Search

The authors' institution exceeded the Texas Science of Teaching Reading (STR) exam's passing rate of 86.6% for the 2021-2022 academic year. The authors think this success was largely due to conducting an analysis of test questions and helping preservice teachers better prepare for the exam. The authors helped preservice teachers supplement the literacy knowledge they needed for their classrooms with test-taking strategies. Six strategies are presented to analyze the STR exam questions. These help preservice teachers analyze the exam questions by decoding the more common scenario-based ones which we categorized as these question types: 1) A teacher wants to do something; 2) Teachers' strategy/activity shows they understand something; 3) Students do this…what's the next step; 4) Why this activity; 5) Tiered vocabulary; 6) What does the assessment tell? The final strategy describes a method for organizing the constructed response analysis.

Abstract: Many studies have found cross-sectional associations between characteristics of the neighborhood built environment and physical activity (PA) behavior. However, most are based on self-reported PA, which is known to result in overestimation of PA and differential misclassification by demographic and biological characteristics. Cardiorespiratory fitness (CRF) is an objective marker of PA because it is primarily determined by PA. Furthermore, it is causally related to long-term health outcomes. Therefore, analyses of the association between CRF and built environment could strengthen arguments for the importance of built environment influences on health. We examined the association between neighborhood walkability and CRF and body-mass index (BMI). This cross-sectional analysis included 16,543 adults (5017 women, 11,526 men) aged 18–90 years with home addresses in Texas who had a comprehensive clinical examination between 1987 and 2005. Outcomes included CRF from total duration on a maximal exercise treadmill test and measured BMI. Three neighborhood walkability factors emerged from principal components analyses of block-group measures derived from the U.S. Census. In multilevel adjusted analyses, the neighborhood walkability factors were significantly associated with CRF and BMI among men and women in the expected direction. An interaction between one of the neighborhood factors and age was also observed. The interaction suggested that living in neighborhoods with older homes and with residents traveling shorter distances to work was more strongly positively associated with CRF among younger adults and more strongly negatively associated with BMI among older adults. In conclusion, neighborhood characteristics hypothesized to support more PA and less driving were associated with higher levels of CRF and lower BMI. Demonstration of an association between built environment characteristics and CRF is a significant advance over past studies based on self-reported PA. Nevertheless, stronger causal evidence depends on more robust study designs and sophisticated measures of the environment, behavior, and their physiological consequences. [Copyright &y& Elsevier]