Building Self-Esteem in Elementary School Students: The Promising Benefits of Bibliotherapy

The purpose of this study was to explore the use of bibliotherapy as an intervention to enhance self-esteem in elementary school students. This study used a quasi-experimental design with two control groups and two experimental groups consisting of both boys and girls. Pre-test and post-test assessments were conducted, and an eight-session training program was implemented for the experimental groups. The training program involved using stories as the primary tool for intervention, which were categorized into four types, including stories aimed at enhancing self-esteem and alleviating pain. From the category of self-esteem stories, eight stories were selected and delivered over four weeks, with two 45-minute sessions per week. The collected data were analyzed using analysis of covariance (ANCOVA). Each session lasted two hours per week. The study found that both boys and girls in the experimental groups experienced a significant increase in self-esteem, with the effect size measure indicating that 87% and 71% of the variance in self-esteem could be attributed to the independent variable of bibliotherapy in boys and girls, respectively. A comparison of the effectiveness of bibliotherapy between male and female students in a quasi-experimental study revealed that girls had significantly higher levels of self-esteem compared to boys. The study suggests that presenting selected stories as an alternative approach to boosting self-esteem can provide valuable insights into children's self-esteem. These results are consistent with previous research that supports the effectiveness of bibliotherapy interventions in promoting self-esteem. The study highlights the potential of bibliotherapy as an effective intervention for enhancing self-esteem in elementary school students

Examining the persistence of telecommuting after the COVID-19 pandemic

This study focuses on the long-term impacts of COVID-19 on telecommuting behavior. We seek to study the future of telecommuting, in the post-pandemic era, by capturing the evolution of observed behavior during the COVID-19 pandemic. To do so, we implemented a comprehensive multi-wave nationwide panel survey (the Future Survey) in the U.S. throughout 2020 and 2021. A panel Generalized Structural Equation Model (GSEM) was used to investigate the effects of two perceptual factors on telecommuting behavior: (1) perceived risk of COVID-19; and (2) perceived telecommuting productivity. The findings of this study reveal significant and positive impacts of productivity and COVID-risk perception on telecommuting behavior. Moreover, the findings indicate a potential shift in preferences toward telecommuting in the post-pandemic era for millennials, employees with long commute times, high-income, and highly educated employees. Overall, a potential increase in telecommuting frequency is expected in the post-pandemic era, with differences across socio-economic groups

A Comparison of Online and In-Person Activity Engagement: The Case of Shopping and Eating Meals

You're viewing a past Journal from the Good Systems Grand Challenge team at The University of Texas at Austin from February 2020.Office of the VP for Researc

How Will Use of Autonomous Vehicles for Running Errands Affect Future Autonomous Vehicle Adoption and Ownership?

69A3551747116Transportation is experiencing disruptive forces in recent years. One key disruption is the development of autonomous vehicles (AVs) that will be capable of navigating roadways on their own without the need for human presence in the vehicle. In a utopian scenario, AVs may enter the transportation landscape and foster a more sustainable and livable ecosystem with shared automated electric vehicles (SAEV) serving mobility needs and eliminating the need for private ownership. In a more dystopian scenario, AVs would be personally owned by households \u2013 enabling people to live farther away from destinations, inducing additional travel, and roaming roadways with zero occupants. Concerned with the potential deleterious effects of having personal AVs running errands autonomously, this report aims to shed light on the level of interest in sending AVs to run errands and how that variable affects the intent to own an AV. Using data from a survey conducted in 2019 in four automobile-oriented metropolitan regions in the United States, the relationship is explored through a joint model system estimated using the Generalized Heterogeneous Data Model (GHDM) methodology. Results show that, even after accounting for socio-economic and demographic variables as well as latent attitudinal constructs, the level of interest in having AVs run errands has a positive and significant effect on AV ownership intent. The findings point to the need for policies that would steer the entry and use of AVs in the marketplace in ways that avoid a dystopian future

Attitudes and Behaviors Causal Relationships: Uncovering Latent Segments Within a Heterogeneous Population

69A3551747116This project aimed at unraveling the contemporaneous relationship that exists between attitudes and choice behaviors. Attitudes, perceptions, and preferences may shape behaviors; likewise, behavioral choices exercised by individuals may offer experiences that shape attitudes. While it is likely that these relationships play out over time, the question of whether attitudes affect behaviors or behaviors affect attitudes at a specific cross-section in time remains unanswered and a fruitful area of inquiry. Various studies in the literature have explored this question, but have done so without explicitly recognizing the heterogeneity that may exist in the population. In other words, the causal structure at play at any point in time may differ across individuals, thus motivating the development of an approach that can account for the presence of multiple segments in the population, each following a different causal structure. Results suggest that there is considerable heterogeneity in the population with the contemporaneous causal structures in which behaviors shape attitudes more prevalent than those in which attitudes affect choice behaviors. These findings have important implications for transport modeling and policy development

The Influence of Mode Use on Level of Satisfaction with Daily Travel Routine: A Focus on Automobile Driving in the United States

69A3551747116How does the extent of automobile use affect the level of satisfaction that people derive from their daily travel routine, after controlling for many other attributes including socio-economic and demographic characteristics, attitudinal factors, and lifestyle proclivities and preferences? This is the research question addressed by this study. In this study, data collected from four automobile-dominated metropolitan regions in the United States (Phoenix, Austin, Atlanta, and Tampa) are used to assess the impact of the amount of driving that individuals undertake on the level of satisfaction that they derive from their daily travel routine. This research effort recognizes the presence of endogeneity when modeling multiple behavioral phenomena of interest and the role that latent attitudinal constructs reflecting lifestyle preferences play in shaping the association between behavioral mobility choices and degree of satisfaction. The model is estimated using the generalized heterogeneous data model (GHDM) methodology. Results show that latent attitudinal factors representing an environmentally friendly lifestyle, a proclivity toward car ownership and driving, and a desire to live close to transit and in diverse land use patterns affect the relative frequency of auto-driving mode use for non-commute trips and level of satisfaction with daily travel routine. Additionally, the amount of driving positively affects satisfaction with daily travel routine, implying that bringing about mode shifts toward more sustainable alternatives remains a formidable challenge\u2014particularly in automobile-centric contexts

Socioeconomic Assessment

High-occupancy toll (HOT) lanes use dynamic pricing to manage demand for lane use and to maintain acceptable traffic flow and traffic speeds. However, minimum occupancy and toll payment requirements raise potential socioeconomic questions concerning disparate negative effects across demographic groups. The objective of this study was to improve the knowledge about socioeconomic aspects of congestion pricing by using the I-85 high-occupancy vehicle (HOV) to HOT conversion in Atlanta, Georgia, as a case study. To evaluate the effects across user groups, more than 1.5 million license plate records were collected during a 2–year period, 1 year before and 1 year after the conversion. Analyses compared collected records with state motor vehicle registration databases to identify the vehicles and link census block group level and marketing household level socioeconomic attributes. In addition, results of a 2-day travel diary survey conducted by Volpe 6 months before and 6 months after the conversion were assessed. This study used all three sources of data in parallel to undertake a socioeconomic evaluation of the HOV-to-HOT conversion. Whereas previous studies were built on only one data source with significantly smaller sample sizes, the use of three distinctive sources of socioeconomic data and an exceptionally large sample size advanced the understanding of the potential socioeconomic effects of managed lanes. Furthermore, with the noted advantages and disadvantages of these data sources, this study provided valuable insight for general demographic analysts. </jats:p

Idle Monitoring, Real-Time Intervention, and Emission Reductions from Cobb County, Georgia, School Buses

Georgia Institute of Technology researchers developed an idle detection and warning notification system that features Global Positioning System-based real-time tracking and a web-based user interface. Four hundred and eighty buses in the Cobb County (Georgia) School District were equipped with the idle detection system, and the research team provided bus dispatchers with a web-based system to track vehicle activity and provide notification of idle events exceeding 5 min. The idle detection and warning notification system can differentiate idling with engine on from key-on events with engine off, an important capability that sets it apart from previous systems that only detected key-on events. Idle reductions were monitored, and emissions and fuel savings were evaluated with the Environmental Protection Agency\u27s MOVES (Motor Vehicle Emission Simulator) model. The idle reduction that resulted from implementing the system was statistically significant—more than 6 min of idle reduction per bus per day. Greater idle reduction could be achieved with more stringent implementation of the system. The anti-idle program reduced total annual emissions of criteria pollutants (oxides of nitrogen, particulate matter, and carbon monoxide) by 1.82 tons and annual emissions of carbon dioxide by 53.3 tons. Implementation throughout the school district would conserve 6,400 gal of diesel fuel. Approximately 41,100 children riding the buses or attending schools served by the buses were positively affected by the idle reduction system