Partial measurement invariance of beliefs about teaching for creativity across U.S. and Chinese educators

Author(s):  
Jen Katz‐Buonincontro ◽  
Richard Hass ◽  
Todd Kettler ◽  
Lisa Min Tang ◽  
Weiping Hu
2020 ◽  
Vol 122 (7) ◽  
pp. 1-22
Author(s):  
Jen Katz-Buonincontro ◽  
Richard W. Hass ◽  
Elaine Perignat

Background/Context Beliefs about teaching for creativity is a newer area of empirical investigation in education. Purpose The purpose of the quantitative study was to measure teachers’ domain-specific beliefs about teaching for creativity, piloted for the first time in this study, and compare these beliefs with domain-general beliefs about creativity. Subjects The study subjects were preservice and practicing teachers enrolled in bachelor's, master's, and doctoral (PhD and EdD) education programs within a private university located in the northeastern United States. Research Design This study surveyed a convenience sample of preservice and practicing teachers’ beliefs about creativity and their beliefs about teaching for creativity to examine their creative self-efficacy, growth and fixed creative mindsets, desirability of creativity for teaching success, and valuing creativity for student learning. Data Collection and Analysis A total of 149 students completed a measure on beliefs about creativity (domain-general) and beliefs about teaching for creativity (domain-specific). Exploratory factor analysis was conducted to examine potential newly aligned items and factors with a change in wording. Results The factor structure of the Fixed Creative Mindset items, Creative Self-Efficacy items and Desirability items was stable when rewording them to represent teacher perspectives. The Growth Creative Mindset items do not show the same stability, but two of the items seem to be related to a single factor, which is evidence that these items are functioning well. The newly worded Value items loaded on a separate factor, with only one cross loading. Educators rated themselves high in most areas, and low in the area of Fixed Creative Mindset. The results indicate that the Beliefs About Teaching for Creativity scales are reliable, with significant correlations among factors. Recommendations We propose research and policy recommendations to further examine the complex relationship between teachers’ beliefs about teaching for creativity and their pedagogical practices, especially in the area of growth and fixed creative mindset.


Assessment ◽  
2016 ◽  
Vol 25 (6) ◽  
pp. 744-758 ◽  
Author(s):  
Kevin M. King ◽  
Jeremy W. Luk ◽  
Katie Witkiewitz ◽  
Sarah Racz ◽  
Robert J. McMahon ◽  
...  

2021 ◽  
pp. 014662162110428
Author(s):  
Steffi Pohl ◽  
Daniel Schulze ◽  
Eric Stets

When measurement invariance does not hold, researchers aim for partial measurement invariance by identifying anchor items that are assumed to be measurement invariant. In this paper, we build on Bechger and Maris’s approach for identification of anchor items. Instead of identifying differential item functioning (DIF)-free items, they propose to identify different sets of items that are invariant in item parameters within the same item set. We extend their approach by an additional step in order to allow for identification of homogeneously functioning item sets. We evaluate the performance of the extended cluster approach under various conditions and compare its performance to that of previous approaches, that are the equal-mean difficulty (EMD) approach and the iterative forward approach. We show that the EMD and the iterative forward approaches perform well in conditions with balanced DIF or when DIF is small. In conditions with large and unbalanced DIF, they fail to recover the true group mean differences. With appropriate threshold settings, the cluster approach identified a cluster that resulted in unbiased mean difference estimates in all conditions. Compared to previous approaches, the cluster approach allows for a variety of different assumptions as well as for depicting the uncertainty in the results that stem from the choice of the assumption. Using a real data set, we illustrate how the assumptions of the previous approaches may be incorporated in the cluster approach and how the chosen assumption impacts the results.


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