Evaluating academic outcomes of Head Start: an application of general growth mixture modeling |
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| Institution: | 1. Institute for Social Science Research, Office 403, Cycad Building, Long Pocket Precent, The University of Queensland, 4072, Australia;2. The University of Queensland Centre for Clinical Research, University of Queensland, Brisbane, Australia;3. Metro North Mental Health, Royal Brisbane and Women''s Hospital, Brisbane, Australia;4. School of Public Health, University of Queensland, Brisbane, Australia;5. School of Social Science and Public Health, University of Queensland, Brisbane, Australia;1. University of Ljubljana, Faculty of Electrical Engineering, Tr?a?ka 25, 1000 Ljubljana, Slovenia;2. Sensum, Computer Vision Systems, Tehnolo?ki park 21, 1000 Ljubljana, Slovenia |
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| Abstract: | This study intends to illustrate the utility of general growth mixture modeling (GGMM) for evaluation of early childhood education programs, using a sample of children with Head Start experience. In the first analysis of this study growth mixture modeling (GMM) found that children with Head Start experience had two distinct growth patterns. In the second analysis of this study general growth mixture modeling found that children with two or more years of program participation did not have faster achievement growth, on average, than children with only one year of program participation. This study also found that a gender gap in mathematics and an income gap in reading and mathematics were exclusively exhibited by the children with no preschool experience. Therefore, it was concluded that the Head Start program may be reducing both a gender gap in mathematics and an income gap in reading and mathematics. |
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