Session Information
09 SES 12 C, Assessing Students' Competencies and Attitudes
Paper Session
Contribution
It has become a widespread consensus that creativity is an important facet of human personality, which should be fostered in schools. Creativity can be regarded as a skill to solve problems or tasks in an unusual but inventive, efficient or even original way. It therefore can be a meaningful prerequisite for learning processes (Hattie, 2009; Runco, 2004). In German-speaking countries, fostering creativity is even considered as an educational goal (Serve, 2000), but still there is a research gap on investigating creativity and its predictors. It is assumed that there are multiple determinants: In addition to individual factors like motivation, intelligence or certain personality traits (e.g. openness, unconventionality, perseverance or curiosity), whether a person is capable of solving problems in an unconventional way also depends on domain specific skills. Beyond these individual factors, external conditions can determine whether somebody acts creatively or not (Cropley, 1991; Urban, 1993).
In this context, the question remains of how to foster creativity in school and in part, this is due to an ongoing challenge in assessing this heterogeneous construct. Thus, knowledge about how creativity develops over age could further be helpful in gaining an understanding of how to foster creativity.
When investigating developmental courses, it is a necessity to check for measurement invariance to assure that repeated measures are comparable over time (Geiser, 2010). Meredith (1993) proposed different stages of invariance ranging from configural invariance (factor patterns are the same), over metric or weakfactorial invariance (factor loadings are the same) up to strongfactorial invariance (in addition to the same patterns and loadings, here the intercepts are the same). Finally, strictfactorial invariance means that in addition to all foregoing restrictions the residual variances are the same as well. The more restrictions are fulfilled, the higher the data quality is. If restrictions for single items are loosened, it leads to particular invariance on the corresponding stage.
As creativity is a heterogeneous construct that is determined by several conditions, it depicts a particular challenge to a) assess it in a global but still economic way and b) to reach sufficient data quality for further resilient empirical analyses. Both aspects reflect important prerequisites in order to pursue empirical studies on how creativity develops.
Within the present study, the Test for Creative Thinking-Drawing Production (TCT-DP; Urban & Jellen, 1996), a relatively well-proven instrument to assess creativity in a global but still economic way shall first be presented. The test provides sufficient data quality in the sense of test-retest-reliability (c.f. ibid.), inter-rater-reliability and intern consistency for elementary school children (.64<α>.73; Theurer, Berner & Lipowsky, in press) but further analyses concerning reliability or validity have not been conducted yet. Hence, an innovative approach of scaling these data was undertaken with the aim of reaching measurement invariance for creativity development from first to fourth grade. Developmental courses as measured by the traditional scaling procedure resp. the new scaling approach are compared in order to check whether the manipulation of the original instrument is acceptable.
Method
Expected Outcomes
References
Cropley, A. J. (1991). Unterricht ohne Schablone: Wege zur Kreativität. [Class Without Former Plate: Tracks Toward creativity.] München: Ehrenwirth. Greb, K., Faust, G., & Lipowsky, F. (2007). Projekt PERLE: Persönlichkeits- und Lernentwicklung von Grundschulkindern [The PERLE-Project: Personality and Learning Development of Elementary School Children]. Diskurs Kindheits- und Jugendforschung, 2(1), 100–104. Geiser, C. (2010). Datenanalyse mit Mplus. Eine anwendungsorientierte Einführung [Analyzing Data With Mplus. An Application-Oriented Introduction]. Wiesbaden: VS Verlag für Sozialwissenschaften. Hattie, J. (2009). Visible Learning: A Synthesis of Over 800 Meta-Analyses Relating to Achievement. Routledge: London & New York. Meredith, W. (1993). Measurement Invariance, Factor Analysis and Factorial Invariance. Psychometrika, 58(4), 525–543. Runco, M. A. (2004). Creativity. Annual Review of Psychology, (55), 657–687. Serve, H. J. (2000). Fundamente (grund‐)schulpädagogischer Kreativitätsförderung. [Basements of Fostering Creativity in (Elementary) School.] In H. J. Serve (Ed.), Kreativitätsförderung [Fostering Creativity] (pp. 10–26). Baltmannsweiler: Schneider‐Verlag Hohengehren. Theurer, C., Berner, N., & Lipowsky, F. (in press). Die Entwicklung der Kreativität im Grundschulalter: Zur Messung der Kreativität im PERLE-Projekt. [Creativity Development During Elementary School: On the Measurement of Creativity Within the PERLE-Project.], Journal for educational research online. Theurer, C., Kastens, C., Berner, N. & Lipowsky, F. (2011). Die Kreativität im frühen Grundschulalter und ihr Zusammenhang mit der Intelligenz. [Creativity in Early Elementary School and Its Relationship Towards Intelligence.] Zeitschrift für Grundschulforschung, 4(2), 83─97. Urban, K. K. & Jellen, H. G. (1996). Test for Creative Thinking - Drawing Production (TCT-DP). Lisse, Netherlands: Swets & Zeitlinger. Urban, K. K. (1993). Neuere Entwicklungen in der Kreativitätsforschung. [Recent Trends in Creativity Research.] Psychologie in Erziehung und Unterricht, 40, 161–181.
Search the ECER Programme
- Search for keywords and phrases in "Text Search"
- Restrict in which part of the abstracts to search in "Where to search"
- Search for authors and in the respective field.
- For planning your conference attendance you may want to use the conference app, which will be issued some weeks before the conference
- If you are a session chair, best look up your chairing duties in the conference system (Conftool) or the app.