Metacognitive Exam Preparation Assignments in an Introductory Biology Course Improve Exam Scores for Lower ACT Students Compared with Assignments that Focus on Terms.

Preparing for exams in introductory biology classrooms is a complex metacognitive task. Focusing on lower achieving students (those with entering ACT scores below the median at our institution), we compared the effect of two different assignments distributed ahead of exams by dividing classes in half to receive either terms to define or open-ended metacognitive questions. Completing metacognitive assignments resulted in moderately higher exam scores for students on the second and third exams.

Naomi: a new modelling tool for estimating HIV epidemic indicators at the district level in sub-Saharan Africa.

Introduction: HIV planning requires granular estimates for the number of people living with HIV (PLHIV), antiretroviral treatment (ART) coverage and unmet need, and new HIV infections by district, or equivalent subnational administrative level. We developed a Bayesian small-area estimation model, called Naomi, to estimate these quantities stratified by subnational administrative units, sex, and five-year age groups.

Methods: Small-area regressions for HIV prevalence, ART coverage and HIV incidence were jointly calibrated using subnational household survey data on all three indicators, routine antenatal service delivery data on HIV prevalence and ART coverage among pregnant women, and service delivery data on the number of PLHIV receiving ART.

Small Area Estimation for Disease Prevalence Mapping.

Small area estimation (SAE) entails estimating characteristics of interest for domains, often geographical areas, in which there may be few or no samples available. SAE has a long history and a wide variety of methods have been suggested, from a bewildering range of philosophical standpoints. We describe design-based and model-based approaches and models that are specified at the area-level and at the unit-level, focusing on health applications and fully Bayesian spatial models.