling of traits and abilities in test construction. European Journal of Psychological Assessment, 26, 1-2.
24. Souvignier, E., Trenk-Hinterberger, I., Adam-Schwebe, S., & Gold, A. (2008). Frankfurter Leseverständnistest für 5. und 6. Klassen [Frankfurt test of reading comprehension for grades 5 and 6]. Göttingen: Hogrefe.
25. Thorndike, R. L., & Hagen, E. (1971). Cognitive abilities test. Boston: Houghton-Mifflin.