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Assessments can provide instructors and students with valuable information regarding student's level of knowledge and understanding, in order to improve both teaching and learning. In this study, we analyzed departmental assessment quizzes given to students at the start of Organic Chemistry 2, over an eight year period. This assessment quiz was designed to test students on core concepts from Organic Chemistry 1 that require the use of symbolic representations, such as drawing Lewis structures and using curved arrows. Using statistical analysis, it was found that students performed significantly lower than expected on the assessment quiz, and there was no significant difference in scores on the quiz over the eight years analyzed. Analysis of each individual question revealed that approximately one-third of the students made mistakes when converting a condensed formula or a chemical name to a chemical structure. For questions that involved more detailed answers such as drawing structures and showing simple mechanisms, approximately 95% of the students made errors.

The increase of exposure to toxic materials and hazardous chemicals is a major concern due to the adverse effect on human health. Among the major concerns of toxicologists is to determine acceptable levels of exposure to hazardous substances. Current approaches often evaluate each endpoint and stressor individually. We propose a novel method to simultaneously determine the Benchmark Dose Tolerable Region (BMDTR) for multiple endpoint and multiple stressor studies by adopting a Bayesian approach. A main concern while assessing the combined toxicological effect of a chemical mixture is the anticipated type of the combined action (i.e. synergistic or antagonistic); thus it was essential to account for interaction effects to handle this situation, imposing more challenges due to the non-linearity of the tolerable region. The proposed method will be evaluated using two approaches, the first one using the estimated value of the posterior median and the second approach using all MCMC samples from the posterior distribution. Furthermore, we propose a new method to determine the endpoint probabilities for each endpoint, which reflects the importance of each endpoint in helping determining the boundaries of the benchmark dose tolerable region (BMDTR). [ABSTRACT FROM AUTHOR]