Improving and Expanding the Teacher Training Sub-Activity Sample Clauses

Improving and Expanding the Teacher Training Sub-Activity. The CBA model for the Teacher Training Sub-Activity is based on the Project’s logic of producing higher quality teachers at the lower secondary level by improving pre-service teacher training, such that it is more closely aligned with the school curriculum and focuses more on key pedagogical and practical training to prepare teachers for the job. Additionally, the creation of two satellite campuses in Gbêkê and San Xxxxx will increase the flow of higher quality teachers into the education system. The counterfactual (without Project scenario) adopted is that the schools would continue to have teachers with the current (lower) skillset. It is important to note that in this sub-activity the teachers are participants in an MCC-funded intervention, but their eventual students are the potential beneficiaries. Therefore, teachers are seen as similar to an improved input to the education system that will produce a greater quality of education for their students. The CBA model aims to include all anticipated costs, whether incurred with funding from MCC, other donors or the Government. The economic analysis includes two main benefit streams:  Improved student learning outcomes as a result of increased teacher knowledge of curriculum material and methods for teaching that material.  Increased future earnings resulting from improved student learning outcomes. The most likely ERR for the Teacher Training Sub-Activity is 21.6%. However, the available literature and data limits our certainty in quantifying and monetizing the above mentioned benefit streams. The most influential parameter on the variance of the ERR calculation is the average increase in future incomes, followed by the average effect size on student learning outcomes. Although there is a demonstrated linkage between teacher training and improvement in student learning outcomes, the literature on evaluations of pre-service teacher training programs is virtually non-existent, and the exact relationship between improvements in student learning and higher wages is unclear. Uncertainty is assessed through completing sensitivity analysis based on a modeling technique known as Monte Carlo simulations. The results indicate that the 80% confidence interval for the ERR is from 16% to 26%, and there is a 99% probability that the ERR is above 10%, the typical threshold applied by MCC. Additionally, a key driver of the CBA model is the flow of student teachers through the ENS training centers. Unlike one-time, in-se...
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