Exploring predictors of impact of school-based management in rural Mexico: Do student engagement, teacher attitudes and parent involvement predict better academic outcomes?. (March 2018)

• Record Type: Journal Article
• Authors: Mejia, Anilena; Filus, Ania
• Is Part Of: International journal of educational research. Volume 88(2018)
• Page Start: 95
• Page End: 108
• Publication Date: 2018-03
• Subjects: School-based management -- Apoyo a la Gestion Escolar -- Predictors -- Multilevel latent growth modeling -- Mexico; Education -- Evaluation -- Periodicals; Curriculum evaluation -- Periodicals; Education -- Periodicals; Program Evaluation -- Periodicals; Éducation -- Évaluation -- Périodiques; Programmes d'études -- Evaluation -- Périodiques; Éducation -- Recherche -- Périodiques; Curriculum evaluation; Education -- Evaluation; Periodicals; 370.72
• DOI: 10.1016/j.ijer.2018.01.010
• Languages: English
• ISSNs: 0883-0355

Abstract

Highlights: We examined the effects of a school-based management (SBM) program in rural Mexico. Providing double vs. standard funding had the same effects on academic outcomes. Reductions in school absenteeism and homework time predicted students' outcomes. In future other predictors of change due to SBM programs should be investigated. Abstract: School-based management (SBM) programs are effective for improving academic performance. However, few studies have examined factors predicting their effectiveness. We analyzed data from a randomized experiment conducted in Mexico designed to test effects of SBM with double resources as compared to standard resources. Results indicated that regardless of the amount of money received, students' standardized scores in mathematics and Spanish improved over time. In addition, the results showed that for all schools a reduction in self-reported student absenteeism predicted improvements in student academic scores while a reduction in self-reported homework time predicted a decrease in academic scores over time. Future studies should explore a wider range of potential predictors.