Time Is On My Side . . . Or Is It?: Time of Day and Achievement in Asynchronous Learning Environments

Previous research suggests that the optimal time of day (TOD) for cognitive function for young adults occurs in the afternoon and evening times (Allen, et al. 2008; May, et al. 1993). The implication is college students may be more successful if they schedule classes and tests in the afternoon and evening times, but in asynchronous learning environments, “class” and tests take place at any TOD (or night) a student might choose. The problem is that there may be a disadvantage for students choosing to take tests at certain TOD. As educators, we need to be aware of potential barriers to student success and be prepared to offer guidance to students. This research study found a significant negative correlation between TOD and assessment scores on tests taken between 16:01 and 22:00 hours as measured in military time. While this study shows that academic performance on asynchronous assessments was high at 16:00 hours, student performance diminished significantly by 22:00 hours. When efforts were taken to mitigate the extraneous variables related to test complexity and individual academic achievement, the effect TOD had on assessment achievement during this time period was comparable to the effect of test complexity on that achievement. However, when analyzed using a small sub-set of the data neither GPA nor TOD could be used to predict student scores on tests taken between 16:01 and 22:00 hours. Finally, individual circadian arousal types (evening, morning and neutral) (Horne & Ostberg, 1976) and actual TOD students took tests were analyzed to determine if synchrony, the match between circadian arousal type and peak cognitive performance, existed. The synchrony effect could not be confirmed among morning type students taking this asynchronous online course, but evidence suggests that synchrony could have contributed to student success for evening types taking this asynchronous online courses. The implication of this study is that online instructors, instructional designers and students should consider TOD as a factor affecting achievement in asynchronous online courses. Results of this research are intended to propose further research into TOD effects in asynchronous online settings, and to offer guidance to online students as well as online instructors and instructional designers faced with setting deadlines and advising students on how to be successful when learning online

extRemes 2.0: An Extreme Value Analysis Package in R

This article describes the extreme value analysis (EVA) R package extRemes version 2.0, which is completely redesigned from previous versions. The functions primarily provide utilities for implementing univariate EVA, with a focus on weather and climate applications, including the incorporation of covariates, as well as some functionality for assessing bivariate tail dependence

Hidden in Plain Sight: Finding Safe Parking for Vehicle Residents

Vehicle residents are a growing part of homeless populations. This guide examines case studies of successful safe parking programs in Washington and California that mitigate harm to vehicle residents and offer support that can lift people out of poverty and into stable, permanent housing. This report synthesizes key lessons from successful Safe Parking Programs, specifically around operational, legal, and public relations or messaging issues

Microfluidic in vivo laser microsurgery screen for identification of compounds enhancing neural regeneration

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 41-42).Discovery of small molecules and novel mechanisms for enhancing neurite regeneration in animal models is significant for therapeutics of central nervous system injuries and neurodegenerative disorders. C. elegans is a widely studied model organisms due to their fully mapped neural network of 302 neurons and amenable genetics. Their small size and short life cycle allows for rapid studies to be conducted; however, after decades of use the manual methods of manipulation have still remained unchanged. This thesis details the development of automated, high-throughput optical and microfluidic technologies for screening C. elegans and demonstrates the production of a reliable system for screening over ten thousand animals. Using the screening system, femtosecond laser microsurgery was performed on thousands of animals followed by incubation in compounds from a chemical library. The screens revealed several high-scoring drug candidates that enhance regeneration after laser microsurgery of C. elegans mechanosensory neurons.by Cody Lee Gilleland.S.M

Non-stationarity in peaks-over-threshold river flows:a regional random effects model

Under the influence of local- and large-scale climatological processes, extreme river flow events often show long-term trends, seasonality, inter-year variability and other characteristics of temporal non-stationarity. Properly accounting for this non-stationarity is vital for making accurate predictions of future floods. In this paper, a regional model based on the generalised Pareto distribution is developed for peaks-over-threshold river flow data sets when the event sizes are non-stationary. If observations are non-stationary and covariates are available then extreme value (semi-)parametric regression models may be used. Unfortunately the necessary covariates are rarely observed and, if they are, it is often not clear which process, or combination of processes, to include in the model. Within the statistical literature, latent process (or random effects) models are often used in such scenarios. We develop a regional time-varying random effects model which allows identification of temporal non-stationarity in event sizes by pooling information across all sites in a spatially homogeneous region. The proposed model, which is an instance of a Bayesian hierarchical model, can be used to predict both unconditional extreme events such as the m-year maximum, as well as extreme events that condition on being in a given year. The estimated random effects may also tell us about likely candidates for the climatological processes which cause non-stationarity in the flood process. The model is applied to UK flood data from 817 stations spread across 81 hydrometric regions

Spatio-temporal models for large-scale indicators of extreme weather

The changing global climate has sparked an interest in how these changes are affecting the intensity and frequency of extreme weather events such as thunderstorms and tornadoes because these extreme events pose a significant threat to life, property, and economic stability. This article uses and evaluates several spatio-temporal statistical extreme value models to model extreme weather from reanalysis data observed across the continental United States and Mexico. The models find that the intensity of extreme weather is particularly high for the central United States. Additionally, the intensity of extreme weather is increasing over time but the amount of increase may not be practically significant