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In the U.S., only 38 of every 100 ninth graders enroll in college; of these 38, only 18 complete bachelors' degrees within six years. Asynchronous learning networks (ALN)--asynchronous, highly interactive, instructor-led, resource-rich, cohort-based learning--can yield high success rates. Growing demand for online education and the expectation among higher education leaders that ALN learning outcomes will exceed face to face outcomes reflect belief in ALN's power to engage learners. Sloan-C's body of research confirms that ALN is especially suited for the anytime, anywhere, affordable access that is responsive to learners in a knowledge society. In fact, the original principles of ALN are the same principles that characterize ALN programs that have high student success rates. This paper includes vignettes from two and four-year ALN programs that have used these principles to achieve high success rates. (Contains 3 figures and 3 tables.)

The concept of sharing, enabled by emerging technologies, is playing an increasingly important role in contributing to a transformation toward more sustainable transportation. This study aimed to contribute to the growing body of literature on on-demand transportation services, with a particular emphasis on sharing or pooling a ride when using services such as transportation-network companies (TNCs) and microtransit. The study conducted a shared mobility survey of over 2,500 respondents from selected locales across Texas—ranging from large urban areas to small cities and rural areas. We analyzed the survey data in detail using extensive statistical analysis and inferential techniques and adopted an analysis approach toward implementation-oriented research to address the gap between theory and practice. Demographic, as well as geographic and built-environment, factors were found to play an important role in determining whether users will opt for a shared or pooled service and/or how they perceive these alternatives. The findings highlight the importance of improving safety and security, increasing awareness of the benefits of ride-sharing, and designing appropriate policy measures to promote sustainable mobility. We identified potential operational improvements, government policies, and employer programs to improve shared-ride services and encourage their use, such as reducing uncertainty in shared rides and minimizing inconvenience for passengers. A critical finding was the need to prioritize operational improvements in shared-ride trips over solely relying on financial incentives to induce behavior change. Enhanced public awareness and education were also determined to be crucial regardless of the nature of improvements, policies, or programs that are implemented. [ABSTRACT FROM AUTHOR]

Encouraging the use of nonmotorized modes of transportation is a goal at the intersection of public health, environment, and transportation, given active transportation's numerous benefits to individuals and communities. However, increased use of nonmotorized modes can also bring increased pedestrian–vehicle and bicycle–vehicle crashes. About 4,000 fatal and serious injury crashes involving a motor vehicle and a pedestrian or bicyclist occurred between 2007 and 2014 in the Texas Department of Transportation Austin District. This study contributed to the field of research by developing four crash frequency and severity models for pedestrians and bicyclists to identify the factors associated with the frequency of crashes and the presence of more severe crashes across the census block groups in the Austin District. The models showed the important role of different variables in crash frequency and severity, including travel demand, commute behaviors, network characteristics, and sociodemographic features. Using the model results, areas of concern with the greatest potential for safety improvements were identified. The study results can help develop safety improvement interventions for vulnerable road users in the Austin District and exemplify how other transportation agencies can estimate pedestrian and bicycle crashes using their existing database and crowdsourced data. [ABSTRACT FROM AUTHOR]

Concerns regarding children's health and physical activity levels have prompted a growing interest in understanding the school mode choice decision. Walking and biking to school can help school-age children achieve recommended daily physical activity levels. The growing literature in this area has provided valuable insights but has often failed to adequately consider the influence of parents on children's decision making. This study aims to provide additional insights by examining the school mode choice with a focus on active travel and the role of parental effects. A multinomial logit model was estimated for children's school mode choice using the 2009 National Household Travel Survey with the add-on sample for Texas. A comprehensive set of variables, including individual and household characteristics, built and travel environment measures, and parental characteristics and attitudes, were found to be influential on the decision of active travel to school. Although the focus of this study is on children's school mode, a model examining parent's active travel was also estimated to provide a picture of parents and their own active travel decisions through a Poisson count regression model for the parents' non-motorized travel frequency (weekly). Findings strongly suggested that mothers' concerns regarding traffic conditions in the neighborhood can discourage children's active mode use. In contrast, fathers' work flexibility seemed to facilitate more non-motorized school travel. Similarly, many factors were important in determining non-motorized trip frequency. A flexible work environment, particularly for the mothers, was observed to increase the overall trip frequency of parents. The results from this study corroborate the findings from several earlier studies while also indicating new factors not previously identified. The work done in this study can be extended in several directions. One particularly interesting avenue of future research is to model the two decisions in a joint model to identify the causal direction while accounting for unobserved factors. [ABSTRACT FROM AUTHOR]

• Intent to use self-driving vehicles in Texas increased from 2015 to 2016. • The significance of demographic variables varied across the four cities. • Psychosocial and personality variables were significant in intent to use. • It is important to track and monitor attitudes towards automation. Early consistent measurement of intent to use automated vehicles will help explore the public's reactions, improve the knowledge base, and facilitate an understanding of the potential benefits that could be achieved. Adopting a car technology acceptance model (CTAM), online surveys were implemented in several Texas cities including 2016 survey of Dallas, Houston, and Waco, which is an extension of a prior 2015 survey study in Austin. Adding different geographic content provided an opportunity to assess trends and to obtain more robust results and different insights on the consumer acceptance and travel behavior impacts of self-driving vehicles. Following an extensive descriptive analyses, a multivariate model was estimated to examine the factors influencing intent to use in Texas cities. The results show an increase in intent to use from 2015 to 2016. Demographic variables mattered but to lesser extent compared to psychosocial variables of the CTAM, which were highly significant in predicting intent to use. Younger individuals, males and individuals with physical conditions that prohibiting them from driving had a higher likelihood of intent to use. Travel behavior characteristics were also important. For example, individuals owning a vehicle with highly automated features had a higher intention to use. The strongest associations with intent to use were observed for attitudes toward self-driving vehicles, performance expectation, perceived safety, and social influence. In moving forward, it will be important to continue to monitor and track the behavior with diverse populations, and build an evidence-based consensus through continuous measurement on intent to use automated vehicles. [ABSTRACT FROM AUTHOR]

Using Texas add-on sample data from the 2009 National Household Travel Survey, this study examines adult workers’ daily active choice decisions in the context of physical activity and attendant health benefits. The study looked at workers’ two choice behaviors: active activity and active travel. The first choice behavior, active activity, is developed as an ordered-response model based on the number of physically active recreational activities pursued during the workday. The second choice behavior, active travel, is developed as a binary-response model that examines workers’ active travel choices—whether or not the worker used any active mode of travel during the same workday. The study improves the understanding and knowledge of observed factors influencing workers’ physically active activity-travel behavior. The study also provides several observations regarding the role (and constraints) of employment in individuals’ active choices. Using a flexible copula modeling methodology, we explore the true correlation (or dependence) between the two behavior choices that could occur due to the presence of unobserved factors, suggesting a simultaneously low or simultaneously high propensity for being physically active across workers. The study findings suggest that transportation and public health policy makers can mutually benefit from encouraging workers to be physically active (from an activity and/or travel perspective). Overall, the study draws attention to the integrated nature of the public health and transportation fields, thereby providing a distinct view of active/inactive choice behavior. To our knowledge, this is the first study exploring a rich variety of components for workers’ active activity-travel behavior through a robust copula approach. [ABSTRACT FROM AUTHOR]

The basic principles of scarcity pricing as implemented in Texas's energy-only electricity markets, forward capacity markets can be implemented simultaneously under a ‘hybrid’ market structure that mutes most criticisms directed to both markets structures. This construct would protect load from extreme pricing years that are required under energy-only market design while providing a hedge for suppliers under adverse conditions created by deficiencies in market designs. [Copyright &y& Elsevier]

In the US, the rise in motorized vehicle travel has contributed to serious societal, environmental, economic, and public health problems. These problems have increased the interest in encouraging non-motorized modes of travel (walking and bicycling). The current study contributes toward this objective by identifying and evaluating the importance of attributes influencing bicyclists’ route choice preferences. Specifically, the paper examines a comprehensive set of attributes that influence bicycle route choice, including: (1) bicyclists’ characteristics, (2) on-street parking, (3) bicycle facility type and amenities, (4) roadway physical characteristics, (5) roadway functional characteristics, and (6) roadway operational characteristics. The data used in the analysis is drawn from a web-based stated preference survey of Texas bicyclists. The results of the study emphasize the importance of a comprehensive evaluation of both route-related attributes and bicyclists’ demographics in bicycle route choice decisions. The empirical results indicate that travel time (for commuters) and motorized traffic volume are the most important attributes in bicycle route choice. Other route attributes with a high impact include number of stop signs, red light, and cross-streets, speed limits, on-street parking characteristics, and whether there exists a continuous bicycle facility on the route. [ABSTRACT FROM AUTHOR]

Background: Active travel to and from a transit station may provide significant amounts of physical activity and improve health. The ease with which people can traverse the distance to the transit station may impede or support active travel. Therefore, transit stations that have features that are supportive of utilitarian physical activity would be desirable. This study aimed to characterize the built environment surrounding new light rail transit (LRT) stations in the City of Houston, Texas.Methods: In 2014, we used a series of systematic protocols and a standardized environmental audit instrument, the Analytic Audit Tool, to collect data on segments (streets) that surround 22 LRT stations that were being newly built. Using Geographic Information System (GIS), we assembled all the segments that intersect a 0.25-mile circular buffer around each station for the audit exercise. Several 3- to 4-member teams of trained auditors completed the audit exercise on a subset of these identified segments. Our analysis were descriptive in nature. We provided the frequency distributions of audited features across the study area. We also followed an original algorithm to produce several composite index scores for our study area. The composite index score is indicative of the prevalence of physical activity friendly/unfriendly features in the study area.Results: In all, we audited a total of 590 segments covering a total of 218 US Census blocks, and eight City of Houston super neighborhoods. Findings suggest the environment around the new LRT stations may not be supportive of physical activity. In general, the audited segments lacked land use integration; had abandoned buildings, had uneven sidewalks; were not bike-friendly, had minimal presence of public-recreational facilities that would support physical activity; and had significant physical disorder. Notably, certain attractive and comfort features were frequently to usually available.Conclusions: Current findings, which will be compared to follow-up audit data, can be useful for future researchers and practitioners interested in the built environment around LRT stations. [ABSTRACT FROM AUTHOR]