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An Explanatory Item Response Model Approach for Studying Latent Growth in Alphabet Knowledge

Wei, Xiaoxin
Format
Thesis/Dissertation; Online
Author
Wei, Xiaoxin
Advisor
Meyer, Patrick
Invernizzi, Marcia
Ryoo, Ji Hoon
Konold, Tim
Abstract
This study reviews growth modeling techniques, and then focused specifically on the use of explanatory item response models for studying growth while accounting for lack of time-invariance among item properties. Using this framework, results suggested there was a significant amount of growth in kindergarteners’ alphabet knowledge from fall to spring of a school year. Individual differences in latent ability and growth were large initially, but became considerably smaller by the end of the year. The difficulty of different item properties influenced examinee’s responses and the person properties have significant impact on the amount of latent growth. Implications were discussed from both substantive and methodological perspectives.
Published
University of Virginia, Curry School of Education, PHD (Doctor of Philosophy), 2015
Published Date
2015-06-04
Degree
PHD (Doctor of Philosophy)
Collection
Libra ETD Repository
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