Writing self-efficacy is a vital component to a students’ motivation and will to succeed towards writing. The measurement of writing self-efficacy over the past 40 years, despite its development, continues to largely be represented by Confirmatory Factor Analysis models that are limited due to their restricted item to factor constraints. These constraints, given prior literature and the theoretical understanding of self-efficacy, do not adequately model construct- relevant psychometric multidimensionality as a product of conceptual overlap or a hierarchical or general factor. Given this, the present study’s purpose was to examine the adapted Self-efficacy for Writing Scale (SEWS) for the presence of construct-relevant psychometric multidimensionality through a series of measurement model comparisons and person-centered approaches. Using a sample 1,466 8th, 9th, and 10th graders, a bifactor exploratory structural equation model was found to best represent the data and demonstrate that the SEWS exhibits both construct-relevant multidimensionality as a function of conceptual overlap and the presence of a hierarchical theme. Using factor scores derived from this model, latent profile analysis was conducted to further establish validity of the measurement model and examine how students disaggregate into groups based on their response trends of the SEWS. Three profiles emerged greatly differentiated by global writing self-efficacy, with obvious and substantively varying specific factor differences between profiles. Concurrent, divergent, and discriminant validity evidence was established through a series of analyses that assessed predictors and outcomes of the profiles (e.g. demographics, standardized writing assessments, grades). Theoretical and educator implications and avenues for future researcher were discussed.
Identifer | oai:union.ndltd.org:vcu.edu/oai:scholarscompass.vcu.edu:etd-7034 |
Date | 01 January 2019 |
Creators | DeBusk-Lane, Morgan |
Publisher | VCU Scholars Compass |
Source Sets | Virginia Commonwealth University |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Theses and Dissertations |
Rights | © The Author |
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